Shubham Innani's Projects
Agriculture-Vision Dataset, Challenge and Workshop (CVPR 2020)
Artificial Neural Networks Lab Session
This repository contains the codes and instructions to use the trained models for all the four datasets described in the paper : 'Script Identification in Natural Scene Image and Video Frame using Attention based Convolutional-LSTM Network'
Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering
A generalizable application framework for segmentation, regression, and classification using PyTorch
Library for Digital Pathology Image Processing
Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.
HoVer-Net inference code for simultaneous nuclear segmentation and classification
Deep learning aids prediction of IDH mutation status from histopathological whole slide images (WSI)
Code for the im4MEC model described in the paper 'Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts'.
library for weak whole slide learning with attention to compress and classify whole slide images
OpenSlide Patch Manager
Fusing Histology and Genomics via Deep Learning - IEEE TMI
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Open source package for Survival Analysis modeling
Survival Convolutional Neural Networks
Two stage Framework for Skin Lesion Segmentation and Classification