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Semantische segmentatie×Instantiesegmentatie×
VakgebiedDeep learningDeep learning
FamilieMachine learningMachine learning
Jaar van ontstaan20152017
GrondleggerLong, J., Shelhamer, E., & Darrell, T.He, K., Gkioxari, G., Dollar, P., Girshick, R.
TypeDense prediction / pixel-wise classificationPixel-level detection and mask prediction
Oorspronkelijke bronLong, J., Shelhamer, E., & Darrell, T. (2015). Fully convolutional networks for semantic segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3431–3440. DOI ↗He, K., Gkioxari, G., Dollar, P., & Girshick, R. (2017). Mask R-CNN. Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2961–2969. DOI ↗
Aliassenpixel-wise classification, scene parsing, dense labeling, semantic scene segmentationinstance-level segmentation, object instance segmentation, mask prediction, panoptic instance segmentation
Verwant54
SamenvattingSemantic segmentation assigns a class label to every pixel in an image, producing a dense, category-annotated map of the scene. Unlike object detection, which draws bounding boxes, it delineates the exact spatial extent of each class, making it indispensable in medical imaging, autonomous driving, satellite analysis, and any task where precise region boundaries matter.Instance segmentation is a computer vision task that simultaneously detects every distinct object in an image and produces a precise pixel-level mask for each individual object instance. Unlike semantic segmentation, which labels every pixel with a class, instance segmentation distinguishes between separate objects of the same class, enabling fine-grained spatial understanding.
ScholarGateGegevensset
  1. v1
  2. 2 Bronnen
  3. PUBLISHED
  1. v1
  2. 2 Bronnen
  3. PUBLISHED

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ScholarGateMethoden vergelijken: Semantic Segmentation · Instance Segmentation. Geraadpleegd op 2026-06-15 via https://scholargate.app/nl/compare