13th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

Top Research Topics at Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing?

• Hyperspectral imaging (90.99%)
• Artificial intelligence (52.12%)
• Pattern recognition (40.88%)

The scientific interests tackled in Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing are Hyperspectral imaging, Artificial intelligence, Pattern recognition, Remote sensing and Pixel. The majority of Hyperspectral imaging studies are focused on the issues of Endmember. It holds forums on Artificial intelligence that merges themes from other disciplines such as Machine learning and Computer vision.

Image segmentation, Object detection, Multispectral image and Full spectral imaging are all areas of Computer vision tackled in Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing. In the conference, researchers investigate the Image segmentation study as part of research in the field of Segmentation. The work on Pattern recognition tackled in Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing brings together disciplines like Spatial analysis and Cluster analysis.

The conference facilitates discussions on Remote sensing that incorporate concepts from other fields like Spectrometer, Imaging spectrometer and Atmospheric model. Pixel research presented in Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing encompasses a variety of subjects, including Image processing and Spectral signature.

What are the most cited papers published at the conference?

• Alternating direction algorithms for constrained sparse regression: Application to hyperspectral unmixing (353 citations)
• A variable splitting augmented Lagrangian approach to linear spectral unmixing (299 citations)
• Survey of geometric and statistical unmixing algorithms for hyperspectral images (80 citations)

Research areas of the most cited articles at Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing:

The most cited articles aim to foster the development of research in Hyperspectral imaging, Artificial intelligence, Pattern recognition, Pixel and Endmember. The Hyperspectral imaging studies which were featured in the most cited papers aim to expound on the research in Remote sensing. Machine learning and Computer vision are some topics wherein Artificial intelligence research discussed in the published articles has an impact.

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 Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (based on the number of publications) are:

• Antonio Plaza (38 papers) absent at the last edition,
• Jocelyn Chanussot (35 papers) absent at the last edition,
• Qian Du (32 papers) absent at the last edition,
• Jose M. Bioucas-Dias (29 papers) absent at the last edition,
• Liangpei Zhang (27 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 Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (based on the number of publications) are:

• Chinese Academy of Sciences (56 papers) absent at the last edition,
• Mississippi State University (47 papers) absent at the last edition,
• University of Extremadura (37 papers) absent at the last edition,
• University of Toulouse (37 papers) absent at the last edition,
• Wuhan University (34 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 2021 edition, 0.00% 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 at the conference. 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 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.