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cs.CV2026

UAV-Based Environmental Monitoring of Rip-Current Indicators Using Wavelet-Derived Texture Features

Yonatan Ben Avraham, Baruch Binyaminov, Yehudit Aperstein

Rip currents are recurrent coastal natural hazards that threaten beachgoers and create operational challenges for lifeguards and coastal managers. Reliable monitoring from standard…

cs.CV2026

Mapping License Plate Recoverability Under Extreme Viewing Angles for Opportunistic Urban Sensing

Igor Adamenko, Orpaz Ben Aharon, Yehudit Aperstein +1

Urban environments contain many imaging sensors built for specific purposes, including ATM, body-worn, CCTV, and dashboard cameras. Under the opportunistic sensing paradigm, these…

cs.CV2026

CalexNet: Soft Cascade-Aligned Training and Calibration for Lightweight Early-Exit Branches

Yehudit Aperstein, Alexander Apartsin

Early-exit cascades over a frozen convolutional backbone enable adaptive inference but suffer from three sources of train-inference mismatch: branches train on samples they will ne…

cs.CV2025

Recognition of Abnormal Events in Surveillance Videos using Weakly Supervised Dual-Encoder Models

Noam Tsfaty, Avishai Weizman, Liav Cohen +2

We address the challenge of detecting rare and diverse anomalies in surveillance videos using only video-level supervision. Our dual-backbone framework combines convolutional and t…

cs.CV2025

Enhancing Classification of Streaming Data with Image Distillation

Rwad Khatib, Yehudit Aperstein

This study tackles the challenge of efficiently classifying streaming data in envi-ronments with limited memory and computational resources. It delves into the application of data…

cs.CV2025

Stitching the Story: Creating Panoramic Incident Summaries from Body-Worn Footage

Dor Cohen, Inga Efrosman, Yehudit Aperstein +1

First responders widely adopt body-worn cameras to document incident scenes and support post-event analysis. However, reviewing lengthy video footage is impractical in time-critica…