birajaghoshal Goto Github PK

noisy_label

Code for the CVPR15 paper "Learning from Massive Noisy Labeled Data for Image Classification"

nonconformist

Python implementation of the conformal prediction framework.

notes

Resources to learn more about Machine Learning and Artificial Intelligence

notes-1

nsclc--lung-cancer-image-analytics

nuclei-detection

Different segmentation architecture for nuclei detection. Created Ensemble variant using SegNet and U-Net

nuclei_classification

A Nuclei classifier that uses active learning

oct_fluid_segmentation

odin-pytorch

Principled Detection of Out-of-Distribution Examples in Neural Networks

ooo-bayesian-introduction

organ_segmentation_analysis

Organ segmentation demo at MICCAI19 Bayesian Deep Learning for Medical Imaging tutorial

organsegc2f

A coarse-to-fine framework for organ segmentation from abdominal CT scan

organsegrstn

An end-to-end coarse-to-fine framework for organ segmentation

other_code

Miscellaneous code

paired_cell_inpainting

Self-supervised learning for microscopy images

pan-cancer-profiling

This repository contains the code to reproduce our exploratory analysis of a pan-cancer plasma proteomics dataset, including differential expression analysis and disease classification (https://doi.org/10.1038/s41467-023-39765-y). The data can be explored in the Human Protein Atlas: www.proteinatlas.org/humanproteome/disease.

pancancer

Building classifiers using cancer transcriptomes across 33 different cancer-types

pancreas-seg

Pancreas Segmentation in Abdominal CT Scans

panseer-cancerseek

papers

Papers for Summer 2018

papers-1

papers-2

Summaries of papers on machine learning, computer vision, autonomous robots etc.

patch-based-3d-fcn-for-brats-tumor-segmentation

patch-based-classification-of-breast-cancer-histology-images

petctcoseg_slicer

petctomics

Perform radiomics-oriented learning using PET, CT, or MRI images

plan-net

An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval

poison-mushrooms

A cost-sensitive neural network analysis for detecting edible vs poisonous mushrooms.

posterior-sampling-uq

posterior sampling (from the paper "deep bayesian inversion") for MRI uncertainty quantification and reconstruction

prediction-interval-nn

Confidence and prediction intervals for feedforward NNs and RNNs