IEEE Transactions on Computational Imaging

Top Research Topics at IEEE Transactions on Computational Imaging?

IEEE Transactions on Computational Imaging aims to foster the development of research in Artificial intelligence, Iterative reconstruction, Algorithm, Computer vision and Pixel. While Artificial intelligence is the key highlight in IEEE Transactions on Computational Imaging, it also covered some subjects on Pattern recognition and Feature (computer vision). IEEE Transactions on Computational Imaging holds forums on Iterative reconstruction that merges themes from other disciplines such as Image quality, Tomography, Inverse problem and Compressed sensing.

Studies on Tomography discussed in the journal link to the field of Projection (set theory). The Algorithm works featured in IEEE Transactions on Computational Imaging incorporate elements from Sparse matrix, Radar imaging and Robustness (computer science). Topics like Image sensor, Image restoration, Light field, Demosaicing and Noise (video) are tackled as part of the discussions on Computer vision.

Image restoration research discussed connects with the study of Kernel (image processing). Image resolution research presented falls under the umbrella topic of Optics. The Deep learning study tackled is a key component of adjacent topics in the area of Artificial neural network.

• Artificial intelligence (45.32%)
• Iterative reconstruction (43.40%)
• Algorithm (40.43%)

What are the most cited papers published in the journal?

• Loss Functions for Image Restoration With Neural Networks (915 citations)
• Video Super-Resolution With Convolutional Neural Networks (364 citations)
• Plug-and-Play ADMM for Image Restoration: Fixed-Point Convergence and Applications (349 citations)

Research areas of the most cited articles at IEEE Transactions on Computational Imaging:

The main points discussed in the published papers deal with Artificial intelligence, Algorithm, Computer vision, Iterative reconstruction and Compressed sensing. Issues in Algorithm were discussed in the journal articles, taking into consideration concepts from other disciplines like Noise reduction and Minification. The most cited articles focus on Iterative reconstruction but the discussions also offer insight into other areas such as Tomography, Image (mathematics) and Inverse problem.

Papers citation over time

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.

Top authors and change over time

The top authors publishing in IEEE Transactions on Computational Imaging (based on the number of publications) are:

• Charles A. Bouman (14 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• Gonzalo R. Arce (10 papers) published 1 paper at the last edition, 3 less than at the previous edition,
• Jeffrey A. Fessler (9 papers) absent at the last edition,
• Yoann Altmann (8 papers) absent at the last edition,
• Stephen McLaughlin (7 papers) published 1 paper at the last edition, 2 less than at the previous edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in IEEE Transactions on Computational Imaging (based on the number of publications) are:

• Purdue University (25 papers) published 2 papers at the last edition, 3 less than at the previous edition,
• University of Michigan (16 papers) absent at the last edition,
• Heriot-Watt University (14 papers) published 1 paper at the last edition, 3 less than at the previous edition,
• University of Delaware (11 papers) published 1 paper at the last edition, 3 less than at the previous edition,
• University of Toulouse (11 papers) published 1 paper at the last edition, 3 less than at the previous edition.

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.

Publication chance based on affiliation

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, 8.89% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 15.85% were posted by at least one author from the top 10 institutions publishing in the journal. Another 20.73% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 29.27% of all publications and 34.15% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

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