Advances in Machine Vision for Industry and Agriculture
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 30 December 2024 | Viewed by 65
Special Issue Editors
Interests: machine vision; recycling; robotics; renewable energy sources; embedded systems; environmental sustainability; neural network; waste management; convolutional neural network; object detection
Interests: virtual and augmented reality; computer vision; image and video processing; image analysis; machine learning; pattern recognition with applications also to medical image analysis and biometrics
Special Issues, Collections and Topics in MDPI journals
Interests: computer architecture; robotics; embedded and cyber-physical systems; gamification; Internet of Things; security and hardware & software cosynthesis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Machine vision has become increasingly useful in many areas in recent years, particularly in the industrial and agricultural sectors, where there seems to be a significant scope for further research. This Special Issue aims to provide concentrated and multidimensional knowledge to researchers and practitioners to showcase their latest advancements, methodologies, and insights in these areas, fostering collaboration and knowledge exchange to address current challenges and propel innovation forward.
Prospective authors are invited to submit original research articles, review papers, and short communications relevant to the theme of this Special Issue. Submissions will undergo a rigorous peer-review process to ensure the quality and significance of accepted contributions. Contributions are invited on a broad spectrum of topics related to machine vision in industry and agriculture, including, but not limited to, the following:
- Machine vision in precision agriculture;
- Automated visual inspection;
- Novel computational methods and methodology on machine vision;
- Experimental techniques and validation studies in machine vision in industry and agriculture;
- Pattern recognition;
- Robot application utilizing machine vision;
- Image analysis for machine vision;
- Robot control using machine vision;
- Agrobots utilizing machine vision;
- Case studies, practical applications, and real-world challenges in the sector of machine vision.
Dr. Dimitris Ziouzios
Dr. Michalis Vrigkas
Dr. Minas Dasygenis
Guest Editors
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 submissions that pass pre-check are 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. Applied Sciences 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 2400 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.
Keywords
- machine vision
- precision agriculture
- recycling
- agrobots
- industry 4.0l
- smart systems
- vision algorithms
- robotics
