meghald Goto Github PK

about_me

Find all my professional details here. Please contact for collaborations at [email protected]

adelaidet

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

ai_in_healthcare

Includes all materials and codes related to the topic.

algorithms-for-computational-biology

android-samples

Samples demonstrating how to use Google Maps Android API v2.

autism_wacv.github.io

awesome-domain-adaptation

A collection of AWESOME things about domian adaptation

basictad

BasicTAD: an Astounding RGB-Only Baselinefor Temporal Action Detection

byol-pytorch

Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch

caltech_birds

A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.

d2_dataloader

data-structure-and-algorithm

Basic all the codes, I've learned till now. :)

deep-lesion

A deep learning framework for detecting lesions in CT scans from Deep Lesion dataset

detectron2_custom_loss_may2021

Detectron2 is FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks.

domain-adaptive-faster-rcnn-pytorch

Domain Adaptive Faster R-CNN in PyTorch

e2e-tad

[CVPR 2022] An Empirical Study of End-to-end Temporal Action Detection

everypixelmatters

Implementation of ECCV 2020 paper "Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector"

fmri_analysis

fms

Facebook based FMS complaint and redressal system

geoar_demo

AR Map

machine-learning--neural-network

machine-learning-for-biomedical-applications

meghald

Config files for my GitHub profile.

miccai-lits2017

liver segmentation using deep learning

mm_action_rec

Video Activity Recognition

neuroai-tuebingen

neurolab-unitue

nilearn-rsa

Applying RSA searchlight to face data.

o-cnn

This repository contains the code of our O-CNN paper.

plotneuralnet

Latex code for making neural networks diagrams