Image processing and computer vision place great importance on image segmentation, as dividing an image into different regions helps in better understanding its content.Image segmentation may involve several stages.This field is applied across various domains, including medical imaging, autonomous vehicles, augmented reality, and image retrieval systems [1].The segmentation process requires dividing the image into non-overlapping but meaningful regions, which is critical for analyzing natural scenes [2].Despite many years of research, feature extraction and modeling remain key challenges.Deep learning technology is used at various stages, including collaborative, traditional, and semantic segmentation.Each stage includes its own specific algorithms and techniques [2].Due to the diversity of human perception and the uncertainty in visual understanding, representing objects and meaningful regions remains a difficult task.New methods of image segmentation using deep neural networks provide more accurate results by leveraging various datasets.
| Jurnal | ТАТУ хабарлари |
|---|---|
| Nashr sanasi | 2025-10-22 |
| DOI | 10.61663/253tuitmct1 |
DOI: 10.61663/253tuitmct1 · Maqolaning asl sahifasi
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