| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 549 | 165 | 225 | 10 |
Artificial intelligence, Computer vision, Algorithm, Pattern recognition and Image (mathematics) are the subjects of interest in Journal of Image and Graphics. The journal primarily discusses Artificial intelligence topics, particularly Pixel, Feature (computer vision), Wavelet, Segmentation and Image segmentation. Topics like Wavelet transform and Wavelet packet decomposition are tackled as part of the discussions on Wavelet.
Stationary wavelet transform is a focus of the presented Wavelet transform works and it dives deep in Stationary wavelet transform. Scale-space segmentation and Segmentation-based object categorization are some of the study areas of Image segmentation discussed. It facilitates discussions on Computer vision that incorporate concepts from other fields like Computer graphics (images) and Robustness (computer science).
The journal explores topics in Algorithm which can be helpful for research in disciplines like Coding (social sciences), Mathematical optimization and Digital watermarking. The research on Pattern recognition tackled can also make contributions to studies in the areas of Facial recognition system and Histogram. The majority of Color image studies are focused on the issues of Color histogram.
The journal papers are mainly concerned with subjects like Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Image (mathematics). Artificial intelligence study tackled in the most cited publications is connected to the field of Computation. The published articles hold forums on Algorithm that merge themes from other disciplines such as Watermark, Canny edge detector, Deriche edge detector, Curvature and Digital watermarking.
Journal of Image and Graphics generally zeroes in on subjects such as Artificial intelligence, Computer vision, Radiology, Pattern recognition and Marine engineering. The work tackled in Journal of Image and Graphics goes beyond the discipline of Artificial intelligence as it also encompasses Presentation. The research on Computer vision featured in it combines topics in other fields like Space (mathematics) and Joint (geology).
While the journal focused on Radiology, it was also able to explore topics like Segmentation and Automatic segmentation. The concepts on Pattern recognition presented in the journal can also apply to other research fields, including Transformation geometry, Probability density function, Detector and Binary descriptor.
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 Image and Graphics (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 Image and Graphics (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, 94.44% 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.
A career in private schools can be rewarding and fulfilling, especially for those who specialize in niche subject matters like Image and Graphics. Particularly, in California where private schools offer latitude for degree specializations and offer programs to students on specialized subjects such as Artificial intelligence, Computer Vision, and Algorithm among others.
Though there's a common understanding that teaching in most private schools requires a degree in education, in reality, that might not be the case for every state. For instance, in California, there are no state laws concerning teacher qualification in private schools. A teacher in a private school does not need to hold a teaching degree or credential, and there is no state oversight of teacher qualification. However, earning a degree in education and completing a teacher certification program will improve your career prospects. While a master’s degree is preferred in most private school settings, especially schools that specialize in subjects like Image and Graphics.
Also, many private schools look for teachers with a master’s or higher degree in their subject area. If you're considering becoming a teacher, you might wonder "do private school teachers need a degree in California"? The answer depends largely on the school. Though it's not technically necessary, having a strong education background, perhaps in Image and Graphics research or a similar field, can certainly make you a more appealing candidate. Having a degree, combined with subject matter knowledge, can help you become a valuable private school teacher.
Ryo Hasegawa;Yutaro Iwamoto
(2020)Kenji Ono;Yutaro Iwamoto
(2020)Jiaqi Wu;Guangxu Li;Huimin Lu
(2021)For students interested in expanding their expertise beyond Computer Science, several closely related online degrees offer valuable career opportunities. Fields such as mechanical and electrical engineering often overlap with computing principles, making programs like mechanical engineering degree online cost a critical consideration for many. These degrees combine technical knowledge with practical design skills, preparing graduates for diverse roles in industries such as manufacturing, robotics, and automation.
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