Israel Ochoa's starred repositories
skin-cancer-classification-machine-learning
This repository contains code to train the model, trained model and code to use the model. Interestingly, the code I used to remove hair from images and smooth them. This method increased the accuracy of the model from 71% to 86%.
SKNet_Pytorch
SKNet及3D SKConv非官方实现
SKNet-PyTorch
Nearly Perfect & Easily Understandable PyTorch Implementation of SKNet
Texture-Classification-using-Wavelet-CNN
Texture classification using wavelet CNN in google colab
skin-cancer-detection-and-segmentation
Segmentation and classification of skin cancer images using CNN
Skin-Cancer-Segmentation
This GitHub repository contains a Jupyter Notebook that implements skin cancer image segmentation using Deep learning techniques. The notebook provides a step-by-step guide on how to preprocess and analyze skin cancer images, and then use a convolutional neural network (CNN) to segment the images into different regions based on their tissue type
MultiResUNet
MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation
TensorflowDeepLabV3Plus-Image-Segmentation-Augmented-Skin-Cancer
TensorflowDeepLabV3Plus Image Segmentation for Skin-Cancer based on Online Augmentation
semantic-segmentation-skin
Deployment of a semantic segmentation neural network for skin cancer detection based on the FPN architecture.
Skin-Cancer-Segmentation-ISIC2018
skin lesion (Melanoma) segmentation using Unet and Mask_RCNN
Skin-Cancer-Lesion-Segmentation
Automatic Skin Lesion Segmentation using SegNet, a Deep Learning architecture with certain extra requirements. Keeping the pre- and post-processing of the photos to a minimum is the secondary goal. The dermoscopic pictures in the PH2 dataset, which are part of the limited amount of images used to train the proposed model, were manually segmented.
CCFBDCI-2021-Ultrasonic-Tumor-Segmentation-Rank1st
This is the source code of the 1st place solution for segmentation task (with Dice 90.32%) in 2021 CCF BDCI challenge.
MIS-R2UNet
A Tensorflow implementation of the Recurrent Residual U-Net for segmentation of retinal blood vessel and skin cancer images
CancelCancer
Segmentation of skin cancers
melanoma_segmentation
Segmentation of skin cancers on ISIC 2017 challenge dataset.
Skin_Lesions_Classification_DCNNs
Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification
Skin-Lesions-Detection-Deep-learning
Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification on HAM10000 dataset largescale data.
Illumination-based-Transformations-Skin-Lesion-Segmentation
This is the code corresponding to our CVPR ISIC 2020 paper.
Summer2025-Internships
Collection of Summer 2025 tech internships!
developer-roadmap
Interactive roadmaps, guides and other educational content to help developers grow in their careers.
build-your-own-x
Master programming by recreating your favorite technologies from scratch.
coding-interview-university
A complete computer science study plan to become a software engineer.