Official Pytorch Code base for "MobileUtr: Revisiting the relationship between light-weight CNN and Transformer for efficient medical image segmentation"

3D virtual staining with 2D and 2.5D U-Nets

An example of easytorch implementation on retinal vessel segmentation.

3D cerebrovascular volume segmentation in Pytorch.

Model training code for "A seasonally invariant deep transform for visual terrain-relative navigation"

U-Net

Land cover classification in Tanzania using ensemble labels and high resolution Planet NICFI basemaps and Sentinel-1 time series.

Monte Carlo dropout method for uncertainty quantification in image segmentation

Segmentation of cancerous tumors using Mamba. Code, resources, and paper provided. We manage to make a small (42k param) model that can segment pretty well.

Transforming 2D images into 3D semantically segmented scenes using innovative CNN architecture and COLMAP reconstruction.

Utilizing U-NET deep-learning to deconvolve Structured Illumination Microscopy (SIM) Images. A clean and concise python implemenation.

This research work basically highlights my undergrad thesis works. In my thesis, I have worked on the BraTS 2020 dataset. My total journey of thesis from building various models to writing paper is presented here.

MICCAI2019: 3D U2-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation

Entries for the 2023 5th National College Student Integrated Circuit EDA Elite Challenge. SoC chip physical layout static IR drop prediction project based on methods such as image processing and NLP unsupervised learning.

crystal structure analysis with RHEED and ML

Modular PyTorch U-Net model

Project outside of course scope at (BSc) Machine Learning and Data Science education programme. Colab between NGI and DIKU at University of Copenhagen.

U-Net based segmentation of CRC tiles and classification for nodal status

Implementation of U-net and pipeline of changing color on human hair.

Machine learning algorithm that identifies how many cells appear in a given microscopy image with a corresponding segmentation mask