|
gptkbp:instance_of
|
gptkb:Model
|
|
gptkbp:bfsLayer
|
5
|
|
gptkbp:bfsParent
|
gptkb:YOLO
|
|
gptkbp:applies_to
|
Image Processing
|
|
gptkbp:based_on
|
gptkb:television_channel
|
|
gptkbp:developed_by
|
gptkb:Wei_Liu
|
|
gptkbp:has_achievements
|
High Accuracy
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
SSD (Single Shot Multi Box Detector)
|
|
gptkbp:improves
|
Real-time Object Detection
|
|
gptkbp:input_output
|
Bounding Boxes
|
|
gptkbp:is_challenged_by
|
gptkb:Faster_R-CNN
gptkb:Retina_Net
|
|
gptkbp:is_compared_to
|
gptkb:YOLO_(You_Only_Look_Once)
|
|
gptkbp:is_discussed_in
|
gptkb:municipality
Online Courses
Webinars
|
|
gptkbp:is_documented_in
|
gptkb:conference
Research Papers
Technical Reports
|
|
gptkbp:is_evaluated_by
|
Benchmark Datasets
Io U (Intersection over Union)
Mean Average Precision (m AP)
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
|
gptkbp:is_influenced_by
|
gptkb:YOLO_Algorithm
Region-based CN Ns
|
|
gptkbp:is_optimized_for
|
Speed and Accuracy
|
|
gptkbp:is_part_of
|
Machine Learning Techniques
Deep Learning Frameworks
Computer Vision Algorithms
Artificial Intelligence Applications
|
|
gptkbp:is_popular_in
|
Computer Vision Community
|
|
gptkbp:is_related_to
|
gptkb:microprocessor
gptkb:Deep_Learning
Image Recognition
Image Segmentation
Feature Extraction
Object Localization
|
|
gptkbp:is_supported_by
|
NVIDIAGP Us
TP Us
|
|
gptkbp:is_used_for
|
Data Labeling
Content Moderation
Image Annotation
Face Detection
Pedestrian Detection
Vehicle Detection
|
|
gptkbp:is_used_in
|
gptkb:musician
gptkb:Autonomous_Vehicles
gptkb:software
gptkb:robot
Surveillance Systems
|
|
gptkbp:recognizes
|
Objects in Images
|
|
gptkbp:requires
|
Training Data
|
|
gptkbp:speed
|
gptkb:R-CNN
|
|
gptkbp:suitable_for
|
Real-time Applications
|
|
gptkbp:supports
|
Multi-class Detection
|
|
gptkbp:training
|
gptkb:Pascal_VOC_Dataset
gptkb:COCO_Dataset
|
|
gptkbp:uses
|
gptkb:Single_Shot_Detection
|
|
gptkbp:utilizes
|
Feature Maps
|
|
gptkbp:year_created
|
gptkb:2016
|