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Anam M.
@anammumtaz325
5,0
4
2,4
2,4
80%
Graphic Designer | Data Entry
$5 USD / óra
・
Pakistan (10:56 du.)
・
Ekkor csatlakozott: november 10, 2020
$5 USD / óra
・
I am expert in python, machine learning, image processing and graphic designing and data entry. I am having more than 5 years of experience in Data sciences, Artificial Intelligence and Graphic designing.
I can work on any type of machine learning projects. I can also work on graphics. I can design logo, postures and flyers .I can do any type of Data Entry in Excel and word.
Great to work with,Anam M, good at problem solving, experienced in coding and knowledgable.
i would highly recommend Anam to anyone who needs help with their work, the quality of work you will receive fromAnam is worth the money.
Good job.Thank you for your help.
Currently, I am working as a research assistant on a research project funded by Higher Education
Commission (HEC).
nov., 2018 - nov., 2020
•
2 év
Content Based Video Indexing and Retrieval (CBVIR).
szept., 2017 - szept., 2018
•
1 év
Bahria University
szept., 2017 - szept., 2018
•
1 év
My focal contributions were, 1) development of multiple
solutions using deep learning techniques (CNN & LSTM) for recognition of Urdu ligature, 2) Labelled
ground truth information.
szept., 2017 - szept., 2018
•
1 év
Tanulmányok
Bahria University
2016 - 2018
•
2 év
MS CS
Pakistan
2016 - 2018
•
2 év
Bahria University
2012 - 2016
•
4 év
BS CS
Pakistan
2012 - 2016
•
4 év
Végzettségek
Certified Associate in python programming
2020
Pakistan Software Export Board(PSEB),
Certified Associate in python programming by Pakistan Software Export Board(PSEB), July-2020
2020
Kiadványok
Recognition of Cursive Caption Text Using Deep Learning-A Comparative Study on Recognition Units
Springer, Cham
In this paper, we employ CNN for recognition of ligatures segmented from caption text and a combination of convolutional and recurrent neural networks for recognition of characters from text line images. Experiments are carried out on 16,000 text lines containing cursive Urdu text extracted from videos of various News channels. The experimental results demonstrate that analytical techniques are more robust as compared to the holistic techniques.
Ligature Recognition in Urdu Caption Text using Deep Convolutional Neural Networks
Best Paper award 14- International Conference on Emerging Technology 21-22 November (2018).
In this paper presents a caption text recognition system targeting cursive text. The technique relies on a holistic approach using ligatures as units of recognition. Data driven feature extraction techniques are employed using a number of pre-trained deep convolution neural networks. The networks are used as feature extractors as well as fine-tuned on the ligature dataset under study and realized high ligature recognition rates.
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