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Machine Learning (ML)
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Zahid H.

@zahidhasta

monthly-level-two.svg
5,0
4
3,9
3,9
100%

AI & EE (Electronics) | ML | LLM | NLP | Chatbots

$15 USD / jam
・
Bendera
Pakistan (8:16 AM)
・
Bergabung Desember 17, 2023
$15 USD / jam
・
I am an AI professional with a Master’s degree in Artificial Intelligence and Autonomous Systems, specializing in developing intelligent systems that drive automation and data-driven insights. Core Expertise: Machine Learning & Deep Learning: Proficient in supervised, unsupervised, and reinforcement learning, leveraging architectures like CNNs, RNNs, and Transformers for diverse applications. Natural Language Processing (NLP): Skilled in advanced NLP techniques using BERT and GPT for text analysis and conversational AI. Computer Vision: Expertise in object detection, image classification, and generative modeling with deep learning frameworks. Data Science & Big Data: Strong background in processing large datasets and building predictive models for actionable insights. Autonomous Systems: Experience in robotics and self-driving technology development. Electrical Engineering ( PCB, Micro controller, FPGA, Verilog ) Key Tools & Technologies: AI & Machine Learning: TensorFlow, PyTorch, Keras, Scikit-learn Big Data Technologies: Apache Spark, Kafka, AWS Kinesis Cloud Platforms: AWS, Azure, Google Cloud Data Visualization: Tableau, Power BI, Matplotlib Robotics Operating System (ROS) Programming Languages: Python, Matlab, Java, C++, SQL What I Offer: Tailored AI solutions to meet business needs End-to-end project development and support Expertise in deploying AI models for real-time applications Let’s collaborate to create innovative AI solutions that propel your business forward!
Verifikasi
Tepat waktu
100%
Sesuai anggaran
100%
Tingkat diterima
100%
Tingkat rekrut kembali
25%
Freelancer Python Developers Pakistan
Lihat semua Python Developers in Pakistan

