abhijitmahalle
Software Engineer at Stellantis. Computer Vision, Machine Learning, and Robotics Software Development
StellantisDetroit Metropolitan Area
abhijitmahalle's Stars
SimplifyJobs/Summer2024-Internships
Collection of Summer 2024 tech internships!
williamfiset/Algorithms
A collection of algorithms and data structures
aladdinpersson/Machine-Learning-Collection
A resource for learning about Machine learning & Deep Learning
xizhengszhang/Leetcode_company_frequency
Collection of leetcode company tag problems. Periodically updating.
NVlabs/neuralangelo
Official implementation of "Neuralangelo: High-Fidelity Neural Surface Reconstruction" (CVPR 2023)
ifzhang/FairMOT
[IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking
titu1994/Image-Super-Resolution
Implementation of Super Resolution CNN in Keras.
knockcat/Leetcode
This Repository Contains All My Solved Leetcode Problems.
erykml/medium_articles
Scripts/Notebooks used for my articles published on Medium
jariasf/CS231n
My assignment solutions for CS231n - Convolutional Neural Networks for Visual Recognition
mantasu/cs231n
Shortest solutions for CS231n 2021-2024
uzh-rpg/e2calib
CVPRW 2021: How to calibrate your event camera
bwiens/leetcode-python
Solving problems with python
chintan1995/Image-Denoising-using-Deep-Learning
mingstellar/CS231n-Spring-2021
My assignments for Stanford CS231n in Spring 2021
nikhilroxtomar/Human-Image-Segmentation-with-DeepLabV3Plus-in-TensorFlow
DeepLabV3+ with squeeze and excitation network for human image segmentation in TensorFlow 2.5.0
ahmedmoawad124/Self-Driving-Vehicle-Control
Self Driving Cars Longitudinal and Lateral Control Design
supperted825/FairMOT-X
FairMOT for Multi-Class MOT using YOLOX as Detector
mirzaim/cs231n
Note and Assignments for CS231n: Convolutional Neural Networks for Visual Recognition
ved27/RED-net
RED30 implementation
Jen-Jon/MalleNet-PyTorch
Unofficial PyTorch implementation of 'Fast and High-Quality Image Denoising via Malleable Convolutions'.
Shakib-IO/Diminishing_Image_Noise_Using_Deep_Learning
Denoising an image is a classical problem that researchers are trying to solve for decades. In earlier times, researchers used filters to reduce the noise in the images. They used to work fairly well for images with a reasonable level of noise. However, applying those filters would add a blur to the image. And if the image is too noisy, then the resultant image would be so blurry that most of the critical details in the image are lost. There has to be a better way to solve this problem. As a result, I have implemented several deep learning architectures that far surpass the traditional denoising filters. In this blog, I will explain my approach step-by-step as a case study, starting from the problem formulation to implementing the state-of-the-art deep learning models, and then finally see the results.
Arnab-0901/Classification-Algorithms
Implementation of Logistic Regression with Pandas & Numpy
lizenan/Monkey-Species-Classification
inception v3, tensorflow, sklearn, transfer learning, kaggle dataset
n-minhhai/monkey-species
Achieved 75% accuracy in multi-class image classification of 10 monkey species using a 5-layer CNN. Implemented in Python, PyTorch.
OlafChrist-github/Image-Denoising-using-Keras
yxie/Face-recognition
Project 1 for ENEE633 Statistical Pattern Recognition course at UMD
KACHAPPILLY2021/Follow_me_ModalAI-m500
FOLLOW ME mode implementation for ModalAI m500 using ROS 1 and C++.
p-akanksha/face_recognition
Classifiers for face recognition
rutujagurav/10-Monkey-Species-Classification-Transfer-Learning
Multi-class classification of 10 species of monkeys using Transfer Learning