Special Issue "3D Images, Point Clouds and Videos Classification and Management by Means of Artificial Intelligence Approaches from Industrial to Agriculture Applications"
Deadline for manuscript submissions: 15 October 2020.
Interests: supervised classification; one-class classification; machine learning; pattern precognition; nearest neighbor algorithm; genetic algorithms; estimation of distribution algorithms; Bayesian networks; applications in medicine; machine learning and data mining in general
Interests: computer vision; biometric applications; machine learning; 3D vision; deep learning
Interests: machine learning; computer vision; 3D vision; deep learning; video action recognition
In recent years, image capture systems have increasingly been used in industrial, commercial, and agricultural applications as a means to obtain information which could improve the quality of the obtained products. The methodologies and technologies related to video processing, imaging processing, 3D modeling, and multimedia have significantly been implemented in the field of computer vision. The continuous development of these technologies has led to an introduction of new methodologies and applications in this field. Machine learning algorithms and deep learning provide paradigms to process and classify obtained 3D images or point clouds, as well as video action recognition.
Recently, advancements in sensor technologies that acquire point cloud data have paved the way for the development of new ideas, methodologies, and solutions in countless remote sensing applications.
This Special Issue addresses the latest research advances in 3D image, point cloud, and video classification. This covers a wide area of applications, such as industrial pieces recognition, crop status management, video action recognition, etc. and several techniques: machine learning, deep learning, etc. The papers will help readers to explore and share their knowledge and experience in technologies and development techniques.
Prof. Dr. Basilio Sierra
Dr. Naiara Aginako
Dr. José María Martínez-Otzeta
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- artificial intelligence
- machine learning
- 3D model processing
- robotic applications
- deep learning for point cloud processing
- point cloud classification
- modeling urban and natural environments from aerial and mobile LiDAR/image-based point clouds
- industrial applications with large-scale point clouds
- machine and robot vision
- 3D Image detection, recognition, and tracking
- biometrics and biomedical image analysis
- action recognition
- mathematical methods in image processing, analysis, and representation
- artificial intelligence tools in image analysis
- pattern recognition algorithms applied for images