BCDU-Net : Medical Image Segmentation
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Updated
Jan 30, 2023 - Python
BCDU-Net : Medical Image Segmentation
HDR image reconstruction from a single exposure using deep CNNs
This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.
Deep Learning sample programs using PyTorch in C++
Deep Learning-based Clustering Approaches for Bioinformatics
anomaly detection by one-class SVM
This is implementation of convolutional variational autoencoder in TensorFlow library and it will be used for video generation.
SegNet-like Autoencoders in TensorFlow
[SIGGRAPH Asia 2017] High-Quality Hyperspectral Reconstruction Using a Spectral Prior
This projects detect Anomalous Behavior through live CCTV camera feed to alert the police or local authority for faster response time. We are using Spatio Temporal AutoEncoder and more importantly three models from Keras ie; Convolutional 3D, Convolutional 2D LSTM and Convolutional 3D Transpose. 👮♂️👮♀️📹🔍🔫⚖
A convolutional autoencoder made in TFLearn.
Unsupervised deep learning system for local anomaly event detection in crowded scenes
Gaussian Mixture Convolutional AutoEncoder applied to CT lung scans from the Kaggle Data Science Bowl 2017
Implementation of a convolutional auto-encoder in PyTorch
Convolutional autoencoder for encoding/decoding RGB images in TensorFlow with high compression ratio
A convolutional auto-encoder for compressing time sequence data of stocks.
Image Compression on COCO Dataset using Convolution AutoEncoders
Use auto encoder feature extraction to facilitate classification model prediction accuracy using gradient boosting models
Image Denoising Using Deep Convolutional Autoencoder with Feature Pyramids
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