Senior Design - Lane Wizard
Lane Wizard is an autonomous vehicle prototype
Lane Wizard is an autonomous vehicle prototype
Mapping above-ground forest biomass across Michigan at 10 m from GEDI lidar, Sentinel-2 and AlphaEarth embeddings
Multicore RISC-V CPU: from a 5-stage pipeline to cached, cache-coherent dual-core designs on an FPGA
Detecting red-light runs, rolling stops and near-collisions from a single traffic camera with YOLO12, ByteTrack and ground-plane homography
A depth-based reinforcement-learning locomotion policy for the Unitree Go2 that climbs stairs, jumps onto boxes, leaps gaps and crosses narrow beams, taken from Isaac Gym to Gazebo to the real robot
A Racing Dataset and Baseline Model for Track Detection in Autonomous Racing
Weighted branch aggregation based deep learning model for track detection in autonomous racing
Published in The Second Tiny Papers Track at ICLR 2024, 2024
WeBACNN, a lightweight CNN that detects the race track in real time without relying on lane markings, running 47× faster than YOLOv8 with 65% fewer parameters.
Recommended citation: Ghosh, S., Chen, Y. H., Huang, C. H., Jameel, A. S. M. M., El Gamal, A., & Labi, S. (2024). "Weighted branch aggregation based deep learning model for track detection in autonomous racing." The Second Tiny Papers Track at ICLR 2024.
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Published in arXiv preprint arXiv:2502.14068, 2025
RoRaTrack, a multi-camera road-racing dataset with pixel-level track annotations, and RaceGAN, a GAN baseline that outperforms eight state-of-the-art models on it.
Recommended citation: Ghosh, S., Chen, Y. H., Huang, C. H., Jameel, A. S. M. M., Ho, C. C., El Gamal, A., & Labi, S. (2025). "A Racing Dataset and Baseline Model for Track Detection in Autonomous Racing." arXiv preprint arXiv:2502.14068.
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Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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