Portofolio

Portofolio

12358725
In the realm of image processing and computer vision, enhancing the accuracy and efficiency of object detection models stands as a pivotal challenge, especially in environments characterized by varying conditions and data quality issues. This series of experiments embarked on an investigative journey to not only address these challenges but also to push the boundaries of what's achievable in image recognition and analysis. Through a meticulously designed workflow encompassing upscaling, enhancements, and data augmentation stages, our endeavor aimed to refine the performance of the YOLO V8 model, leveraging cutting-edge techniques such as ESRGAN, CLAHE, Gamma correction, and an array of augmentation strategies. The primary goal was to systematically evaluate and identify the most effective methods for improving the mean Average Precision (mAP50) and mAP50-95 metrics, which are crucial for assessing the accuracy of object detection models. By initiating with a baseline and progressive
Combination of aumgneting techniques
In the realm of image processing and computer vision, enhancing the accuracy and efficiency of object detection models stands as a pivotal challenge, especially in environments characterized by varying conditions and data quality issues. This series of experiments embarked on an investigative journey to not only address these challenges but also to push the boundaries of what's achievable in image recognition and analysis. Through a meticulously designed workflow encompassing upscaling, enhancements, and data augmentation stages, our endeavor aimed to refine the performance of the YOLO V8 model, leveraging cutting-edge techniques such as ESRGAN, CLAHE, Gamma correction, and an array of augmentation strategies. The primary goal was to systematically evaluate and identify the most effective methods for improving the mean Average Precision (mAP50) and mAP50-95 metrics, which are crucial for assessing the accuracy of object detection models. By initiating with a baseline and progressive
Combination of aumgneting techniques
11896409
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
11754839
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
11754800
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
11797359
text summarization model based on trasfer learning
12358725
In the realm of image processing and computer vision, enhancing the accuracy and efficiency of object detection models stands as a pivotal challenge, especially in environments characterized by varying conditions and data quality issues. This series of experiments embarked on an investigative journey to not only address these challenges but also to push the boundaries of what's achievable in image recognition and analysis. Through a meticulously designed workflow encompassing upscaling, enhancements, and data augmentation stages, our endeavor aimed to refine the performance of the YOLO V8 model, leveraging cutting-edge techniques such as ESRGAN, CLAHE, Gamma correction, and an array of augmentation strategies. The primary goal was to systematically evaluate and identify the most effective methods for improving the mean Average Precision (mAP50) and mAP50-95 metrics, which are crucial for assessing the accuracy of object detection models. By initiating with a baseline and progressive
Combination of aumgneting techniques
In the realm of image processing and computer vision, enhancing the accuracy and efficiency of object detection models stands as a pivotal challenge, especially in environments characterized by varying conditions and data quality issues. This series of experiments embarked on an investigative journey to not only address these challenges but also to push the boundaries of what's achievable in image recognition and analysis. Through a meticulously designed workflow encompassing upscaling, enhancements, and data augmentation stages, our endeavor aimed to refine the performance of the YOLO V8 model, leveraging cutting-edge techniques such as ESRGAN, CLAHE, Gamma correction, and an array of augmentation strategies. The primary goal was to systematically evaluate and identify the most effective methods for improving the mean Average Precision (mAP50) and mAP50-95 metrics, which are crucial for assessing the accuracy of object detection models. By initiating with a baseline and progressive
Combination of aumgneting techniques
11896409
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
I showcase my expertise in image processing and computer vision, particularly in the realm of camera calibration and distortion correction. Leveraging advanced techniques, I adeptly remove image distortion through meticulous calibration processes. By capturing multiple images of known calibration targets from diverse angles, I employ feature detection algorithms to identify key points essential for parameter estimation. Utilizing libraries like OpenCV, I meticulously compute intrinsic camera parameters and distortion coefficients, enabling precise distortion correction. Through rigorous validation, I ensure the accuracy of calibration results, guaranteeing that straight lines remain straight and objects maintain correct shapes post-correction. My portfolio reflects my proficiency in implementing calibration methodologies to enhance image quality, a skillset crucial for various applications in fields such as robotics, augmented reality, and computer-aided design.
Distortion remove from images
11754839
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
The primary objective of this research is to devise a comprehensive framework tailored to the creation of panoramic images from a multitude of individual photographs. This framework operates seamlessly as an automatic process, systematically analyzing the input images to discern their interconnections. Subsequently, it eliminates any redundant or overlapped areas that might exist within the collection and adeptly constructs a cohesive panoramic image, offering a holistic representation of the original scene. The proposed framework stands as an innovative solution in the realm of automated image organization and panoramic photography, providing a streamlined and efficient approach to seamlessly merge diverse images into a unified visual panorama.
Panorama 360 view
11754800
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
This project achieved the successful navigation of a TurtleBot3 through a simulated environment to locate Wally the Brick autonomously. Key accomplishments include the implementation of 2D LiDAR SLAM for mapping, custom decision-making logic for exploration, and efficient object detection using computer vision techniques. These efforts demonstrated the project's efficiency, with the robot efficiently exploring the environment and accurately detecting the brick. The novelty lies in the custom exploration strategy, offering a unique approach compared to standard ROS packages. While the project is robust and well-tested, there is room for improvement, such as enhancing the object detection to handle varying lighting conditions and optimizing the exploration strategy further. Future work could involve deploying a real TurtleBot3 in a physical environment, expanding the scope of autonomous tasks, and refining the project for real-world applications.
Autonomous navigation of robot
11797359
text summarization model based on trasfer learning
Perubahan disimpan
5.0 · 4 Reviews
Ulasan
Avatar Pengguna
Re-Run Colab Notebooks • $200 USD
A++++++++++++++++ Good job !
Krzysztof W.
@krzysztof36
•
Bendera
Kręczki, Poland
•
2 bulan yang lalu
Bagikan
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Looking for long-term python AI/ML Delevoper to small and medium projects • $40 USD
A+++++++++++++++++++++++
Krzysztof W.
@krzysztof36
•
Bendera
Kręczki, Poland
•
3 bulan yang lalu
Bagikan
Avatar Pengguna
Transformer Network Architecture Implementation • $350 USD
Very responsive, attentive, and punctual. I have requested him to do a likely difficult task and he did his best to help me out. Will continue to work with him.
Muhd Baqer M.
@mbaqer123
•
Bendera
Singapore, Singapore
•
3 bulan yang lalu
Bagikan
Avatar Pengguna
Photo Distortion Removal • $145 USD
good and fast work. patient man :)
Krzysztof W.
@krzysztof36
•
Bendera
Kręczki, Poland
•
3 bulan yang lalu
Bagikan
Pengalaman
Research Assistant
Mar, 2023 - Mar, 2024
•
1 tahun
NCAI
Mar, 2023 - Mar, 2024
•
1 tahun
I have worked on Augmented and virtual reality to preserve Intellectual Heritage.
Mar, 2023 - Mar, 2024
•
1 tahun
AI Developer
Apr, 2021 - Agu, 2023
•
2 tahun, 4 bulan
Thinktecq
Apr, 2021 - Agu, 2023
•
2 tahun, 4 bulan
I have work on Autonomous navigation of robot and detect the required object in indoor environment.
Apr, 2021 - Agu, 2023
•
2 tahun, 4 bulan
Edukasi
National University of Science and Technology
2022 - 2024
•
2 tahun
MS in Artificial intelligence and Autonomous Systems
Bendera
Pakistan
2022 - 2024
•
2 tahun
The University of Lahore
2017 - 2021
•
4 tahun
BS Electrical Engineering
Bendera
Pakistan
2017 - 2021
•
4 tahun
Kualifikasi
The quantum 2050, AI & technology workshop
2023
NUST
Have done workshop on quantum bit and artificial intelligence.
2023
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