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aming's Projects

3d_denseseg icon 3d_denseseg

The implementation of 3D_DenseSeg for infant brain MRI segmentation

act icon act

Real-time 'Actor-Critic' tracking

ad3dmil icon ad3dmil

Attention Based Deep 3D Multiple Instance Learning

adelaidet icon adelaidet

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

adn icon adn

ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

advent icon advent

Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation

advsemiseg icon advsemiseg

Pytorch implementation of the paper "Adversarial Learning for Semi-supervised Semantic Segmentation," Wei-Chih Hung, Yi-Hsuan Tsai, Yan-Ting Liou, Yen-Yu Lin, and Ming-Hsuan Yang

ag-cnn icon ag-cnn

This is a reimplementation of AG-CNN. ("Thorax Disease Classification with Attention Guided Convolutional Neural Network","Diagnose like a Radiologist: Attention Guided Convolutional Neural Network for Thorax Disease Classification")

alice icon alice

NIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

amazing-semantic-segmentation icon amazing-semantic-segmentation

Amazing Semantic Segmentation on Tensorflow && Keras (include FCN, UNet, SegNet, PSPNet, PAN, RefineNet, DeepLabV3, DeepLabV3+, DenseASPP, BiSegNet)

anatomysketch-software icon anatomysketch-software

A medical image segmentation software supporting user interventions and user-defined funtion extention

angionet icon angionet

Semantic segmentation network for X-ray angiography images, based on Deeplabv3+

ann icon ann

semantic segmentation,pytorch,non-local

attention-gated-networks icon attention-gated-networks

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

attention-module icon attention-module

Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"

attentiondeepmil icon attentiondeepmil

Implementation of Attention-based Deep Multiple Instance Learning in PyTorch

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