sadiksatir's Stars
Asabeneh/30-Days-Of-JavaScript
30 days of JavaScript programming challenge is a step-by-step guide to learn JavaScript programming language in 30 days. This challenge may take more than 100 days, please just follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
microsoft/AI-For-Beginners
12 Weeks, 24 Lessons, AI for All!
matterport/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
facebookresearch/detr
End-to-End Object Detection with Transformers
abraunegg/onedrive
OneDrive Client for Linux
udacity/deep-reinforcement-learning
Repo for the Deep Reinforcement Learning Nanodegree program
LuNiZz/siber-guvenlik-sss
SSS sorulari burada...
udacity/ud851-Exercises
udacity/ud851-Sunshine
NVIDIA/CUDALibrarySamples
CUDA Library Samples
jplag/JPlag
State-of-the-Art Source Code Plagiarism & Collusion Detection
NVIDIA-developer-blog/code-samples
Source code examples from the Parallel Forall Blog
aarcosg/traffic-sign-detection
Traffic Sign Detection. Code for the paper entitled "Evaluation of deep neural networks for traffic sign detection systems".
addy1997/Robotics-Resources
List of commonly used robotics libraries and packages
woctezuma/finetune-detr
Fine-tune Facebook's DETR (DEtection TRansformer) on Colaboratory.
paclopes/HungarianGPU
An GPU/CUDA implementation of the Hungarian algorithm
Allopart/rbpf-gmapping
MatLab implementation of a Rao-Blacwellized Particle Filter for Grid- Based FastSlam
xgfs/node2vec-c
node2vec implementation in C++
shakti365/soft-actor-critic
TF2 Implementation of the Soft Actor-Critic Algorithm
salihmarangoz/RobotMappingCourse
Solutions to assignments of Robot Mapping Course WS 2013/14
z1223343/TCP-communication-between-Python-and-Maltab-Simulink
This repo summaries the method that I used in my work to build communication between Simulink model and Python
Vicondrus/Roadster
In this project, a traffic sign recognition system, divided into two parts, is presented. The first part is based on classical image processing techniques, for traffic signs extraction out of a video, whereas the second part is based on machine learning, more explicitly, convolutional neural networks, for image labeling.
MinoruHenrique/data_augmentation_yolov7
Apply data augmentation techniques on YOLO v7 format dataset.
thibaudmartinez/node2vec
An efficient node2vec implementation in C++ with a Python API.
woctezuma/detr
Finetune DETR.
canozcivelek/traffic-sign-recognition
Traffic signs can be identified with machine learning
woctezuma/VIA2COCO
Convert annotations from VIA to COCO.
LaurentVeyssier/Landmark-detection-and-robot-tracking
Apply Simultaneous Localization And Mapping (SLAM) to derive landmark positions and robot localization from measures made by the robot
muneeb706/Sparse-Matrix-Vector-Mul
Parallelized Sparse Matrix Vector multiplication using OpenMP
sancarder/lt2216-vt19