Conference Information

IML 2017: International Conference on Internet of Things and Machine Learning

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Submission Date:
2017-05-30 Extended
Notification Date:
2017-06-20
Conference Date:
2017-10-17
Location:
Liverpool, UK
Viewed: 15506   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

42.1 / 100
Ranked #4,141 of 5,683 conferences · Top 73%

#538 of 740 in Artificial Intelligence & Machine Learning #648 of 864 in Networks & Communications

Limited evidence: this conference is not listed in CCF / ICORE / QUALIS and has no acceptance-rate data on file, so most of the score falls back to the neutral baseline.
Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%) No data - scored at the neutral baseline of 50 —
Community attention (10%)
8
Public record completeness (15%)
25

Inputs used: Researchers who opened this page in the past 24 months: 2

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 25% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-21

Call For Papers

IML 2017 (International Conference on Internet of Things and Machine Learning) is an academic conference held in Liverpool, UK on 2017-10-17. The paper submission deadline is 2017-05-30 (extended). Acceptance notifications are sent on 2017-06-20.

The International Conference on Internet of Things and Machine Learning (IML 2017) will be held from October 17 – 18, 2017 in Liverpool John Moores University, Liverpool city, United Kingdom. Through its technical program, the conference aims to provide an outstanding opportunity for both academic and industrial communities alike to address new trends and challenges, emerging technologies and progress in standards on topics relevant to today’s fast moving areas of Internet of Things and Machine Learning. This workshop will discuss new results in the field of Internet of things and machine learning. IML 2017 will offer oral, poster sessions, tutorials and, professional meetings. The program of the IML 2017 Conference intends to foster interaction so as to open the way to future cooperation between participants. All researchers and teams who develop research or recently became interested in the domains of Internet of things and machine learning are invited. Submitted papers are expected to cover state-of-the-art technologies, theoretical concepts, standards, products implementation, ongoing research projects and innovative applications of the Internet of things and machine learning technologies use. All accepted papers (regular, short, and poster) will be published by ACM – International Conference Proceedings Series (ICPS) and will be available in ACM Digital Library . ISBN: 978-1-4503-5243-7 Authors are invited to submit papers presenting original research in all areas of Internet of things and machine learning. Original unpublished manuscripts, and not currently under review in another journal or conference, are solicited in relevant areas including, but not limited to: Internet of Things: Wireless communications Understanding Networks and Networking protocols Sensors and hardware programming Smart Cities (Smart parking, Smartphone detection, Traffic congestion, Smart lighting, etc.). Smart Water (Potable water monitoring, Chemical leakage detection in rivers, River floods, etc.). Security & Emergencies Retail (Supply chain control, Intelligent shopping applications, Smart product management, etc.). Logistics (Quality of shipment conditions, Item location, etc.). Industrial Control (M2M Applications, Indoor air quality, Temperature monitoring, etc.). Smart Agriculture (Green houses) Digital Health-care / Telehealth / Telemedicine Information security Cloud computing IP multimedia subsystems Connectivity Smart Farming Smart Grids Machine Learning: Statistical Methods Data Engineering (capture, storage, search, sharing, modeling) Advanced Data Computing Visualization Pattern Recognition Data Interpretation and Analysis Data Mining Data Analytics Big Data Challenges Multimedia Learning Multi-Graph Learning Deep Learning Neural Networks Support Vector Machines Evolutionary computations Fuzzy approaches Genetic Algorithms Features Selection Artificial Intelligence Signal and Image Processing Applications of Machine Learning
Last updated by Dou Sun on

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