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gptkbp:instance_of
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gptkb:cosmic_ray_detector
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gptkbp:based_on
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gptkb:YOLO_(You_Only_Look_Once)
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gptkbp:can_detect
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80 object classes
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gptkbp:developed_by
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gptkb:Joseph_Redmon
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gptkbp:has
|
real-time performance
open-source code
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gptkbp:has_achieved
|
high accuracy
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|
https://www.w3.org/2000/01/rdf-schema#label
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YOLOv2
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gptkbp:improves
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gptkb:YOLOv4
gptkb:YOLOv5
gptkb:YOLOv3-tiny
real-time object detection
speed of detection
|
|
gptkbp:input_output
|
416x416 pixels
bounding boxes and class probabilities
|
|
gptkbp:is_a_framework_for
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gptkb:Darknet
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gptkbp:is_compatible_with
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gptkb:Tensor_Flow
gptkb:Keras
gptkb:Py_Torch
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|
gptkbp:is_evaluated_by
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gptkb:PASCAL_VOC
gptkb:Cityscapes_dataset
gptkb:KITTI_dataset
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|
gptkbp:is_popular_in
|
computer vision community
|
|
gptkbp:is_trained_in
|
gptkb:COCO_dataset
|
|
gptkbp:is_used_for
|
image classification
image segmentation
object tracking
|
|
gptkbp:is_used_in
|
gptkb:sports_team
gptkb:medical_imaging
gptkb:vehicles
gptkb:drones
gptkb:robotics
augmented reality
environmental monitoring
industrial automation
quality control
gesture recognition
security systems
surveillance systems
video analysis
facial recognition
traffic monitoring
retail analytics
wildlife monitoring
smart cameras
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|
gptkbp:release_year
|
gptkb:2016
|
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gptkbp:reliability
|
gptkb:YOLOv3
gptkb:Retina_Net
gptkb:Mask_R-CNN
|
|
gptkbp:speed
|
gptkb:Faster_R-CNN
gptkb:R-CNN
gptkb:Fast_R-CNN
|
|
gptkbp:successor
|
gptkb:YOLOv3
|
|
gptkbp:supports
|
multiple object detection
|
|
gptkbp:uses
|
convolutional neural networks
batch normalization
anchor boxes
|
|
gptkbp:written_in
|
C and CUDA
|
|
gptkbp:bfsParent
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gptkb:YOLO
|
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gptkbp:bfsLayer
|
5
|