পদ্ধতির তুলনা করুন

	Semi-supervised Semantic Segmentation	ইনস্ট্যান্স সেগমেন্টেশন
ক্ষেত্র	গভীর শিখন	গভীর শিখন
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	2018–2020	2017
প্রবর্তক	Multiple (Ouali et al., Zou et al., Chen et al.)	He, K., Gkioxari, G., Dollar, P., Girshick, R.
ধরন	Semi-supervised deep learning for pixel-level classification	Pixel-level detection and mask prediction
মৌলিক উৎস	Ouali, Y., Hudelot, C., & Tami, M. (2020). Semi-Supervised Semantic Segmentation with Cross-Consistency Training. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 12674–12684.	He, K., Gkioxari, G., Dollar, P., & Girshick, R. (2017). Mask R-CNN. Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2961–2969.
অপর নাম	Semi-SSL segmentation, pseudo-label segmentation, consistency regularization segmentation, label-efficient semantic segmentation	instance-level segmentation, object instance segmentation, mask prediction, panoptic instance segmentation
সম্পর্কিত	5	4
সারসংক্ষেপ	Semi-supervised semantic segmentation trains pixel-level labeling models using a small set of fully labeled images combined with a much larger set of unlabeled images. Techniques such as pseudo-labeling and consistency regularization extract supervisory signal from unlabeled data, making it possible to achieve near-fully-supervised accuracy at a fraction of the annotation cost.	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.