| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 348 | 142 | 163 | 16 |
The main points discussed in the journal deals with Computer graphics, Computer graphics (images), Visualization, Data visualization and Artificial intelligence. The featured Computer graphics studies mainly concentrate on Human–computer interaction but also cover areas of interest in User interface. The studies on Computer graphics (images) discussed can also contribute to research in the domains of Computational geometry and Solid modeling.
Topics in Visualization explored in it were investigated in conjunction with research in World Wide Web and Data science. Data visualization research featured in it incorporates concerns from various other topics such as Visual analytics and Information visualization. IEEE Computer Graphics and Applications dives deep in exploring the relationship between the study of Artificial intelligence and Computer vision.
IEEE Computer Graphics and Applications concentrates on Computer vision topics that focus on Image processing and Pixel. 3D computer graphics research in the journal involves the investigation of Graphics software studies, all of which are linked to disciplines such as Computer graphics lighting. Issues in Virtual reality were discussed, taking into consideration concepts from other disciplines like Virtual machine and Immersion (virtual reality).
The most cited papers aim to foster the development of research in Computer graphics, Artificial intelligence, Computer vision, Computer graphics (images) and Human–computer interaction. Issues in Computer graphics were discussed in the published papers, taking into consideration concepts from other disciplines like Visualization, Computational geometry, Rendering (computer graphics) and Graphics. The study of Computer graphics (images) in the most cited papers encompasses disciplines such as Solid modeling, as well as fields such as Computer-aided manufacturing, all of which overlap with one another.
The aim of the journal is to expand the discussion of research in Visualization, Data visualization, Artificial intelligence, Data science and Human–computer interaction. The research on Visualization featured in IEEE Computer Graphics and Applications combines topics in other fields like Domain (software engineering), Multimedia, Set (abstract data type), User experience design and Virtual reality. Data modeling, Field (computer science), Climate change, Information retrieval and Use case are some topics wherein Data visualization research discussed in IEEE Computer Graphics and Applications have an impact.
While Artificial intelligence is the focus of it, it also provided insights into the studies of Machine learning, Computer vision and Pattern recognition. Visual analytics and Workflow are some topics wherein Data science research discussed in it have an impact. The Human–computer interaction research presented in the journal explores the relationship between Focus (computing) and the closely related topic of Task analysis.
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 IEEE Computer Graphics and Applications (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 IEEE Computer Graphics and Applications (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, 22.22% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 1.43% were posted by at least one author from the top 10 institutions publishing in the journal. Another 18.57% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 22.86% of all publications and 57.14% 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.
With a rapid evolution in the field of computer graphics and applications, an abundance of career prospects is emerging for students and professionals interested in this domain. One such prospect is the career of a high school art teacher specialized in digital image processing or 3D modeling. To pursue a career teaching art, particularly in areas of computer graphics applications, certain educational qualifications and skill sets are required. For instance, in Alaska, the requirements are unique due to the regional context in the digital art field. For those wondering how to become a high school art teacher in Alaska, it involves acquiring state-level certification after completing an approved teacher education program, including student teaching experience and passing competency exams. In addition to becoming teachers, graphic designers can explore opportunities in fields like web design, animation, UI/UX design, game development, data visualization, AR/VR development, etc. However, the path to success in these fields often involves rigorous training, both formal and informal, and real-world experience. Trends also suggest a growing integration of artificial intelligence in graphic design, broadening the scope for research and career opportunities. To conclude, the field of computer graphics and applications is not limited to academic research. It also opens a wide array of career opportunities for interested individuals. With the right qualifications and passion, one can truly excel in this ever-evolving domain.
Bongshin Lee;Eun Kyoung Choe;Petra Isenberg;Kim Marriott
(2020)Alexandra Luccioni;Victor Schmidt;Vahe Vardanyan;Yoshua Bengio
(2021)Matthias Kraus;Karsten Klein;Johannes Fuchs;Daniel Keim
(2021)William E. Lorensen;Chris Johnson;Dave Kasik;Mary C. Whitton
(2020)Christina Gillmann;Noeska N. Smit;Eduard Groller;Bernhard Preim
(2021)For those interested in advancing their Computer Science education in flexible formats, exploring self paced degrees can be an excellent option. These programs allow students to balance learning with personal and professional commitments, tailoring their progress to individual schedules.
Cost is often a key consideration, especially for graduate studies. Many students find value in cheap masters programs that maintain quality while reducing financial barriers. These affordable options make it easier to gain advanced technical skills without a heavy debt load.
For students just beginning their academic journey or seeking quicker entry into the workforce, understanding what is the easiest associate's degree to get can guide decisions. These programs often emphasize foundational knowledge with shorter completion times, providing a stepping stone into IT and tech-related roles.
Regardless of the degree level, it's essential to verify the reputation of the institution. Attending one of the online universities that are accredited ensures that the education meets established standards, which is crucial for both employment and further study opportunities.
French Institute for Research in Computer Science and Automation - INRIA
Publications: 4
