20th International Conference on Content-based Multimedia Indexing

Top Research Topics at Content-Based Multimedia Indexing?

• Artificial intelligence (56.95%)
• Pattern recognition (27.49%)
• Search engine indexing (25.98%)

The conference primarily tackles Artificial intelligence, Pattern recognition, Search engine indexing, Information retrieval and Feature extraction. Issues in Artificial intelligence were discussed, taking into consideration concepts from other disciplines like Machine learning and Computer vision. The Artificial neural network studies presented in the conference fall under the field of Machine learning, but it also has connections to other fields such as Task analysis.

The event dives deep in exploring the relationship between the study of Computer vision and Robustness (computer science). Pattern recognition research featured in it incorporates concerns from various other topics such as Contextual image classification, Feature (computer vision) and Cluster analysis. It holds forums on Search engine indexing that merges themes from other disciplines such as Multimedia, Speech recognition, Index (publishing) and Natural language processing.

In addition to Multimedia research, Content-Based Multimedia Indexing aims to explore topics under World Wide Web and The Internet. The conference focuses on Information retrieval but the discussions also offer insight into other areas such as Annotation, Context (language use), Metadata and Semantics. The studies tackled, which mainly focus on Feature extraction, apply to Feature vector as well.

What are the most cited papers published at the conference?

• Experimenting with musically motivated convolutional neural networks (100 citations)
• Large-Scale Study of Chord Estimation Algorithms Based on Chroma Representation and HMM (74 citations)
• Content based 3D model retrieval: A survey (60 citations)

Research areas of the most cited articles at Content-Based Multimedia Indexing:

The conference papers are organized to reinforce research efforts on Artificial intelligence, Search engine indexing, Pattern recognition, Computer vision and Feature extraction. While Artificial intelligence is the key highlight in the published articles, thet also covered some subjects on Machine learning and Heuristic function. The conference articles explore topics in Search engine indexing which can be helpful for research in disciplines like Multimedia, Statistical classification, Service (systems architecture) and Shot (filmmaking).

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

• Artificial intelligence
• Machine learning
• Computer vision

The previous edition focused in particular on these issues:

The conference covers a variety of subjects, including Artificial intelligence, Pattern recognition, Information retrieval, Deep learning and Machine learning. The research on Artificial intelligence featured in the event combines topics in other fields like Computer vision and Natural language processing. Topics in Pattern recognition were tackled in line with various other fields like Speech recognition, Selection (genetic algorithm), Maximally stable extremal regions, Cluster analysis and Character (mathematics).

The studies on Information retrieval discussed can also contribute to research in the domains of Lifelog and Metadata. Issues in Machine learning were discussed, taking into consideration concepts from other disciplines like Contextual image classification and Selection (linguistics). The event explores research in Human brain and overlapping concepts in Search engine indexing to expand the discourse in Binary classification.

The most cited articles from the last conference are:

• Music Feature Maps with Convolutional Neural Networks for Music Genre Classification (23 citations)
• FuseMe: Classification of sMRI images by fusion of Deep CNNs in 2D+ε projections (18 citations)
• Detecting adversarial example attacks to deep neural networks (17 citations)

Papers citation over time

A key indicator for each conference 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 at Content-Based Multimedia Indexing (based on the number of publications) are:

• Georges Quénot (12 papers) published 1 paper at the last edition the same number as at the previous edition,
• Jenny Benois-Pineau (11 papers) published 2 papers at the last edition, 1 more than at the previous edition,
• Bogdan Ionescu (10 papers) absent at the last edition,
• Bernard Merialdo (9 papers) absent at the last edition,
• Patrick Lambert (7 papers) absent at the last edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing at Content-Based Multimedia Indexing (based on the number of publications) are:

• University of Bordeaux (12 papers) published 2 papers at the last edition, 1 more than at the previous edition,
• Dublin City University (10 papers) published 1 paper at the last edition the same number as at the previous edition,
• Centre national de la recherche scientifique (10 papers) absent at the last edition,
• Institut Eurécom (10 papers) absent at the last edition,
• Politehnica University of Bucharest (9 papers) absent at the last edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

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 2017 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 21.05% were posted by at least one author from the top 10 institutions publishing at the conference. Another 26.32% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 7.89% of all publications and 44.74% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference 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 conference 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 at a conference. The index includes the authors publishing at the last edition of a conference, 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.