| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 974 | 11 | 14 | 3 |
International Journal of Intelligent Systems Technologies and Applications was organized to reinforce research efforts on Artificial intelligence, Computer vision, Control theory, Control engineering and Pattern recognition. Studies on Artificial intelligence discussed in International Journal of Intelligent Systems Technologies and Applications link to the field of Machine learning. The journal focused on Machine learning research but expanded to cover Data mining.
Segmentation and Pixel are all topics related to Computer vision research discussed. The in-depth study on Control theory also explores topics in the intersecting field of Fuzzy logic. It links adjacent topics like Control engineering with Control system.
It emphasizes research on Pattern recognition, which includes concerns such as Feature extraction. Topics like Robot control and Mobile robot are tackled as part of the discussions on Robot. International Journal of Intelligent Systems Technologies and Applications explores research in Artificial neural network and the adjacent study of Algorithm.
The journal papers explore disciplines such as Artificial intelligence, Computer vision, Algorithm, Pixel and Time-of-flight camera. The most cited publications focus on Artificial intelligence research which is adjacent to topics in Calibration. While Computer vision is the key highlight in the most cited papers, thet also covered some subjects on Robot calibration and Collision avoidance (spacecraft), Mobile robot navigation, Structure from motion, Translation (geometry) and Filter (signal processing).
The aim of the journal is to expand the discussion of research in Artificial intelligence, The Internet, Computer security, Field (computer science) and Ball (bearing). The journal primarily discusses Artificial intelligence topics, particularly Medical imaging, Local search (optimization), Selection (genetic algorithm), Taxonomy (general) and Contextual image classification. Bandwidth (computing), Privacy protection and SIMPLE (military communications protocol) are some topics wherein The Internet research discussed in it have an impact.
The featured works in Security analysis and Authentication protocol, which all belong in the domain if Computer security, also overlaps with concepts under Smart environment and Home automation. The research on Field (computer science) tackled can also make contributions to studies in the areas of Identification (information), Benchmark (computing), Swarm intelligence and Feature selection, Pattern recognition. It facilitates discussions on Ball (bearing) that incorporate concepts from other fields like Industrial robot, Tracking (particle physics), Computer vision and Trajectory.
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 International Journal of Intelligent Systems Technologies 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 International Journal of Intelligent Systems Technologies 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, 20.00% 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 25.00% of all publications and 75.00% 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.
Interest in studying Intelligent Systems and Technologies, such as Artificial Intelligence (AI), Computer Vision, and Machine Learning, often leads individuals to ponder about applicable career paths. For instance, those with a particular interest in AI and education may consider pursuing a path towards becoming an elementary teacher specializing in the introduction of AI basics. If you're located in New Mexico and are interested in teaching elementary students about the wonders of AI, we have a guide on how to become an elementary teacher in New Mexico. Knowing early on what career you can jump into right after studying these intelligent systems technologies can aid in formulating a focused academic and professional roadmap. There are numerous career opportunities in AI and related fields. AI specialists can work in different sectors such as healthcare, e-commerce, social media, or even in government agencies. Some of the most common job titles include AI Specialist, Software Engineer, Data Scientist, Machine Learning Engineer, and Research Scientist. Each role may require a specific set of skills. For instance, a machine learning engineer might need to have a grasp of programming languages like Python, C++, and Java. Meanwhile, a data scientist should be proficient in using data handling tools and methodologies, including SQL, data mining, and data integration. Understanding early what these roles entail, and the knowledge you'll need to acquire, can help you make the most of your studies in artificial intelligence and its myriad applications.
Imran Qureshi;Muhammad Attique Khan;Muhammad Sharif;Tanzila Saba
(2020)Benito Taccardi;Piercosimo Rametta;Pierluigi Carcagnì;Marco Leo
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