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Generating and Evaluating Post-Hoc Explanation from Deep Neural Networks for Multi-Modal Medical Image Analysis Tasks
Here is my undergraduate thesis
Here are the codes for the "Swin Transformer and Deep Convolutional Neural Networks for Coastal Wetland Classification using Sentinel-1, Sentinel-2, and LiDAR Data" paper.
tensorflow->BCNN + pytorch -> vgg16/resnet/BCNN
Multi-center and Multi-channel Pooling Graph Convolutional Network
The model of "Attention Based Glaucoma Detection: A Large-scale Database with a CNN Model" (CVPR2019)
A deep-learning algorithm for the diagnosis of primary open-angle glaucoma from fundus photographs
Using multi-task learning to capture signals simultaneously from the fovea efficiently and the neighboring targets in the peripheral vision generate a visual response map. A calibration-free user-i…
Source code for GARDNet: Robust Multi-View Network for Glaucoma Classification in Color Fundus Images
This is the code of Glaucoma Grading from Multi-Modality imAges. Task 1 is glaucoma grading, task 2 is macular fovea localization, and task 3 is optic disc/cup segmentation.
Multi-input, multi-modal (image, audio) ResNet
[MICCAI 2021] The official code for "Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation"
This project uses RGB and Depth images as input into two different convolutional network of same architecture (namely VGGNet, RESNet, AlexNet) and fuses them
Multi-Modal learning toolkit based on PaddlePaddle and PyTorch, supporting multiple applications such as multi-modal classification, cross-modal retrieval and image caption.
Dual-modal Convolutional Networks for Progression of Mild Cognitive Impairment into Alzheimer's Disease
Pytorch version of the HyperDenseNet deep neural network for multi-modal image segmentation
Pytorch version of multi-view harmonized bilinear network for 3D object recognition
For the remote sensing scene classification task in complex background, we proposed a lightweight convolutional neural network with bilinear feature extraction structure. The idea of branch feature…
Optical coherence tomography (OCT) is an optical imaging method. It can be considered analogous to ultrasound imaging with greater resolution but lower penetration depth. OCT cannot penetrate the t…
A simple GUI for reconstructing SD-OCT images
The project page of paper: Trusted Multi-View Classification [ICLR'2021 paper]
EfficientNet based fall detection using channel state information
Siamese neural network based Covid-19 Pneumonia classification using EfficientNet with attention mechanism