Aurelio Campilho – författare

This two-volume set LNCS 11662 and 11663 constitutes the refereed proceedings of the 16th International Conference on Image Analysis and Recognition, ICIAR 2019, held in Waterloo, ON, Canada, in August 2019.

This two-volume set LNCS 11662 and 11663 constitutes the refereed proceedings of the 16th International Conference on Image Analysis and Recognition, ICIAR 2019, held in Waterloo, ON, Canada, in August 2019.

This two-volume set LNCS 12131 and LNCS 12132 constitutes the refereed proceedings of the 17th International Conference on Image Analysis and Recognition, ICIAR 2020, held in Póvoa de Varzim, Portugal, in June 2020.The 54 full papers presented together with 15 short papers were carefully reviewed and selected from 123 submissions. The papers are organized in the following topical sections: image processing and analysis; video analysis; computer vision; 3D computer vision; machine learning; medical image and analysis; analysis of histopathology images; diagnosis and screening of ophthalmic diseases; and grand challenge on automatic lung cancer patient management.

Due to the corona pandemic, ICIAR 2020 was held virtually only.

This two-volume set LNCS 12131 and LNCS 12132 constitutes the refereed proceedings of the 17th International Conference on Image Analysis and Recognition, ICIAR 2020, held in Póvoa de Varzim, Portugal, in June 2020.The 54 full papers presented together with 15 short papers were carefully reviewed and selected from 123 submissions. The papers are organized in the following topical sections: image processing and analysis; video analysis; computer vision; 3D computer vision; machine learning; medical image and analysis; analysis of histopathology images; diagnosis and screening of ophthalmic diseases; and grand challenge on automatic lung cancer patient management.

Due to the corona pandemic, ICIAR 2020 was held virtually only.

This book constitutes the thoroughly refereed proceedings of the 13th International Conference on Image Analysis and Recognition, ICIAR 2016, held in Póvoa de Varzim, Portugal, in July 2016. The 79 revised full papers and 10 short papers presented were carefully reviewed and selected from 167 submissions. The papers are organized in the following topical sections: Advances in Data Analytics and Pattern Recognition with Applications, Image Enhancement and Restoration, Image Quality Assessment, Image Segmentation, Pattern Analysis and Recognition, Feature Extraction, Detection and Recognition, Matching, Motion and Tracking, 3D Computer Vision, RGB-D Camera Applications, Visual Perception in Robotics, Biometrics, Biomedical Imaging, Brain Imaging, Cardiovascular Image Analysis, Image Analysis in Ophthalmology, Document Analysis, Applications, and Obituaries.

The chapter ''Morphological Separation of Clustered Nuclei in Histological Images'' is published open access under a CCBY 4.0 license at link.springer.com. 

The 73 revised full papers presented were carefully reviewed and selected from 133 submissions. The papers are organized in the following topical sections: machine learning in image recognition; machine learning for medical image computing; image enhancement and reconstruction; image segmentation; motion and tracking; 3D computer vision; feature extraction; detection and classification; biomedical image analysis; image analysis in ophthalmology; remote sensing; applications.

This book constitutes the thoroughly refereed proceedings of the 15th International Conference on Image Analysis and Recognition, ICIAR 2018, held in Póvoa de Varzim, Portugal, in June 2018.

The 91 full papers presented together with 15 short papers were carefully reviewed and selected from 179 submissions. The papers are organized in the following topical sections: Enhancement, Restoration and Reconstruction, Image Segmentation, Detection, Classication and Recognition, Indexing and Retrieval, Computer Vision, Activity Recognition, Traffic and Surveillance, Applications, Biomedical Image Analysis, Diagnosis and Screening of Ophthalmic Diseases, and Challenge on Breast Cancer Histology Images.