2016 1st International Workshop on Sensing, Processing and Learning for Intelligent Machines, SPLINE 2016 - Proceedings

Country

United States

Universities and research institutions in United States
Media Ranking in United States

Subject Area and Category

Computer Science

Engineering
- Biomedical Engineering

Physics and Astronomy
- Instrumentation

Publisher

H-Index

Publication type

Conferences and Proceedings

ISSN

Coverage

Information

Homepage

Scope

Machines are playing an ever-increasing role in how we conduct our daily lives and business, and this trend is certainly not expected to slow down any time soon. Intelligent machines and robots penetrate into every corner of our environments, and interlink humans, physical and digital worlds. Key scientific areas include sensing, signal and data processing, and machine learning. These areas are challenging, but exciting ones, and require bringing together several central technologies in a harmonious way. It is therefore not surprising that interest in these areas has surged in recent years, and activities are now very high. This workshop aims at creating a forum for researchers and engineers from a wide variety of disciplines related to creating intelligent machines and robots. We encourage contributions that will bring state-of-the-art forward, and facilitate an active and constructive exchange of ideas on current areas of interest. The workshop will feature keynote speeches, industrial talks, invited presentations and presentations with full paper submissions, and demos. Scope We invite previously unpublished manuscripts directly targeting areas related to sensing and processing, machine learning and pattern recognition, social and service robots, big data, biometrics and de-identification. The scope includes, but is not limited to:  Sensing Technology  Audio and Speech Processing  Computer Vision and Image Processing  Signal Processing  Data Science and Big Data  Recommender Systems  Pattern Recognition and Machine Learning  Deep Learning  Artificial Intelligence  Perceptual Models  Social and Service Robots  Human-Robot Interaction  Biometrics, Soft-Biometrics and De-identification  Privacy Protection.

Join the conversation about this journal

SJR

The SJR is a size-independent prestige indicator that ranks journals by their 'average prestige per article'. It is based on the idea that 'all citations are not created equal'. SJR is a measure of scientific influence of journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from It measures the scientific influence of the average article in a journal, it expresses how central to the global scientific discussion an average article of the journal is.

Year	SJR
2017	0.281
2018	0.180
2019	0.205

Total Documents

Evolution of the number of published documents. All types of documents are considered, including citable and non citable documents.

Year	Documents
2017	0
2018	0
2019	0

Citations per document

This indicator counts the number of citations received by documents from a journal and divides them by the total number of documents published in that journal. The chart shows the evolution of the average number of times documents published in a journal in the past two, three and four years have been cited in the current year. The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric.

Cites per document	Year	Value
Cites / Doc. (4 years)	2017	1.400
Cites / Doc. (4 years)	2018	1.200
Cites / Doc. (4 years)	2019	1.200
Cites / Doc. (3 years)	2017	1.400
Cites / Doc. (3 years)	2018	1.200
Cites / Doc. (3 years)	2019	1.200
Cites / Doc. (2 years)	2017	1.400
Cites / Doc. (2 years)	2018	1.200
Cites / Doc. (2 years)	2019	0.000

Total Cites

Self-Cites

Evolution of the total number of citations and journal's self-citations received by a journal's published documents during the three previous years.
Journal Self-citation is defined as the number of citation from a journal citing article to articles published by the same journal.

Cites	Year	Value
Self Cites	2017	0
Self Cites	2018	0
Self Cites	2019	0
Total Cites	2017	35
Total Cites	2018	30
Total Cites	2019	30

External Cites per Doc

Cites per Doc

Evolution of the number of total citation per document and external citation per document (i.e. journal self-citations removed) received by a journal's published documents during the three previous years. External citations are calculated by subtracting the number of self-citations from the total number of citations received by the journal’s documents.

Cites	Year	Value
External Cites per document	2017	1.400
External Cites per document	2018	1.200
External Cites per document	2019	1.200
Cites per document	2017	1.400
Cites per document	2018	1.200
Cites per document	2019	1.200

% International Collaboration

International Collaboration accounts for the articles that have been produced by researchers from several countries. The chart shows the ratio of a journal's documents signed by researchers from more than one country; that is including more than one country address.

Year	International Collaboration
2017	0
2018	0
2019	0

Citable documents

Non-citable documents

Not every article in a journal is considered primary research and therefore "citable", this chart shows the ratio of a journal's articles including substantial research (research articles, conference papers and reviews) in three year windows vs. those documents other than research articles, reviews and conference papers.

Documents	Year	Value
Non-citable documents	2017	2
Non-citable documents	2018	2
Non-citable documents	2019	2
Citable documents	2017	23
Citable documents	2018	23
Citable documents	2019	23

Cited documents

Uncited documents

Ratio of a journal's items, grouped in three years windows, that have been cited at least once vs. those not cited during the following year.

Documents	Year	Value
Uncited documents	2017	10
Uncited documents	2018	13
Uncited documents	2019	15
Cited documents	2017	15
Cited documents	2018	12
Cited documents	2019	10

Show this widget in your own website

Just copy the code below and paste within your html code:

SCImago Graphica

Explore, visually communicate and make sense of data with our new data visualization tool.