A Deep-Learning Model with Task-Specific Bounding Box Regressors and Conditional Back-Propagation for Moving Object Detection in ADAS Applications. - Guan-Ting Lin; Vinay Malligere Shivanna; Jiun-In Guo (Sensors, 2020)

MTSAN: Multi-Task Semantic Attention Network for ADAS Applications. - Chun-Yu Lai; Bo-Xun Wu; Vinay Malligere Shivanna; Jiun-In Guo (IEEE Access, 2021)

Real-Time Multiple Pedestrian Tracking With Joint Detection and Embedding Deep Learning Model for Embedded Systems. - Hung-Wei Lin; Vinay Malligere Shivanna; Hsiu Chi Chang; Jiun-In Guo (IEEE Access, 2022)

iVS Dataset and ezLabel: A Dataset and a Data Annotation Tool for Deep Learning Based ADAS Applications. - Yu-Shu Ni; Vinay Malligere Shivanna; Jiun-In Guo (Remote. Sens., 2022)

ConcentrateNet: Multi-Scale Object Detection Model for Advanced Driving Assistance System Using Real-Time Distant Region Locating Technique. - Bo-Xun Wu; Vinay Malligere Shivanna; Hsiang-Hsuan Hung; Jiun-In Guo (Sensors, 2022)

360° Map Establishment and Real-Time Simultaneous Localization and Mapping Based on Equirectangular Projection for Autonomous Driving Vehicles. - Bo-Hong Lin; Vinay Malligere Shivanna; Jiun-Shiung Chen; Jiun-In Guo (Sensors, 2023)

Deep Learning Derived Object Detection and Tracking Technology Based on Sensor Fusion of Millimeter-Wave Radar/Video and Its Application on Embedded Systems. - Jia-Jheng Lin; Jiun-In Guo; Vinay Malligere Shivanna; Ssu-Yuan Chang (Sensors, 2023)

Object Detection, Recognition, and Tracking Algorithms for ADASs - A Study on Recent Trends. - Vinay Malligere Shivanna; Jiun-In Guo (Sensors, 2024)