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cs.CV2024
VWise: A novel benchmark for evaluating scene classification for vehicular applications
Pedro Azevedo, Emanuella Araújo, Gabriel Pierre +5
Current datasets for vehicular applications are mostly collected in North America or Europe. Models trained or evaluated on these datasets might suffer from geographical bias when…
cs.CV2019★ 1 cited
Bio-Inspired Foveated Technique for Augmented-Range Vehicle Detection Using Deep Neural Networks
Pedro Azevedo, Sabrina S. Panceri, Rânik Guidolini +4
We propose a bio-inspired foveated technique to detect cars in a long range camera view using a deep convolutional neural network (DCNN) for the IARA self-driving car. The DCNN rec…