Advances in Instance Segmentation: Technologies, Metrics and Applications in Computer Vision

Instance segmentation is an advanced technique in computer vision that focuses on identifying and classifying each individual object in an image at the pixel level. Unlike semantic segmentation, which groups pixels of similar objects without distinguishing between different instances, instance segme...

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Detalles Bibliográficos
Autores: Molina, José Manuel, Llerena Caña, Juan Pedro|||0000-0002-3476-6261, Usero Aragonés, Luis|||0000-0001-8658-9992, Patricio Guisado, Miguel Ángel
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universidad de Alcalá (UAH)
Repositorio:e_Buah Biblioteca Digital Universidad de Alcalá
Idioma:inglés
OAI Identifier:oai:ebuah.uah.es:10017/64626
Acceso en línea:http://hdl.handle.net/10017/64626
https://dx.doi.org/10.1016/j.neucom.2025.129584
Access Level:acceso abierto
Palabra clave:Computer Vision
Instance Segmentation
Evaluation Metrics
Datasets
Informática
Computer science
Descripción
Sumario:Instance segmentation is an advanced technique in computer vision that focuses on identifying and classifying each individual object in an image at the pixel level. Unlike semantic segmentation, which groups pixels of similar objects without distinguishing between different instances, instance segmentation assigns unique labels to each object, even if they are of the same class. This makes it possible not only to detect the presence and category of objects in an image but also to locate each specific instance and clearly distinguish them from each other. This problem not only advances the technical and theoretical understanding of how machines see and process digital images, but also has a direct impact on various industries and sectors where computer vision is an essential part of the system. In this paper, we present the current deep learning-based technologies, the metrics used for their evaluation, and a review of general and concrete datasets in general and drone-specific contexts. The results of this study provide a compendium of easily deployable deep learning-based technologies. This review paper aims to accelerate the process of understanding and using instance segmentation technologies for the reader.