0923-5965
Published by: Elsevier
https://www.sciencedirect.com/journal/signal-processing-image-communication
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 267 | 152 | 189 | 21 |
| Electronics and Electrical Engineering | 392 | 15 | 21 | 7 |
Artificial intelligence, Computer vision, Algorithm, Pattern recognition and Coding (social sciences) are the subjects of interest in the journal. Presentations on Artificial intelligence include those discussing Image processing, Image (mathematics), Image quality, Pixel and Motion estimation. The Image quality study tackled is a key component of adjacent topics in the area of Human visual system model.
The study on Motion estimation featured in Signal Processing-image Communication expounds on the topic of Quarter-pixel motion in particular. Data compression, Motion compensation, Image compression, Discrete cosine transform and Segmentation are all subfields of Computer vision research that were featured in it. The journal holds forums on Algorithm that merges themes from other disciplines such as Encoder, Real-time computing, Wavelet and Theoretical computer science.
Wavelet research presented is mostly focused on the subject of Wavelet transform. Pattern recognition research featured in the journal incorporates concerns from various other topics such as Feature (computer vision) and Robustness (computer science). It investigates Coding (social sciences) research which frequently intersects with Codec.
The journal papers primarily focus on research topics in Artificial intelligence, Computer vision, Image processing, Image quality and Algorithm. The studies on Artificial intelligence discussed at the journal papers can also contribute to research in the domains of Coding (social sciences) and Pattern recognition. Aside from discussions in Algorithm, the most cited articles also deal with the subject of Encryption which intersects with Theoretical computer science disciplines.
The scientific interests tackled in Signal Processing-image Communication are Artificial intelligence, Computer vision, Natural (archaeology), Clock rate and Throughput (business). In addition to Artificial intelligence research, Signal Processing-image Communication aims to explore topics under Key (cryptography) and Pattern recognition. Topics in Clock rate were tackled in line with various other fields like Deblocking filter, Parallel processing (DSP implementation), Encoder, Coding tree unit and Block (data storage).
Signal Processing-image Communication aims to bridge the gap between the study of Throughput (business) and research in different fields like Computer hardware and Hardware architecture.
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 Signal Processing-image Communication (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 Signal Processing-image Communication (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, 33.33% 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.
The article provides a comprehensive review of various research topics, the most cited papers, key areas of study, and other elements that make the field of Signal Processing and Image Communication diverse and exciting. However, it is also pivotal to discuss the career opportunities and professional growth within this domain. This section aims to provide relevant information on how to become professionally involved in this field and what to expect in terms of career perspectives. If you are interested in pursuing a career in signal processing and image communication, it would be beneficial to start with a strong foundation in the basics of computer science and develop a particular interest and expertise in fields like artificial intelligence and computer vision. In addition, having a strong understanding of algorithms and pattern recognition can play a pivotal role in making you a sought-after professional in the field. Aside from the technical skills, successful professionals in this field also often demonstrate strong analytical thinking abilities, problem-solving skills, and a keen interest in image processing and quality. There are diverse roles that you can aspire to within this domain, such as research scientist, data scientist, signal processing engineer, or a teacher in related subjects. For instance, if you are interested in teaching, you may find guidance on becoming an English educator in a relevant area, such as Utah, on our dedicated career page. Here is a helpful guide on {anchor} how to be an english teacher in utah. Finally, it is important to note that the field of Signal Processing and Image Communication is constantly evolving, which requires ongoing learning and skill enhancement. This commitment to continual learning will enable you to stay abreast of the latest research and developments in the field, and ultimately, enhance your professional growth and career prospects in the long run.
Muwei Jian;Muwei Jian;Muwei Jian;Xiangyu Liu;Hanjiang Luo;Xiangwei Lu
(2021)Xueyang Fu;Xiangyong Cao
(2020)Ning Yang;Qihang Zhong;Kun Li;Runmin Cong;Runmin Cong
(2021)Ling Du;Anthony T.S. Ho;Anthony T.S. Ho;Anthony T.S. Ho;Runmin Cong
(2020)Yuling Xi;Yanning Zhang;Songtao Ding;Shaohua Wan;Shaohua Wan
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