Proof-of-concept implementation for automated CBAM report
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Updated
Oct 31, 2023
Proof-of-concept implementation for automated CBAM report
Spatiotemporal encoder-decoder networks with attention for remote photoplethysmography (rPPG)
Remote Sensing Change Detection
An Image colorization algorithm using PatchGan and Convolution Block Attention Modules (CBAM)
Research Project in A3C reinforcement learning algorithm used for path finding mobile robots
Pytorch implementation of "Wavelet-based residual attention network for image super-resolution"
Developed a deep novel coupled profile to frontal face recognition network incorporating pose as an auxiliary information via attention mechanism (i.e., implemented a pose attention module).
This repository provides the official implementation of 'Learning to ignore: rethinking attention in CNNs' accepted in BMVC 2021.
The topic was from huawei cloud garbage classification competition.
This projected explored the effect of introducing channel and spatial attention mechanisms, namely SEN-Net, ECA-Net, and CBAM to existing CNN vision-based models such as VGGNet, ResNet, and ResNetV2 to perform the Facial Emotion Recognition task.
A minimal Tensorflow2.0 implementation of Resnet on CIFAR10 dataset.
training a classification model with xray14 dataset
pytorch implementation of several CNNs for image classification
Code for paper "Channel Pruning Guided by Spatial and Channel Attention for DNNs in Intelligent Edge Computing"
This is a torchvision style CNN models collection based on pytorch.
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