Search Results - Image Processing AND Computer Vision—Segmentation~

Computer vision segmentation model--deep learning for categorizing microplastic debris.

Authors: Royer, Sarah-Jeanne Wolter, Helen Delorme, Astrid E. et al.

Source: Frontiers in Environmental Science; 2024, p1-13, 13p

Subject Terms: COMPUTER vision, IMAGE recognition (Computer vision), IMAGE segmentation, DEEP learning, MARINE debris, DEPLOYMENT (Military strategy), IMAGE processing

Learning few-shot semantic segmentation with error-filtered segment anything model.

Authors: Feng, Chen-Bin Lai, Qi Liu, Kangdao et al.

Source: Visual Computer; Aug2025, Vol. 41 Issue 10, p7351-7365, 15p

Subject Terms: COGNITIVE psychology, ARTIFICIAL intelligence, IMAGE processing, COMPUTER vision, IMAGE analysis

Research on hotspots and frontiers of agricultural pests and diseases image recognition technology based on bibliometrics.

Authors: Zhang, Hongtao Zheng, Li Liu, Yu et al.

Source: Multimedia Tools & Applications; Jul2025, Vol. 84 Issue 24, p28559-28581, 23p

Subject Terms: IMAGE recognition (Computer vision), AGRICULTURAL pests, AGRICULTURAL research, BIBLIOMETRICS, CONCEPT mapping, CROP science, REMOTE sensing

Company/Entity: CHINESE Academy of Sciences (Beijing, China)

A Comparative Analysis of Image Segmentation Using Classical and Deep Learning Approach.

Authors: Plaksyvyi, Arsen Skublewska-Paszkowska, Maria Powroznik, Paweł

Source: Advances in Science & Technology Research Journal; 2023, Vol. 17 Issue 6, p127-139, 13p

Subject Terms: IMAGE segmentation, DEEP learning, IMAGE analysis, COMPUTER vision, MACHINE learning, IMAGE processing, ARTIFICIAL neural networks

Lightweight Leather Surface Defect Inspection Model Design for Fast Classification and Segmentation.

Authors: Lee, Chin-Feng Chen, Yu-Chuan Shen, Jau-Ji et al.

Source: Symmetry (20738994); Mar2025, Vol. 17 Issue 3, p358, 23p

Subject Terms: INDUSTRIAL architecture, COMPUTER vision, IMAGE processing, SURFACE defects, MODULAR design

Improvement of chest X-ray image segmentation accuracy based on FCA-Net.

Authors: Wahyuningrum, Rima Tri Yunita, Indah Siradjuddin, Indah Agustien et al.

Source: Cogent Engineering; 2023, Vol. 10 Issue 1, p1-16, 16p

Subject Terms: X-ray imaging, X-rays, DEEP learning, IMAGE segmentation, IMAGE processing, COMPUTER vision, TISSUE extracts, DIAGNOSTIC imaging

Advanced Techniques for the Intelligent Diagnosis of Fish Diseases: A Review.

Authors: Li, Daoliang Li, Xin Wang, Qi et al.

Source: Animals (2076-2615); Nov2022, Vol. 12 Issue 21, p2938, 26p

Subject Terms: FISH diseases, DIAGNOSIS, DEEP learning, EXPERT systems, COMPUTER vision, ULTRASONIC imaging, THREE-dimensional imaging, IMAGE processing

A Comprehensive Survey on Sampling-Based Image Matting.

Authors: Yao, Guilin Zhao, Zhijie Liu, Shaohui

Source: Computer Graphics Forum. Dec2017, Vol. 36 Issue 8, p613-628. 16p. 13 Color Photographs, 1 Black and White Photograph, 2 Diagrams, 5 Charts.

Subject Terms: IMAGE processing, SAMPLING (Process), COMPOSITING (Cinematography), MOTION picture editing, MULTIPLE-image shot (Cinematography)

Segmentation of Vitiligo images using modified Watershed Segmentation.

Authors: Agrawal, Neha Aurelia, Sagaya

Source: Library of Progress-Library Science, Information Technology & Computer; Jul-Dec2024, Vol. 44 Issue 3, p2934-2941, 8p

Subject Terms: IMAGE analysis, VITILIGO, IMAGE processing, IMAGE segmentation, WATERSHEDS

On the Affinity of Image Smoothing and Segmentation Problems.

Authors: Chochia, P. A.

Source: Journal of Communications Technology & Electronics; Jul2024, Vol. 69 Issue 7, p319-329, 11p

Subject Terms: IMAGE processing, ARTIFICIAL intelligence, VIDEO processing, ALGORITHMS

Shared Sampling for Real-Time Alpha Matting.

Authors: Gastal, Eduardo S. L. Oliveira, Manuel M.

Source: Computer Graphics Forum. May2010, Vol. 29 Issue 2, p575-584. 10p. 4 Color Photographs, 1 Diagram, 2 Charts.

Subject Terms: *ESTIMATION theory, DIGITAL image processing, COMPUTER vision, PIXELS, MATTES, COMPUTER graphics

A Systematic Review on Caries Detection, Classification, and Segmentation from X-Ray Images: Methods, Datasets, Evaluation, and Open Opportunities.

