| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 27 | 637 | 808 | 83 |
The main research concerns discussed in the journal are Artificial intelligence, Computer vision, Pattern recognition (psychology), Pattern recognition and Image processing. The studies on Artificial intelligence discussed can also contribute to research in the domains of Algorithm and Machine learning. Studies on Algorithm discussed in International Journal of Computer Vision link to the field of Mathematical optimization.
The journal focuses on Computer vision as well as the interrelated topic of Robustness (computer science). The Pattern recognition (psychology) works featured in the journal incorporate elements from Feature (computer vision), Representation (mathematics), Face (geometry), Deep learning and Convolutional neural network. Pattern recognition research featured in it incorporates concerns from various other topics such as Object detection and Facial recognition system.
Image processing research is concerned with Edge detection in particular. In particular, the Segmentation works presented emphasize discussions on Scale-space segmentation. Research on Motion estimation addressed in the journal frequently intersections with the field of Optical flow.
The journal papers cover a variety of subjects, including Artificial intelligence, Computer vision, Pattern recognition (psychology), Image processing and Pattern recognition. The studies on Artificial intelligence discussed at the most cited articles can also contribute to research in the domains of Algorithm and Machine learning. The featured Pattern recognition (psychology) studies in the journal articles mainly concentrate on Convolutional neural network but also cover areas of interest in Deep learning.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in International Journal of Computer Vision (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in International Journal of Computer Vision (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2022 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 100.00% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
If you're interested in contributing to the discussions featured in the International Journal of Computer Vision, you can consider conducting research in the numerous research concerns discussed in the journal such as Artificial intelligence, Computer vision, Pattern recognition (psychology), Pattern recognition, and Image processing. Before you do that, it's imperative to familiarize yourself with the most cited papers and research areas of interest, which would give you a strong foundation in the subject areas the journal covers. Moreover, it's important to understand the citation trends over time, as well as the contributions of top authors and institutions to the journal. Following their published work in the Journal could help budding authors identify trends in popular topics, and shape their research to align with the Journal's audience and reach. Furthermore, a good grasp of the Returning Authors Index and Experience to Innovation Index could offer insights into patterns from which you could learn. For example, you'll understand if authors usually submit their papers to the Journal consecutively and see if authors with varying experience levels contribute their work. Finally, it could be beneficial to note the contributions of the top institutions in the field, particularly if you're affiliated with an institution. This could help identify collaborations and opportunities to expand the reach of your own research. If you're an aspiring educator with a particular interest in elementary education, you may wish to combine these interests using valuable resources such as this comprehensive guide on {how to become an elementary teacher in missouri}. Education plays a crucial role in technology adoption and the development of AI-based techniques. This guide could provide valuable insights while working on research in these subject areas.
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(2020)Unknown
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Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)
Publications: 8
