3d-cnn-model

Here are 9 public repositories matching this topic...

WAMAWAMA / WAMA_Modules

A PyTorch Computer Vision (CV) module library for building n-D networks flexibly ~

image video pytorch transformer pretrained-models attention-mechanism 3d-models medical-image-analysis 3d-densenet 3d-resnet 3d-cnn-model 3d-vgg

Updated Oct 4, 2024
Python

TomStog / Infrared-SpO2

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The dataset used for the "A non-contact SpO2 estimation using video magnification and infrared data" publication

python video linear-regression cnn dataset transformer infrared photoplethysmography eulerian-video-magnification spo2 generalized-additive-models video-magnification contactless infrared-images cnn-regression 3d-cnn-model vivit multisource-data

Updated Jun 27, 2024
Python

meghana-kshirsagar / 3DCNN_protein_structures

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3D CNN for protein structures

protein-structure protein 3d-convolutional-network 3d-cnn 3d-cnn-model

Updated Nov 14, 2022
Jupyter Notebook

dinaYriad / Action-Recognition

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This project involves the identification of different actions from video clips where the action may or may not be performed throughout the entire duration of the video. This is done using two CNN models which are 3D-CNN and LSTM models.

lstm-model action-recognition video-action-recognition 3d-cnn-model

Updated Aug 31, 2020
Jupyter Notebook

Monesh-97 / Multi-Label-Prediction-For-videos-using-Zero_Shot_Learning

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Multi-Label-Prediction-For-videos-using-Zero_Shot_Learning

computer-vision zero-shot-learning ucf101-dataset tensorboard-projector 3d-cnn-model

Updated May 2, 2023
Jupyter Notebook

srija-cell / MODELLING-MORPHOGENESIS-IN-3D-NEURAL-CELLULAR-AUTOMATA

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The objectives of this project are: Developing an extension of the methodology described in the paper “Growing Neural Cellular Automata” to facilitate complex structure generation in three dimensions and to simulate the growth of multicellular structure starting from a single cell.

cellular-automata voxels 3d-cnn-model

Updated May 21, 2023
Python

vishal815 / Deep-Learning-Models-for-3D-MRI-based-Brain-Tumor-Segmentation-using-Seg-Net-V--Net-and-U-Net

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This project focuses on the segmentation of brain tumors in 3D MRI images using Convolutional Neural Network (CNN) models. The research compares the performance of SegNet, V-Net, and U-Net architectures for brain tumor segmentation and evaluates them based on complexity, training time, and segmentation accuracy.