Authors: Zanini, Luiz Guilherme Kasputis Rubira-Bullen, Izabel Regina Fischer Nunes, Fátima de Lourdes dos Santos

Source: Journal of Digital Imaging; Aug2024, Vol. 37 Issue 4, p1824-1845, 22p

Subject Terms: DIAGNOSIS of dental caries, DENTAL radiography, RESEARCH funding, DESCRIPTIVE statistics, SYSTEMATIC reviews, MEDLINE, X-rays, DENTISTRY, DENTAL caries, DENTAL technology, DIGITAL image processing, ONLINE information services, MACHINE learning, COMPARATIVE studies

Deep Learning Based Detection and Classification of Gastrointestinal Abnormalities from Endoscopic Imaging Data.

Authors: Kumari, T. Swetha Vasuki, R.

Source: International Research Journal of Multidisciplinary Technovation (IRJMT); 2025, Vol. 7 Issue 5, p223-239, 17p

Subject Terms: DEEP learning, INTESTINAL abnormalities, IMAGE processing, DETECTION algorithms, MATHEMATICAL optimization, ENDOSCOPIC ultrasonography, ROUTINE diagnostic tests

Computer‐Vision‐Based Approach to Classify and Quantify Flaws in Li‐Ion Electrodes

Authors: Sohrab R. Daemi Chun Tan Thomas G. Tranter et al.

Source: Small Methods. 6

Subject Terms: convolutional networks, Neural Networks, Computers, Image Processing, lithium-ion batteries, 02 engineering and technology, 01 natural sciences, computer vision, X-Ray Computed, 0104 chemical sciences, Computer, Computer-Assisted, Image Processing, Computer-Assisted, mask R-CNN, nano X-ray tomography, Neural Networks, Computer, Tomography, X-Ray Computed, 0210 nano-technology, Tomography, Electrodes

Access URL: https://pubmed.ncbi.nlm.nih.gov/36089665
http://hdl.handle.net/10044/1/107781
https://discovery-pp.ucl.ac.uk/id/eprint/10155966/

SASAM: a semantic-aware SAM framework for weld seam vision measurement.

Authors: Zhang, Xingyi Yu, Changqi Chen, Shihao et al.

Source: Measurement Science & Technology; Jul2025, Vol. 36 Issue 7, p1-14, 14p

Subject Terms: LANGUAGE models, JOINING processes, MANUFACTURING processes, IMAGE segmentation, WELDING, DEEP learning

Methods for estimating agricultural cropland yield based on the comparison of NDVI images analyzed by means of Image segmentation algorithms: A tool for spatial planning decisions.

Alternate Title: Métodos de estimación del rendimiento de las tierras de cultivo basados en la comparación de imágenes NDVI analizadas mediante algoritmos de segmentación de imágenes: Una herramienta para la toma de decisiones de planificación espacial

Authors: Hernández Molina, David D. Gulfo Galaraga, Julio M. López López, Ana Milena et al.

Source: INGENIARE - Revista Chilena de Ingeniería. 2023, Vol. 31, p1-12. 12p.

Subject Terms: *IMAGE segmentation, *MULTISPECTRAL imaging, *AGRICULTURE, *NORMALIZED difference vegetation index, *FARMS, *COMPUTER vision, *DIGITAL image processing

Deep Learning for Diabetic Retinopathy Analysis: A Review, Research Challenges, and Future Directions.

Authors: Nadeem, Muhammad Waqas Goh, Hock Guan Hussain, Muzammil et al.

Source: Sensors (14248220); Sep2022, Vol. 22 Issue 18, p6780-N.PAG, 48p

Subject Terms: DIABETIC retinopathy, DEEP learning, IMAGE analysis, IMAGE processing, COMPUTER-assisted image analysis (Medicine), COMPUTER vision

Computer vision segmentation model—deep learning for categorizing microplastic debris

Authors: Sarah-Jeanne Royer Helen Wolter Astrid E. Delorme et al.

Source: Frontiers in Environmental Science, Vol 12 (2024)

Subject Terms: microplastic, deep learning, plastic pollution, segmentation model, marine debris, Environmental sciences, GE1-350

Relation: https://www.frontiersin.org/articles/10.3389/fenvs.2024.1386292/full; https://doaj.org/toc/2296-665X; https://doaj.org/article/094a92e7abd94296a40f99cdb7e31022

Availability: https://doi.org/10.3389/fenvs.2024.1386292
https://doaj.org/article/094a92e7abd94296a40f99cdb7e31022

Single image super-resolution: a comprehensive review and recent insight.

Authors: Al-Mekhlafi, Hanadi Liu, Shiguang

Source: Frontiers of Computer Science; Feb2024, Vol. 18 Issue 1, p1-18, 18p

Efficient CIEDE2000-Based Color Similarity Decision for Computer Vision.

Authors: Pereira, Americo Carvalho, Pedro Coelho, Gil et al.

Source: IEEE Transactions on Circuits & Systems for Video Technology; Jul2020, Vol. 30 Issue 7, p2141-2154, 14p

Subject Terms: COMPUTER vision, VISUAL perception, COLOR, IMAGE processing, COLORS, APPLICATION software, ALGORITHMS