Remote Sensing Change Detection
-
Updated
Dec 3, 2023 - Python
Remote Sensing Change Detection
Pytorch implementation of "Wavelet-based residual attention network for image super-resolution"
Proof-of-concept implementation for automated CBAM report
Research Project in A3C reinforcement learning algorithm used for path finding mobile robots
Spatiotemporal encoder-decoder networks with attention for remote photoplethysmography (rPPG)
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.
The topic was from huawei cloud garbage classification competition.
An Image colorization algorithm using PatchGan and Convolution Block Attention Modules (CBAM)
A minimal Tensorflow2.0 implementation of Resnet on CIFAR10 dataset.
pytorch implementation of several CNNs for image classification
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.
training a classification model with xray14 dataset
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.
Add a description, image, and links to the cbam topic page so that developers can more easily learn about it.
To associate your repository with the cbam topic, visit your repo's landing page and select "manage topics."