Name: Kuldeep Purohit
Type: User
Company: Phiar Technologies
Bio: AI Research Engineer @ Google, working in Computer Vision and Deep Learning. Earlier: AI Researcher @ Phiar, Postdoc @ Michigan State University, Ph.D @ IIT
Location: Mountain View, California, USA
Blog: https://kuldeeppurohit.github.io/
Kuldeep Purohit's Projects
List of all AI related learning materials and practical tools to get started with AI apps
Best Practices, code samples, and documentation for Computer Vision.
After watching all the videos of the famous Standford's CS231n course that took place in 2017, i decided to take summary of the whole course to help me to remember and to anyone who would like to know about it. I've skipped some contents in some lectures as it wasn't important to me.
Code for the paper "Depth-guided dense dynamic filtering network for bokeh effect rendering", ICCV Workshop 2019
Image Deblurring using Generative Adversarial Networks
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
DenseNet Implementation in Tensorflow
PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)
Just a collection of essential set of codes that can be plugged in at needed places
How to write cuda kernels or c functions in pytorch, especially for former caffe users.
Config files for my GitHub profile.
Learn OpenCV : C++ and Python Examples
This repository contains the solutions and explanations to the algorithm problems on LeetCode. Only medium or above are included. All are written in C++/Python and implemented by myself. The problems attempted multiple times are labelled with hyperlinks.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
All Algorithms implemented in Python
PyTorch wrapper for FFTs
Geometric Deep Learning Extension Library for PyTorch
Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.
Results of AAAI2020 "Region-Adaptive Dense Network for Efficient Motion Deblurring"
This provides a sandbox simulator for training a self-driving car. This uses Unity for simulation and Python with Keras and Tensorflow for training. Recently updated to work on Python 3.4+ and Keras 2+
Speech recognition module for Python, supporting several engines and APIs, online and offline.
Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks