Pinned Repositories
data_set_end_to_end
employee-leave-management
Ongoing project Demo
jetson-multicamera-pipelines
library-management-spring
Library Management System in Spring MVC
Local-Planner-Visualization-Project
An all-in-one application to visualize multiple different local path planning algorithms
pathfinder
Deep Learning Autonomous Car based on Raspberry Pi, SunFounder PiCar-V Kit, TensorFlow, and Google's EdgeTPU Co-Processor
robotics_project_Q-Learning
For a mobile robot generally, the essential goal has defined a strategy that allows it to reach the goal from the starting point without collisions and an optimal path to its destination. In our project we aim and seek through experimentation to make our robot evolve in the right direction in its environment: avoidance of obstacles, recognition of the path to move easily from one point to another in the environment, and in particular, execute the scripts by varying the parameters alpha, gamma, epsilon and the number of episodes in order to see for which combination of these values there is optimization of the path and minimization of the number of steps (steps) for each episode and let's increase them cumulative rewards for our robot.
wagaabderrahim
yolo_nano
YOLO Nano implementation with Pytorch
yoloresnetbywaga
wagaabderrahim's Repositories
wagaabderrahim/Local-Planner-Visualization-Project
An all-in-one application to visualize multiple different local path planning algorithms
wagaabderrahim/pathfinder
Deep Learning Autonomous Car based on Raspberry Pi, SunFounder PiCar-V Kit, TensorFlow, and Google's EdgeTPU Co-Processor
wagaabderrahim/robotics_project_Q-Learning
For a mobile robot generally, the essential goal has defined a strategy that allows it to reach the goal from the starting point without collisions and an optimal path to its destination. In our project we aim and seek through experimentation to make our robot evolve in the right direction in its environment: avoidance of obstacles, recognition of the path to move easily from one point to another in the environment, and in particular, execute the scripts by varying the parameters alpha, gamma, epsilon and the number of episodes in order to see for which combination of these values there is optimization of the path and minimization of the number of steps (steps) for each episode and let's increase them cumulative rewards for our robot.
wagaabderrahim/wagaabderrahim
wagaabderrahim/data_set_end_to_end
wagaabderrahim/employee-leave-management
Ongoing project Demo
wagaabderrahim/jetson-multicamera-pipelines
wagaabderrahim/library-management-spring
Library Management System in Spring MVC
wagaabderrahim/yolo_nano
YOLO Nano implementation with Pytorch
wagaabderrahim/yoloresnetbywaga