algo_and_data_structure

Algorithms and Data Structures

byolmed3d

BYOL3d for SElf-Supervised Analysis of MEdical Videos (SESAME)

cameracalibrationusing3dobject

Calibration of Camera using a 3D object model

canny

Adaptive Threshold Algorithm for Canny Edge Detector

cifar2png

Convert CIFAR-10 and CIFAR-100 datasets into PNG images

classic-ai

cnn_tf

Convolutional Neural Networks using Tensorflow

codalab_instructions

compression

Data Compression Techniques in C and Matlab

computer_vision

Matlab Implementation of Harris-Laplace and Harris-Affine Interest Point Detection Algorithms

consysmodification

A little modification of control systems function in MATLAB to make life a little easier

deep_learning

Notes on deep learning

deep_learning_docker_images

detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

dsp

Coding DSP functions with C, Python & MATLAB

easy-faster-rcnn-pytorch

An easy implementation of Faster R-CNN (https://arxiv.org/pdf/1506.01497.pdf) in PyTorch.

face-emo-rec

face-emotion-recognition

Setting up a Hugging Face Spaces Demo using Streamlit

few-shot-semantic-segmentation-papers

Few Shot Semantic Segmentation Papers

gradient_accumulation

Optimizer with Gradient Accumulation and Custom Learning Rate Scheduler

graphcolouring

Graph Colouring Problem using Constraint Satisfaction Problem in C

hobby_projects

idx2numpy_array

Convert data in IDX format in MNIST Dataset to Numpy Array using Python

image_processing_in_c_matlab_py

Basic Image Processing in C, Matlab and Python

jpop_net

keras_load_pretrained_model_without_loading_the_model

Often it is required to initialize the layers of a model with the weights of a pre-trained model, but also freeing the memory occupied by the pre-trained model becomes necessary in a low GPU memory nevironment

kmeansplusplusclustering

K-Means++ Clustering using Gap Statistic for determining optimal value of K in Python

lars_pytorch

Implementation of LARS Optimizer in PyTorch

mrnet

PyTorch implementation of the MRNet paper, developed for the MRNet Competition hosted by the Stanford ML Group

neuralnets

Implementation of various state-of-the-art architectures in Tensorflow, Keras and Python