Vision

46 methods in this family.

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Background SubtractionBackground subtraction is a video processing technique that separates moving foreground objects from a static or slowly changing background by comparing each frame to a learned or Blob DetectionBlob detection is a technique for identifying regions of interest (blobs)—connected, homogeneous areas that differ from their surroundings—at multiple scales. Introduced by Lindebe Canny Edge DetectionThe Canny edge detector, introduced by John Canny in 1986, is a multi-stage algorithm for identifying edges in digital images where significant intensity changes occur. Canny's met CNN Image ClassificationCNN image classification uses deep convolutional architectures such as ResNet (He et al., 2016), VGG and EfficientNet (Tan & Le, 2019) to sort images into categories. Stacked convo Contour AnalysisContour analysis is the process of detecting and analyzing the boundaries of objects in images by identifying connected edges and extracting shape information. The Suzuki-Abe algor DETR (Detection Transformer)DETR (Detection Transformer) is an end-to-end framework for object detection introduced by Carion et al. in 2020 that reformulates detection as a direct set prediction problem usin

All methods 46

Background Subtraction Blob Detection Canny Edge Detection CNN Image Classification Contour Analysis DETR (Detection Transformer)Domain-adaptive image classification Explainable Image Classification Explainable Object Detection Explainable Semantic Segmentation Few-Shot Object Detection Fine-Tuned Image Classification Fine-Tuned Semantic Segmentation Fully Convolutional Network (FCN)Harris Corner Detection Histogram Equalization Hough Transform Image Classification Image Morphology Operations Lucas-Kanade Optical Flow Mask R-CNN Multilingual Image Classification Multilingual Semantic Segmentation Multimodal Image Classification Multimodal Object Detection Multimodal Semantic Segmentation Object Detection ORB Feature Descriptor Pixel-Based Classification Scale-Space Theory Self-supervised Image Classification Self-supervised Object Detection Self-supervised Semantic Segmentation Semantic Segmentation Semi-supervised Image Classification Semi-supervised Object Detection Semi-supervised Semantic Segmentation SIFT Feature Detection Stereo Matching Transfer Learning with Image Classification Transfer Learning with Object Detection Watershed Segmentation Weakly Supervised Image Classification Weakly Supervised Object Detection Weakly Supervised Semantic Segmentation YOLO