Introduces an early-exit mechanism in YOLOv8 that uses inter-vessel distance and closing speed from trajectories to adapt computation depth per frame in maritime scenes.
Branchynet: Fast inference via early exiting from deep neural networks
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Combining pruning, quantization, and early exits in CNNs reduces inference latency and memory on real edge devices with minimal accuracy loss.
Early-exit Tiny U-Net reduces average multiplications by up to 42% with comparable IoU for onboard UAV radar processing of oil spills.
citing papers explorer
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Trajectory-Aware Adaptive Inference in Object Detection Models
Introduces an early-exit mechanism in YOLOv8 that uses inter-vessel distance and closing speed from trajectories to adapt computation depth per frame in maritime scenes.
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A Comparative Study of CNN Optimization Methods for Edge AI: Exploring the Role of Early Exits
Combining pruning, quantization, and early exits in CNNs reduces inference latency and memory on real edge devices with minimal accuracy loss.
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Early Exiting U-Net for Efficient Processing on UAVs: A Case Study in Environmental Monitoring
Early-exit Tiny U-Net reduces average multiplications by up to 42% with comparable IoU for onboard UAV radar processing of oil spills.