Faster R-CNN

URI: https://gptkb.org/entity/Faster_R-CNN

GPTKB entity

Statements (124)

Predicate	Object
gptkbp:instance_of	gptkb:cosmic_ray_detector
gptkbp:applies_to	gptkb:neural_networks computer vision image classification instance segmentation object localization
gptkbp:benefits	high accuracy high speed computationally intensive requires large datasets
gptkbp:can_detect	Objects in Images
gptkbp:developed_by	gptkb:Ross_B._Girshick gptkb:Shaoqing_Ren gptkb:Kaiming_He Jian Sun
gptkbp:has	High Accuracy End-to-End Training
gptkbp:has_achieved	State-of-the-art Performance state-of-the-art performance
gptkbp:has_applications_in	gptkb:sports_team gptkb:medical_imaging gptkb:vehicles gptkb:robotics augmented reality surveillance systems facial recognition retail analytics drone monitoring
gptkbp:has_feature	high accuracy real-time processing end-to-end training
gptkbp:has_limitations	computationally intensive requires large datasets
gptkbp:has_variants	gptkb:Faster_R-CNN_with_FPN Faster R-CNN with attention mechanisms
https://www.w3.org/2000/01/rdf-schema#label	Faster R-CNN
gptkbp:improves	gptkb:R-CNN gptkb:Fast_R-CNN Object Detection Speed
gptkbp:is_adopted_by	gptkb:Industry Academia
gptkbp:is_based_on	gptkb:R-CNN gptkb:Fast_R-CNN deep learning Convolutional Neural Networks (CNNs)
gptkbp:is_cited_in	over 10,000 papers
gptkbp:is_compared_to	gptkb:SSD gptkb:YOLO
gptkbp:is_enhanced_by	gptkb:stage_adaptation gptkb:Hyperparameter_Tuning Data Augmentation
gptkbp:is_evaluated_by	gptkb:Cityscapes_Dataset gptkb:KITTI_Dataset gptkb:Open_Images_Dataset gptkb:PASCAL_VOC gptkb:MS_COCO gptkb:COCO_dataset
gptkbp:is_implemented_in	gptkb:Tensor_Flow gptkb:Py_Torch
gptkbp:is_influenced_by	gptkb:Deep_Residual_Networks Region-based CNNs
gptkbp:is_influential_in	computer vision applications deep learning research
gptkbp:is_known_for	Flexibility Scalability Feature Reusability High Recall Rate Real-Time Detection
gptkbp:is_optimized_for	GPU Processing
gptkbp:is_part_of	gptkb:AI_technology Machine Learning Applications computer vision Deep Learning Frameworks deep learning frameworks Computer Vision Research Faster R-CNN family
gptkbp:is_popular_in	gptkb:academic_research industry applications
gptkbp:is_related_to	gptkb:SSD gptkb:YOLO gptkb:Mask_R-CNN
gptkbp:is_supported_by	gptkb:Open_CV gptkb:NVIDIA_GPUs gptkb:TPUs gptkb:NVIDIA
gptkbp:is_trained_in	gptkb:Open_Images gptkb:Image_Net
gptkbp:is_used_for	image segmentation real-time object detection
gptkbp:is_used_in	gptkb:Augmented_Reality gptkb:Autonomous_Vehicles gptkb:Computer_Vision gptkb:medical_imaging gptkb:vehicles gptkb:robotics Facial Recognition Image Analysis Medical Imaging Surveillance Systems image classification facial recognition video surveillance instance segmentation object localization
gptkbp:performance	Precision Recall image analysis Frames Per Second (FPS) object detection tasks image segmentation tasks Inference time mean Average Precision (m AP) video analysis tasks
gptkbp:published_in	gptkb:2015
gptkbp:reduces	False Positive Rate
gptkbp:release_year	gptkb:2015
gptkbp:requires	Large Datasets
gptkbp:supports	Multi-Class Detection
gptkbp:uses	gptkb:Region_Proposal_Network_(RPN) Region Proposal Networks Convolutional Neural Networks (CNNs)
gptkbp:bfsParent	gptkb:YOLO gptkb:Mask_R-CNN
gptkbp:bfsLayer	5