M²E-UAV is the first benchmark dataset and evaluation protocol for tiny UAV detection from a moving event camera in motion-on-motion conditions.
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Yolov10: Real-time end- to-end object detection
11 Pith papers cite this work. Polarity classification is still indexing.
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A new global corpus of dense Sentinel-1 SAR time series for 15,606 offshore wind infrastructure locations is released with baseline semantic labels and an expert benchmark, enabling analyses of deployment dynamics.
BabelDOC uses an intermediate representation to decouple layout from content for improved layout-preserving PDF translation.
DM³-Nav delivers decentralized multi-agent semantic navigation for multimodal open-vocabulary multi-object tasks that matches centralized baselines in simulation and succeeds in real-world robot deployments.
YOLOv12 is a new attention-based real-time object detector that reports higher accuracy than YOLOv10, YOLOv11, and RT-DETR variants at comparable or better speed and efficiency.
Vision-aided deep learning delivers 98.96% beam prediction accuracy and over 98% proactive blockage prediction for mm-wave links, including the first treatment of simultaneous non-uniform mobility.
A scale-robust lightweight CNN for glottis segmentation achieves 92.9% mDice at over 170 FPS with a 19 MB model size on three datasets.
DocRevive builds a unified pipeline using OCR, image analysis, language models, and diffusion to reconstruct degraded document text, backed by a 30k-image synthetic dataset and the UCSM metric.
MinerU delivers an open-source pipeline for high-precision document content extraction by integrating specialized models with tuned preprocessing and postprocessing rules.
YOLO11n achieves the highest mAP@0.5:0.95 of 0.6065 for apple localization, with other detectors showing trade-offs in recall and precision at low confidence thresholds.
YOLOv11 adds blocks such as C3k2, SPPF, and C2PSA to improve feature extraction, mAP, and efficiency while supporting detection, segmentation, pose, and oriented detection across model sizes.
citing papers explorer
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M$^2$E-UAV: A Benchmark and Analysis for Onboard Motion-on-Motion Event-Based Tiny UAV Detection
M²E-UAV is the first benchmark dataset and evaluation protocol for tiny UAV detection from a moving event camera in motion-on-motion conditions.
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Global Offshore Wind Infrastructure: Deployment and Operational Dynamics from Dense Sentinel-1 Time Series
A new global corpus of dense Sentinel-1 SAR time series for 15,606 offshore wind infrastructure locations is released with baseline semantic labels and an expert benchmark, enabling analyses of deployment dynamics.
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BabelDOC: Better Layout-Preserving PDF Translation via Intermediate Representation
BabelDOC uses an intermediate representation to decouple layout from content for improved layout-preserving PDF translation.
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DM$^3$-Nav: Decentralized Multi-Agent Multimodal Multi-Object Semantic Navigation
DM³-Nav delivers decentralized multi-agent semantic navigation for multimodal open-vocabulary multi-object tasks that matches centralized baselines in simulation and succeeds in real-world robot deployments.
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YOLOv12: Attention-Centric Real-Time Object Detectors
YOLOv12 is a new attention-based real-time object detector that reports higher accuracy than YOLOv10, YOLOv11, and RT-DETR variants at comparable or better speed and efficiency.
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Deep Learning-Based Computer Vision for Beam Selection and Proactive Blockage Prediction
Vision-aided deep learning delivers 98.96% beam prediction accuracy and over 98% proactive blockage prediction for mm-wave links, including the first treatment of simultaneous non-uniform mobility.
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A Real-time Scale-robust Network for Glottis Segmentation in Nasal Transnasal Intubation
A scale-robust lightweight CNN for glottis segmentation achieves 92.9% mDice at over 170 FPS with a 19 MB model size on three datasets.
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DocRevive: A Unified Pipeline for Document Text Restoration
DocRevive builds a unified pipeline using OCR, image analysis, language models, and diffusion to reconstruct degraded document text, backed by a 30k-image synthetic dataset and the UCSM metric.
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MinerU: An Open-Source Solution for Precise Document Content Extraction
MinerU delivers an open-source pipeline for high-precision document content extraction by integrating specialized models with tuned preprocessing and postprocessing rules.
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A Comparative Study of Modern Object Detectors for Robust Apple Detection in Orchard Imagery
YOLO11n achieves the highest mAP@0.5:0.95 of 0.6065 for apple localization, with other detectors showing trade-offs in recall and precision at low confidence thresholds.
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YOLOv11: An Overview of the Key Architectural Enhancements
YOLOv11 adds blocks such as C3k2, SPPF, and C2PSA to improve feature extraction, mAP, and efficiency while supporting detection, segmentation, pose, and oriented detection across model sizes.