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cs.CV2024
Fractals as Pre-training Datasets for Anomaly Detection and Localization
C. I. Ugwu, S. Casarin, O. Lanz
Anomaly detection is crucial in large-scale industrial manufacturing as it helps detect and localise defective parts. Pre-training feature extractors on large-scale datasets is a p…
cs.CV2024
Your Image is My Video: Reshaping the Receptive Field via Image-To-Video Differentiable AutoAugmentation and Fusion
Sofia Casarin, Cynthia I. Ugwu, Sergio Escalera +1
The landscape of deep learning research is moving towards innovative strategies to harness the true potential of data. Traditionally, emphasis has been on scaling model architectur…
cs.CV2022
A Low Memory Footprint Quantized Neural Network for Depth Completion of Very Sparse Time-of-Flight Depth Maps
Xiaowen Jiang, Valerio Cambareri, Gianluca Agresti +4
Sparse active illumination enables precise time-of-flight depth sensing as it maximizes signal-to-noise ratio for low power budgets. However, depth completion is required to produc…