Elsevier Ltd
1872-8138
Monthly
4.2
0262-8856
2025
31204853911
Netherlands The
English
YES
Google Scholar
imavis@elsevier.com
Image and Vision Computing has as a primary aim the provision of an effective medium of interchange for the results of high quality theoretical and applied research fundamental to all aspects of image interpretation and computer vision. The journal publishes work that proposes new image interpretation and computer vision methodology or addresses the application of such methods to real world scenes. It seeks to strengthen a deeper understanding in the discipline by encouraging the quantitative comparison and performance evaluation of the proposed methodology. The coverage includes: image interpretation, scene modelling, object recognition and tracking, shape analysis, monitoring and surveillance, active vision and robotic systems, SLAM, biologically-inspired computer vision, motion analysis, stereo vision, document image understanding, character and handwritten text recognition, face and gesture recognition, biometrics, vision-based human-computer interaction, human activity and behavior understanding, data fusion from multiple sensor inputs, image databases. In addition to regular manuscripts, Image and Vision Computing Journal solicits manuscripts for the Opinions Column, aimed at initiating a free forum for vision researchers to express their opinions on past, current, or future successes and challenges in research and the community. An opinion paper should be succinct and focused on a particular topic. Addressing multiple related topics is also possible if this helps making the point. While posing questions helps raising awareness about certain issues, ideally, an opinion paper should also suggest a concrete direction how to address the issues. Topics of interest include, but are not limited to: Comments on success and challenges in a (sub-) field of computer vision, Remarks on new frontiers in computer vision Observations on current practices and trends in research, and suggestions for overcoming unsatisfying aspects Observations on current practices and trends in the community regarding, e.g., reviewing process, organizing conferences, how journals are run, and suggestions for overcoming unsatisfying aspects Reviews of early seminal work that may have fallen out of fashion Summaries of the evolution of one's line of research Recommendations for educating new generations of vision researchers.
One of the primary limitations of deep learning is data-hungry techniques. Deep learning approaches do not typically generalize well for limited datasets with fewer samples. Drawing the insp...
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