| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 246 | 28 | 42 | 11 |
| Computer Science | 335 | 68 | 91 | 17 |
| Engineering and Technology | 823 | 19 | 28 | 10 |
The journal covers a variety of subjects, including Artificial intelligence, Algorithm, Computer vision, Mathematical analysis and Image (mathematics). Studies on Artificial intelligence discussed in it link to the field of Pattern recognition. Algorithm research featured in the journal incorporates concerns from various other topics such as Image restoration, Mathematical optimization and Topology.
The journal focused on Mathematical optimization research but expanded to cover Applied mathematics. Image segmentation is a focus of the presented Segmentation works and it dives deep in Image segmentation. The majority of Image segmentation studies in the journal are focused on the subject of Scale-space segmentation.
The study on Scale-space segmentation featured in Journal of Mathematical Imaging and Vision expounds on the topic of Segmentation-based object categorization in particular.
Algorithm, Artificial intelligence, Computer vision, Topology and Mathematical analysis are the main subjects of interest in the journal articles. Specifically, studies on Total variation denoising are prevalent in the Algorithm works discussed in the journal articles. Most of the Artificial intelligence studies addressed in the published articles also intersect with Pattern recognition.
Journal of Mathematical Imaging and Vision is mainly concerned with subjects like Algorithm, Artificial intelligence, Mathematical analysis, Applied mathematics and Image (mathematics). It explores topics in Algorithm which can be helpful for research in disciplines like Segmentation, Image segmentation, Poisson distribution, Noise (video) and Noise. It holds forums on Artificial intelligence that merges themes from other disciplines such as Computer vision and Pattern recognition.
Journal of Mathematical Imaging and Vision explores issues in Computer vision which can be linked to other research areas like Lens (optics) and Motion (geometry). The Mathematical analysis works featured in Journal of Mathematical Imaging and Vision incorporate elements from Boundary (topology) and Projection (mathematics). The featured Image (mathematics) research zeroes in on concepts in Contextual image classification but also tackles themes under Redundancy (engineering).
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 Journal of Mathematical Imaging and 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 Journal of Mathematical Imaging and 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 2021 edition, 10.29% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 18.03% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.56% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 13.11% of all publications and 62.30% 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.
Lars Ruthotto;Eldad Haber
(2020)Sören Dittmer;Tobias Kluth;Peter Maass;Daniel Otero Baguer
(2020)Mujibur Rahman Chowdhury;Jing Qin;Yifei Lou
(2020)Ivan W. Selesnick;Alessandro Lanza;Serena Morigi;Fiorella Sgallari
(2020)Zhihui Zhu;Daniel Soudry;Yonina C. Eldar;Michael B. Wakin
(2020)Alexander Effland;Erich Kobler;Karl Kunisch;Thomas Pock
(2020)Rémi Gribonval;Mila Nikolova
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