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Journal of Imaging is a peer-reviewed journal published by MDPI, covering Advanced Neural Network Applications, AI in cancer detection, Radiomics and Machine Learning in Medical Imaging. Over its lifetime it has published 2,509 papers, which have received 33,038 citations.
| Publisher | MDPI |
|---|---|
| Reference style | Numbered (MDPI) Numbered — [1], [2] in the text 1. Smith, A.; Jones, B.; Lee, C. A Representative Article Title. Journal of Imaging 2023, 12, 45–58.
Formats any DOI in Journal of Imaging style. No sign-up. |
| Abbreviation (ISO-4) | J. Imaging |
| Publishes research in | Advanced Neural Network Applications AI in cancer detection Radiomics and Machine Learning in Medical Imaging Advanced Image and Video Retrieval Techniques Advanced Vision and Imaging |
| ISSN | 2313-433X |
| Citation impact (2-yr) | 3.83 |
| h-index | 72 |
| i10-index | 857 |
| Article processing charge | $1,732 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | Centre National de la Recherche Scientifique |
| Journal website | www.mdpi.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Hand gestures are a form of nonverbal communication that can be used in several fields such as communication between deaf-mute people, robot control, human-computer interaction (HCI), home automation and medical applications. Research papers based on hand gestures have adopted many different techniques, including those based on instrumented sensor technology and computer vision. In other words,…
Modern hyperspectral imaging systems produce huge datasets potentially conveying a great abundance of information; such a resource, however, poses many challenges in the analysis and interpretation of these data. Deep learning approaches certainly offer a great variety of opportunities for solving classical imaging tasks and also for approaching new stimulating problems in the spatial-spectral domain.…
In the past decade, deep neural networks, particularly convolutional neural networks, have revolutionised computer vision. However, all deep learning models may require a large amount of data so as to achieve satisfying results. Unfortunately, the availability of sufficient amounts of data for real-world problems is not always possible, and it is well recognised that a…
Machine vision for precision agriculture has attracted considerable research interest in recent years. The aim of this paper is to review the most recent work in the application of machine vision to agriculture, mainly for crop farming. This study can serve as a research guide for the researcher and practitioner alike in applying cognitive technology…
Crop growth models simulate the relationship between plants and the environment to predict the expected yield for applications such as crop management and agronomic decision making, as well as to study the potential impacts of climate change on food security. A major limitation of crop growth models is the lack of spatial information on the…
