Ajinkya Kulkarni's Projects
Config files for my GitHub profile.
A collection of resources on bioimage analysis and related tools and techniques
Research code on Functional Tissue Units
A Python GUI-based framework for segmentation, tracking and cell cycle annotations of microscopy data
a generalist algorithm for cellular segmentation with human-in-the-loop capabilities
One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classification
Using Convolutional Neural Networks (CNNs) to classify biomedical images into different classes.
Automatically find issues in image datasets and practice data-centric computer vision.
Simulating Collatz's Conjucture
Image restoration for fluorescence microscopy
Segmentation of nuclei and cells from drosophila embryos from 3D stacks
Code Implementation for EmbedSeg, an Instance Segmentation Method for Microscopy Images
An implementation of unsupervised example of the Forward-Forward algorithm proposed by (Hinton, 2020)
Fluorescence Lifetime Ultimate Explorer (FLUTE) is a GUI for exploring and analyzing Fluorescence Lifetime Microscopy (FLIM) data
PyTorch implementation of Hinton's FF Algorithm with hard negatives sampling
:zap: Dynamically generated stats for your github readmes
Python program to generate NetworkX graphs from segmented images.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Library for Digital Pathology Image Processing
HistoQC is an open-source quality control tool for digital pathology slides
Interpretable Gland-Graph Networks