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Small-size object detection, Real-time, YOLO, Robotic vision,
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Object detection, Feature extraction, Remote sensing, Proposals,
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CBAM, dilated convolution, object detection,
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Detectors, Feature extraction, Object detection, Convolution,
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Few-shot object detection, Transfer learning, Real-time,
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Small object detection, Feature enhancement, Spatial-aware
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Architectural changes, Deep learning, Autonomous driving,
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2303
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Detectors, Feature extraction, Object detection, Training,
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Deep learning, Convolutional neural networks,
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Deep learning, Small target detection, Multi-scale feature fusion,
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computer vision, image recognition, insulators, object detection
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Feature extraction, Convolution, Object detection,
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Training, Deep learning, Computational modeling, Neural networks,
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YOLO, Measurement, Analytical models, Reviews,
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Training, Image segmentation, Computational modeling, Data models,
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Convolution, Computational modeling, Roads, Object detection,
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Head, Computational modeling, Robot kinematics, Object detection,
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Yolo-SG: Salience-Guided Detection Of Small Objects In Medical Images,
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Deep learning, Analytical models, Image resolution,
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Ghost-YOLOX: A Lightweight and Efficient Implementation of Object
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Training, Image segmentation, Costs, Convolution, Fuses,
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WACV22(1311-1321)
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Performance evaluation, Deep learning,
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Quantization (signal), Power demand, Network topology,
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Yolo+FPN: 2D and 3D Fused Object Detection With an RGB-D Camera,
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Training, Visualization, Fuses,
Object detection, Benchmark testing, Cameras
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Remote sensing, Feature extraction, Image resolution,
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Effect of Annotation Errors on Drone Detection with YOLOv3,
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Detectors, Training, Feature extraction, Labeling, Real-time systems,
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2004
object detection, road safety, traffic engineering computing,
object detection algorithms, Gaussian YOLOv3, Feature extraction
BibRef
Simon, M.[Martin],
Milz, S.[Stefan],
Amende, K.[Karl],
Gross, H.M.[Horst-Michael],
Complex-YOLO: An Euler-Region-Proposal for Real-Time 3D Object
Detection on Point Clouds,
CVRoads18(I:197-209).
Springer DOI
1905
Lidar, automated driving.
BibRef
Redmon, J.[Joseph],
Farhadi, A.[Ali],
YOLO9000: Better, Faster, Stronger,
CVPR17(6517-6525)
IEEE DOI
1711
Award, CVPR, HM. Detectors, Feature extraction, Image resolution, Object detection,
Real-time systems, Training
Real time, 9000 object categories.
BibRef
Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
SWIN Transformer .