zy20030535
My name is zach jerzy, I am a college student and most of the time have to study. lenjoy rap and dancing, as well as playing basketball.
zy20030535's Stars
ellisdg/3DUnetCNN
Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
MedMNIST/MedMNIST
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
alexandonian/pretorched-x
Pretrained Image & Video ConvNets and GANs for PyTorch: NASNet, ResNeXt (2D + 3D), ResNet (2D + 3D), InceptionV4, InceptionResnetV2, Xception, DPN, NonLocalNets, R(2+1)D nets, MultiView CNNs, Temporal Relation Networks, BigGANs StyleGANs, etc.
junqiangchen/LiTS---Liver-Tumor-Segmentation-Challenge
LiTS - Liver Tumor Segmentation Challenge
neuro-ml/resnet_cnn_mri_adni
Code for Residual and Plain Convolutional Neural Networks for 3D Brain MRI Classification paper
Small-Years/MiNi_Table_Demo
小程序表格实现/排班时间表
hasibzunair/3D-image-classification-tutorial
Tutorial to train a 3D CNN to predict presence of pneumonia from CT scans.
xyj77/MCF-3D-CNN
Temporal-spatial Feature Learning of DCE-MR Images via 3DCNN
regnerus/keras-alzheimers-3d-conv
Implementation of a 3D Convolutional Neutral Network in Keras on an Alzheimers Disease MRI Scan Dataset
bthyreau/hippodeep
Brain Hippocampus Segmentation
MinhazPalasara/keras
Theano-based Deep Learning library (convnets, recurrent neural networks, and more).
zhenweishi/QMITH
MRI-based quantitative measure of intra-tumoral heterogeneity in breast cancer
BigDaMa/DFS
LijunRio/Spine-cobb-angle-measurement
Using Opencv to calculate cobb angles
cyrillelanchua/Cobb_Angle_calculator
Automatic cobb angle detection using the YOLO neural network.
plapa/prostatex-thesis
rhythm92/CNN3D_Medical
3D Convolutional neural network for medical image segmentation
christinajiang/3D-Convolutional-Neural-Network
3D CNN for 3D image classification
hugegene/3D-CNN-on-PROSTATEx2
arpitmaheshwari213/Epitome-Extraction-and-Tumour-Classification-from-MRIs-of-Brain
A CNN based classification model for 3D NIfTI MRIs of the brain.
clabat9/MRI-Imaging-Classification-via-Concatenated-Neural-Network-Architectures-and-Distributed-Stochastic-
Reference Papers: "A framework for parallel and distributed training of neural networks", Simone Scardapane and Paolo Di Lorenzo , NEURAL NETWORK 91 (2017) "Stochastic Training of Neural Networks via Successive Convex Approximations", Simone Scardapane and Paolo di Lorenzo, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2018) "Distributed Stochastic Nonconvex Optimization and Learning based on Successive Convex Approximation", Paolo Di Lorenzo and Simone Scardapane, ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS (2019)
LuisRondoCuevas/Brain-Tumor-VSegmentation-Using-3D-CNN
In this work, two neural networks architectures based on the Unet network have been designed and trained to automatically segment different tumor substructures using the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2020 training dataset.
radiology-guru/cobb-angles
andreaccioly/3DCNN-MRI
Cerebral Microbleeds (CMB) diagnostic of 3D SWI-MRI using Spatial Pyramid Pooling modified 3D CNNs
deepz123go/Multiple-Pooling-in-Convolutional-Neural-Networks-Max-Range-Pooling-
Model Architecture consist of a convolution layer followed by a Max Pooling layer. The convolution layer is used to create minimum pooling layer, which in turn is subtracted from a max pool layer to obtain a range pooling layer. The max pooling layer and range pooling layers are concatenated to get the final pooling layer.
haohao12321/3D-CNN-for-HCC
harris2012/mini-program-paiban
微信小程序 排班
holdfire/TF2Learning
learning paddlepaddle from a CV course
zy20030535/Medical_Imaging
CNNs and ML regression methods for 3D brain MRI segmentation and patient age regression
zy20030535/Multiclass-Classification-on-STL-10-dataset-using-FineTuned-Resnet50-and-SVM-Classifier
a) Features extracted from the last fully-connected layer of pretrained Rsenet50 on ImageNet dataset is used to train a multiclass SVM classifier on STL-10 dataset