most citedNEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks

3 citations · 3 across the 2 of their papers we have counts for

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cs.CV2026

Railway Artificial Intelligence Learning Benchmark (RAIL-BENCH): A Benchmark Suite for Perception in the Railway Domain

Annika Bätz, Pavel Klasek, Seo-Young Ham +3

Automated train operation on existing railway infrastructure requires robust camera-based perception, yet the railway domain lacks public benchmark suites with standardized evaluat…