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Tags

• RoI pooling
• Fast R-CNN
• hard negative mining
• pytorch
• RPN
• Anchor box
• Non maximum suppression
• YOLO
• Multi-task loss
• Region proposal Network
• multi task loss
• fine tune AlexNet
• Bounding box regressor
• mean Average Precision
• Average Precision
• Object Detection metric
• Linear SVM
• Faster R-CNN
• R-CNN
• Darknet
• Object Detection
• IOU
• AP
• Map
• object queries
• Hungarian algorithm
• Detection Transformer
• herbwood
• BiFPN
• detr
• compound scaling
• feature pyramid
• Lateral connections
• Top-down pathway
• Bottom-up pathway
• Feature Pyramid Network
• FPN
• YOLO v2 loss function
• multi-scale training
• wordtree
• darknet-19
• YOLO v2 설명
• YOLO v2 논문
• YOLO v2
• efficientDet
• position-sensitive pooling
• position-sensitive score map
• translation variance
• translation invariance
• R-FCN 논문
• fully convolutional network
• R-FCN
• default box
• multi scale feature map
• SSD 논문
• grid cell
• 1-stage detector
• YOLO v1 논문
• You Only Look Once
• online hard example mining
• hard RoI sampler
• class imbalance
• OHEM 논문
• OHEM
• Alternating training
• Faster R-CNN 논문
• smooth l1 loss
• log loss
• truncated SVD
• hierarchical sampling
• Region of Interest
• greedy merge strategy
• spatial output
• multi-scale
• Overfeat
• Bounding box regression
• PASCAL VOC
• Non max suppression
• bounding box
• Intersection over Union
• EfficientNet
• confidence score
• selective search
• Single Shot MultiBox Detector
• Batch Normalization
• k-means clustering
• receptive field
• classifier
• bipartite matching
• recall
• precision
• False Positive
• transformer
• ROI
• ssd
• readonly
• Python
• anchor