《深度学习与计算机视觉》配套代码
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Updated
Nov 30, 2020 - Python
《深度学习与计算机视觉》配套代码
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Real-Time Semantic Segmentation in Mobile device
U-Net Biomedical Image Segmentation
Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.
Winning solution for the Kaggle TGS Salt Identification Challenge.
DATA-SCIENCE-BOWL-2018 Find the nuclei in divergent images to advance medical discovery
Official implementation of DoubleU-Net for Semantic Image Segmentation in TensorFlow & Pytorch (Nominated for Best Paper Award (IEEE CBMS))
A deep learning based approach for brain tumor MRI segmentation.
Dstl Satellite Imagery Feature Detection
Official Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)
Deep Learning sample programs using PyTorch in C++
A PyTorch implementation of image steganography utilizing deep convolutional neural networks
Segmentation of ID Cards using Semantic Segmentation
Code for "Quantized Densely Connected U-Nets for Efficient Landmark Localization" (ECCV 2018) and "CU-Net: Coupled U-Nets" (BMVC 2018 oral)
PyTorch Implementation of Stacked U-Nets (SUNets)
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