| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 523 | 36 | 35 | 11 |
The scientific interests tackled in the journal are Artificial intelligence, Pattern recognition (psychology), Computer vision, Biometrics and Pattern recognition. Image processing, Segmentation, Feature (computer vision), Pixel and Robustness (computer science) are some of the facets of Artificial intelligence tackled in it. It emphasizes research on Image processing, which includes concerns such as Digital image processing.
Issues in Pattern recognition (psychology) were discussed, taking into consideration concepts from other disciplines like Face (geometry), Image (mathematics), Algorithm and Machine learning, Convolutional neural network. Research on Computer vision presented in the journal focuses, in particular, on Video tracking, Image segmentation, Image quality, Tracking (particle physics) and Feature detection (computer vision). While the journal focused on Biometrics, it was also able to explore topics like Classifier (UML), Speech recognition, Multimedia, Deep learning and Coding (social sciences).
The research on Pattern recognition tackled can also make contributions to studies in the areas of Histogram, Local binary patterns and Facial recognition system.
The most cited publications primarily tackle Artificial intelligence, Computer vision, Pattern recognition (psychology), Biometrics and Pattern recognition. The published articles explore research in Machine learning and overlapping concepts in Pixel to expand the discourse in Artificial intelligence. The journal publications focus on Computer vision but sometimes tackle the closely related topic of Coding (social sciences) which is concerned with Scalability.
The journal primarily tackles Pattern recognition (psychology), Artificial intelligence, Biometrics, Pattern recognition and Convolutional neural network. The work on Pattern recognition (psychology) tackled in it brings together disciplines like Landmark, Code (cryptography), Object (computer science), Image (mathematics) and Function (mathematics). It facilitates discussions on Artificial intelligence that incorporate concepts from other fields like Machine learning and Computer vision.
Research on Computer vision addressed in the journal frequently intersections with the field of Robustness (computer science). The journal addresses concerns in Biometrics which are intertwined with other disciplines, such as Point (geometry), Coding (social sciences), Steganography and Benchmark (computing). It features works in Pattern recognition, more specifically Segmentation, and explores their relation to disciplines like IIf.
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 Eurasip Journal on Image and Video Processing (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 Eurasip Journal on Image and Video Processing (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 2021 edition, 6.25% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 20.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 20.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 3.33% of all publications and 56.67% 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 are a scholar or researcher who specializes in the topics covered by Eurasip Journal on Image and Video Processing, contributing an article can be a significant addition to your CV. Contributors to the journal are typically experts working in fields related to Artificial intelligence, Computer vision, Pattern recognition, and Biometrics, to name a few.
To successfully submit your work to the journal, it is crucial to adhere to their submission guidelines and ensure that your research falls under their topics of interest. Prospective contributors should also be prepared to undergo a peer review process.
Contributors come from various backgrounds, including Ph.D. candidates, professors, and experts working in the field. For those committed to a career in academia, like becoming a high school history teacher in Pennsylvania, having published work in respected journals such as the Eurasip Journal on Image and Video Processing can significantly bolster their credibility in the field.
The road to publication may be challenging, but it can be gratifying for those dedicated to their respective disciplines. Best of luck to all prospective contributors!
Jannis Priesnitz;Christian Rathgeb;Nicolas Buchmann;Christoph Busch
(2021)Renjie Zhu;Xinpeng Zhang;Mengte Shi;Zhenjun Tang
(2020)Wei Xiong;Wei Xiong;Lei Zhou;Ling Yue;Lirong Li
(2021)Yi Cao;Zhili Zhou;Q. M. Jonathan Wu;Chengsheng Yuan
(2020)Muhammad Attique Khan;Tallha Akram;Muhammad Sharif;Majed Alhaisoni
(2021)Chih Shuan Huang;Ya Han Huang;Din Yuen Chan;Jar Ferr Yang
(2020)Lin He;Xiaomin Yang;Lu Lu;Wei Wu
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