[CVPR 2024] "CFAT: Unleashing Triangular Windows for Image Super-resolution"

Courses, Articles and many more which can help beginners or professionals.

DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.

Collection of Papers and Trials on Deep Learning to aid EE design

A curated list of awesome hardware/chip design resources for deep learning

Implementation of Squeeze and Excitation Networks in Keras

Pytorch Pedestrian Attribute Recognition: A strong PyTorch baseline for pedestrian attribute recognition and multi-label classification.

Code for the paper "Improving Pedestrian Attribute Recognition With Weakly-Supervised Multi-Scale Attribute-Specific Localization", ICCV 2019, https://arxiv.org/abs/1910.04562.

Person Detection using HOG Feature and SVM Classifier

[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021

Curated list of papers on the topic of Pedestrian Detection

Pedestrian classification from photos using the Linear SVM and HOG features in INRIA dataset

Detects Pedestrians in images using HOG as a feature extractor and SVM for classification

Audio classification is a popular topic, here I implement several models using TenserFlow and Keras.

C++ Template Codes for Competitive Programming.

A curated list of awesome research papers, projects, code, dataset, workshops etc. related to virtual try-on.

Create an LSTM encoder-decoder model that will translate English sentences into French using Encoder-Decoder LSTM.

Solving Previous Year Questions of 6 Companies, by taking it as a challenge.

Simple Tensorflow implementation of "Squeeze and Excitation Networks" using Cifar10 (ResNeXt, Inception-v4, Inception-resnet-v2)

ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze the performance of active learning methods.

Notes and experiments on Bayesian regression

This directory contains a sample from the code which I wrote during my master thesis on Active Learning with Bayesian Neural Networks with Gaussian Processes. Two example scripts are provided which…