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Explores predictive models and trackers for autonomous vehicles, covering object detection, tracking challenges, neural network-based tracking, and 3D pedestrian localization.
Explores environmental computational science and earth observation through accurate deep learning models for monitoring, integrating domain knowledge in species models, and enhancing image search.
Examines perceptual modeling and spatial thinking in visual intelligence, exploring theories, cognitive maps, and the interplay between bottom-up and top-down processing.
Explores advancements in robot learning for autonomy at scale, covering deep learning challenges, efficient architecture, benchmarking results, and societal implications.
