Decision-level fusion with WBF outperforms feature-level fusion for occlusion-robust detection on ultra-low-end hardware, with gains up to +0.3827 mAP across three views and on-device execution on Coral boards.
Image and Vision Computing107, 104117 (2021)
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ED-CCF projects detections into a quad-state error taxonomy and applies class-conditional calibration only when empirically justified, raising mAP50 for a hard class by 22.4% on a 600-image benchmark while keeping global mAP50 stable.
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Tiny Collaborative Inference for Occlusion-Robust Object Detection
Decision-level fusion with WBF outperforms feature-level fusion for occlusion-robust detection on ultra-low-end hardware, with gains up to +0.3827 mAP across three views and on-device execution on Coral boards.
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Error-Decomposed Class-Conditional Fusion for Statistically Guaranteed Hard-Category Robust Perception
ED-CCF projects detections into a quad-state error taxonomy and applies class-conditional calibration only when empirically justified, raising mAP50 for a hard class by 22.4% on a 600-image benchmark while keeping global mAP50 stable.
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