| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 887 | 25 | 24 | 4 |
The journal focuses on Artificial intelligence, Algorithm, Pattern recognition, Computer vision and Humanities. Traitement Du Signal encompasses presentations on Artificial intelligence, specifically Image (mathematics), Segmentation, Image processing, Convolutional neural network and Feature extraction. Most of the works presented in it deals with Algorithm but it intersects with the subject of Signal.
The most cited publications aim to foster the development of research in Artificial intelligence, Algorithm, Image segmentation, Signal processing and Humanities. Machine learning, Computer vision and Pattern recognition are some topics wherein Artificial intelligence research discussed in the journal papers has an impact. Issues in Algorithm were discussed in the most cited publications, taking into consideration concepts from other disciplines like Self-organizing map, Coding (social sciences) and Digital watermarking.
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 Traitement Du Signal (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 Traitement Du Signal (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, 99.25% 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 100.00% 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 0.00% 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.
Traitement Du Signal, as a journal focusing on various aspects of signal processing, including Artificial Intelligence, Algorithms, and even Humanities, appeals to a range of professionals and academics in the field. Being a part of such research not only paves the way for endless career opportunities but also contributes significantly to the world of knowledge and technologically advanced solutions. An example of the expansive career spectrum in this field includes not merely researchers and scientists, but also education professionals such as elementary school teachers who need a solid foundation in these subjects to influence the next generation's learning process. You can read more about the importance of understanding such technologies in the teaching profession in our article on how to become an elementary teacher in Massachusetts.
However, it doesn't stop at teaching. Signal Processing and related fields have applications in industries as varied as healthcare, defense, entertainment, and more. Thus, building or enhancing career opportunities in this area may be advantageous due to the range of industries looking for experts in signal processing and related fields. Therefore, whether it is academia, industry research, or teaching, the discipline of Signal Processing research offers a wide variety of career paths for interested individuals.
Chaima Ben Rabah;Gouenou Coatrieux;Riadh Abdelfattah
(2020)Hichem Telli;Salim Sbaa;Salah Eddine Bekhouche;Fadi Dornaika
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