World's Best Scientists 2026 revealed!
Electronic Imaging (Ingenta)
H-index 12

Electronic Imaging (Ingenta)

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Electronics and Electrical Engineering 438 18 36 5
Computer Science 508 94 258 11
Engineering and Technology 1340 13 31 3

Additional Metrics

Number of Best Scientists*: 142
Documents by Best Scientists*: 326
Top 100 Ranked Scientists*: 1
SCIMAGO H-index:
SCIMAGO SJR:
Impact Factor: N/A

Overview

Top Research Topics at electronic imaging?

The main research concerns discussed in electronic imaging are Artificial intelligence, Computer vision, Image processing, Optics and Computer graphics (images). Studies on Artificial intelligence discussed in it link to the field of Pattern recognition. Electronic imaging tackles issues in Computer vision, particularly in the topics of Stereoscopy, Segmentation, Image sensor, Image resolution and Image compression.

Electronic imaging focuses on Stereoscopy as well as the interrelated topic of Stereo display. It features Image compression research that overlaps with concepts in Data compression. Image processing research featured in it incorporates concerns from various other topics such as Algorithm and Image segmentation.

The work on Optics addressed in it expands to the thematically related Optoelectronics. Computer graphics (images) and Visualization are closely related fields of research discussed in it.

  • Artificial intelligence (51.37%)
  • Computer vision (44.39%)
  • Image processing (15.58%)

What are the most cited papers published in the journal?

  • Depth-image-based rendering (DIBR), compression, and transmission for a new approach on 3D-TV (1293 citations)
  • UCID: an uncompressed color image database (880 citations)
  • Impact of Artificial "Gummy" Fingers on Fingerprint Systems (689 citations)

Research areas of the most cited articles at electronic imaging:

The published papers explore disciplines such as Artificial intelligence, Computer vision, Image processing, Computer graphics (images) and Digital watermarking. The most cited publications deal with Artificial intelligence in conjunction with Pattern recognition and similar fields in Steganalysis. The studies on Computer graphics (images) discussed at the journal publications can also contribute to research in the domains of Liquid-crystal display, Visualization and Autostereoscopy.

What topics the last edition of the journal is best known for?

  • Artificial intelligence
  • Optics
  • Operating system

The previous edition focused in particular on these issues:

The objective of the journal is to combine knowledge in the areas of Artificial intelligence, Computer vision, Pattern recognition, Optics and Human–computer interaction. Many of the studies tackled connect Artificial intelligence with a similar field of study like Machine learning. The journal focused on Computer vision research but expanded to cover Quality (business).

The most cited articles from the last journal are:

  • An End-to-End Food Image Analysis System (4 citations)
  • Analysis of IoT Security Risks based on the exposure of the MQTT Protocol (1 citations)
  • The effect of display brightness and viewing distance: a dataset for visually lossless image compression (1 citations)

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.

The top authors publishing in electronic imaging (based on the number of publications) are:

  • Jan P. Allebach (93 papers) published 12 papers at the last edition, 3 less than at the previous edition,
  • Karen Egiazarian (67 papers) published 2 papers at the last edition, 3 less than at the previous edition,
  • Edward J. Delp (46 papers) published 2 papers at the last edition the same number as at the previous edition,
  • Sos S. Agaian (45 papers) absent at the last edition,
  • Reiner Creutzburg (40 papers) published 12 papers at the last edition, 1 more 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.

Only papers with recognized affiliations are considered

The top affiliations publishing in electronic imaging (based on the number of publications) are:

  • Purdue University (128 papers) absent at the last edition,
  • Tampere University of Technology (102 papers) absent at the last edition,
  • Hewlett-Packard (98 papers) absent at the last edition,
  • Philips (66 papers) absent at the last edition,
  • Stanford University (65 papers) absent at the last 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, 98.54% 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.

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.

Career Prospects in Electronic Imaging

In recent years, the field of electronic imaging has seen great advancements, with significant research focused on areas like artificial intelligence, computer vision, and image processing. These fields overlap with numerous other areas such as optics and computer graphics. Therefore, a professional with expertise in electronic imaging has a diverse range of career options. One such avenue is to become an educator. If you have a gift for instructing others and wish to further expand knowledge in this field, you could consider a career in teaching. Besides the basic requirements, individual states may have specific criteria that need to be met. For instance, if you want to know about the specifics to become a teacher in Hawaii, our career guide can help. You can find more details about this pathway, including the educational prerequisites, state-specific licensure information, and expected salary ranges by visiting How to Become an Elementary Teacher in Hawaii. Beyond teaching, there are numerous other verticals within the electronic imaging sector. Careers within research institutions, tech companies, and the digital art industry are booming. Job roles can vary significantly, from roles focusing on AI and machine learning to positions in graphic design and 3D visualizations. This field's breadth and diversity forward make it an excellent choice for those interested in a dynamic and evolving career path. It's certainly worth considering if you have a passion for technology and innovation. Whatever route you take, remember: continuous learning and keeping up-to-date with recent research will always be keys to success.

Top Publications

  • Watermarking in Deep Neural Networks via Error Back-propagation.

    Jiangfeng Wang;Hanzhou Wu;Xinpeng Zhang;Yuwei Yao

    (2020)
    54 Citations
  • WearMask: Fast in-browser face mask detection with serverless edge computing for COVID-19

    (2023)
    35 Citations
  • Generative Text Steganography Based on LSTM Network and Attention Mechanism with Keywords.

    Huixian Kang;Hanzhou Wu;Xinpeng Zhang

    (2020)
    28 Citations
  • Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars

    Anthony Bourached;George Cann;Ryan-Rhys Griffiths;David G. Stork

    (2021)
    15 Citations
  • Frequency Domain-Based Detection of Generated Audio.

    Emily R. Bartusiak;Edward J. Delp

    (2021)
    15 Citations
  • Detection, Attribution and Localization of GAN Generated Images

    Michael Goebel;Lakshmanan Nataraj;Tejaswi Nanjundaswamy;Tajuddin Manhar Mohammed

    (2021)
    15 Citations
  • Synthetic speech attribution using self supervised audio spectrogram transformer

    (2023)
    14 Citations
  • Controllable Medical Image Generation via Generative Adversarial Networks.

    Zhihang Ren;Stella X. Yu;David Whitney

    (2021)
    13 Citations
  • A deep perceptual metric for 3D point clouds

    Maurice Quach;Aladine Chetouani;Giuseppe Valenzise;Frédéric Dufaux

    (2021)
    12 Citations
  • Drone Object Detection Using RGB/IR Fusion

    (2022)
    12 Citations

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