Cinnabar2

Cinnabar2's Stars

• Tan-995120332/OCT_flask_APP

  OCT Classification web demo

  Language:Python3

• weinajin/multimodal_explanation

  Generating and Evaluating Post-Hoc Explanation from Deep Neural Networks for Multi-Modal Medical Image Analysis Tasks

  Language:Jupyter Notebook222

• jiongchengli/1st-in-MICCAI-GAMMA-2021-challenge

  Language:Python41

• jesseLiu2000/Multimodel_Sarcasm_Detection

  Here is my undergraduate thesis (2022.6)

  Language:Python232

• aj1365/MultiModelCNN

  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.

  Language:Jupyter Notebook136

• chencodeX/Bilinear_CNN_dog_classifi

  tensorflow->BCNN + pytorch -> vgg16/resnet/BCNN

  Language:Python9228

• Xuegang-S/MMP-GCN

  Multi-center and Multi-channel Pooling Graph Convolutional Network

  Language:Python132

• smilell/AG-CNN

  The model of "Attention Based Glaucoma Detection: A Large-scale Database with a CNN Model" (CVPR2019)

  6710

• bionlplab/GlaucomaNet

  A deep-learning algorithm for the diagnosis of primary open-angle glaucoma from fundus photographs

  Language:Python4

• jinglescode/ssvep-multi-task-learning

  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-independent solution, desirable for clinical diagnostics. A stepping stone for an objective assessment of glaucoma patients’ visual field.

  Language:Python354

• ahmed1996said/gardnet

  Source code for GARDNet: Robust Multi-View Network for Glaucoma Classification in Color Fundus Images

  Language:Jupyter Notebook106

• RealMarco/GlaucomaRecognition

  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.

  Language:Jupyter Notebook5

• LucasNPrice/Multi-Input-ResNet

  Multi-input, multi-modal (image, audio) ResNet

  Language:Python2

• YaoZhang93/MAML

  [MICCAI 2021] The official code for "Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation"

  Language:Python436

• Bharathgc/Evaluating-Fusion-points-for-multi-stream-networks-handling-cross-modal-data

  This project uses RGB and Depth images as input into two different convolutional network of same architecture (namely VGGNet, RESNet, AlexNet) and fuses them

  Language:Python114

• njustkmg/OMML

  Multi-Modal learning toolkit based on PaddlePaddle and PyTorch, supporting multiple applications such as multi-modal classification, cross-modal retrieval and image caption.

  Language:Python56198

• lizoyu/DmCNN

  Dual-modal Convolutional Networks for Progression of Mild Cognitive Impairment into Alzheimer's Disease

  Language:Python93

• maheshgonella/Digestive-System-Pathological-Image-Classification-using-Dual-Stage-CNN-

  Language:Python2

• josedolz/HyperDenseNet_pytorch

  Pytorch version of the HyperDenseNet deep neural network for multi-modal image segmentation

  Language:Python7712

• RBirkeland/MVCNN-PyTorch

  Language:Python9934

• liyuan24/MHBNN-PyTorch

  Pytorch version of multi-view harmonized bilinear network for 3D object recognition

  Language:Jupyter Notebook234

• scp19801980/Remote-sensing-scene-classification

  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 fusion was proposed to fuse the extracted features of different branches.

  Language:Python3810

• SunNoJJ/MultimodalGlaucomaGrading

  Language:Python1

• astridflorio/Image-Reconstruction-from-multiple-OCT-Partial-Images

  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 tooth fully to observe tooth decay in-between teeth, since this area cannot be accessed directly, unlike with X-rays. This project attempts to reconstruct a 3D image of a tooth from partial 2D images taken from the side of a tooth which are normally accessible. Various techniques were explored both in terms of image capture and image registration.

  Language:MATLAB94

• benjimaclellan/OCT-Image-Reconstruction

  A simple GUI for reconstructing SD-OCT images

  Language:Python41

• Davidczy/SupCon_GAMMA

  Language:Python42

• hanmenghan/TMC

  The project page of paper: Trusted Multi-View Classification [ICLR'2021 paper]

  Language:Python21943

• yc541/ENetFall

  EfficientNet based fall detection using channel state information

  Language:Python2

• Sudhandar/EfficientNet-Attention-in-a-Siamese-Network

  Siamese neural network based Covid-19 Pneumonia classification using EfficientNet with attention mechanism

  Language:Jupyter Notebook83

• pbizopoulos/comprehensive-comparison-of-deep-learning-models-for-lung-and-covid-19-lesion-segmentation-in-ct

  Language:TeX132