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Vehicle Perception researcher with a strong background in computer vision and robotics. I'm currently working on the Indy Autonomous Challenge, where I develop and implement the perception stack of the racing cars. The hardware perception package I work with Involves Luminar Lidars, Mako Cameras, Radars, and GPSs all connected to a Cisco 5000 Series switch. mMy previous experience includes computer vision internships, robotics projects, and secure database and file sharing systems. I'm also currently working on a project investigating the suitability of DQR on constrained RL tasks from OpenAI's safety gym simulation with Aaron Kandel. Reach out to [email protected] for inquiries

(Chris) Wei Xun Lai's Projects

lidar_livox_camera_calib icon lidar_livox_camera_calib

This repository is used for automatic calibration between high resolution LiDAR and camera in targetless scenes.

rhtn icon rhtn

RHTN Starter from Aaron

ros2_yolov7 icon ros2_yolov7

Implementation of the Trainable Bag of Freebies YOLOv7 Repository. Basically a ROS2 wrapper around detect.py!

segment-anything icon segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

stock-prediction-models icon stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

stock_analyzer_twitter_etc icon stock_analyzer_twitter_etc

Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis

yolobbox2seg icon yolobbox2seg

Yolo Bounding Box to Image segmentations for Autonomous Racing Applications

yolov5 icon yolov5

Yolov5 Badminton shuttlecock detection

yolov8 icon yolov8

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

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