An Efficient ADAS Framework for Cross-Domain Image Translation and Feature Preservation Utilizing CycleGAN
Published in CONFLUENCE 2025, Noida — Springer LNEE, 2025
A CycleGAN-based advanced driver-assistance (ADAS) framework for cross-domain image translation that preserves task-relevant features. Presented at CONFLUENCE 2025 (Noida, India); to appear in Springer Lecture Notes in Electrical Engineering.
Recommended citation: A. Bidhan, N. K. Shah, R. Kumar, V. Gupta, and S. Prakash. (2025). "An Efficient ADAS Framework for Cross-Domain Image Translation and Feature Preservation Utilizing CycleGAN." 15th Int. Conf. on Cloud Computing, Data Science & Engineering (CONFLUENCE 2025), Noida, India. Springer Lecture Notes in Electrical Engineering.
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