marco-nguyen Goto Github PK

browser-based-models-with-tensorflowjs

You may think that machine learning models can only be trained with supercomputers and big data. This first course shows you how you can train and run machine learning models in any browser using TensorFlow.js. You’ll learn techniques for handling data in the browser, and at the end you’ll build a computer vision project that recognizes and classifies objects from a webcam. deeplearning.ai certificate : https://www.coursera.org/account/accomplishments/records/BURZEBYF8K3A

darknet

Convolutional Neural Networks

deep_sort

Simple Online Realtime Tracking with a Deep Association Metric

digital_control_system

drone-based_car_counter

Drone-based Car Counter

emoji-cheat-sheet

A markdown version emoji cheat sheet

flask_backend_server

flaskseries

This is the Code from my Flask Series - JimShapedCoding. Each Folder is a checkpoint where we stopped at that particular episode number

flexible-yolov5

More readable and flexible yolov5 with more backbone(resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer) and (cbam，dcn and so on), and tensorrt

marco-nguyen

Config files for my GitHub profile.

mobile_robot_project

robotvision

rpl

[ICCV'23] Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation

self-study

smartparking

tfjs-web-inference

transportation_optimization

Transportation optimization project

yolov4-deepsort

Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.

yolov8_tracking

Real-time multi-object tracking and segmentation using YOLOv8 with DeepOCSORT and OSNet