IJMISSP promotes research in machine intelligence/signal processing, highlighting developments in randomised algorithms, deep learning, other learning techniques, sampling theory, transformations and data compression. Besides theory/fundamentals encountered in the main subject area, applications associated with cybersecurity, health sciences, finance and engineering are essential. Design of advanced computational intelligence systems for subtle pattern recognition/discovery, visual data understanding/retrieval, robust face recognition, streaming data processing and intelligent control/software is stressed. Submissions on technology development and real-world applications of complex machine intelligence systems are encouraged.
Topics covered include
Deep networks and deep learning algorithms
Randomised methods for development of neural networks
Machine learning for big data analytics
Ensemble, distributed, interactive and reinforcement learning
Self-organising learning for data clustering and sampling
Adaptive neuro-fuzzy inference systems and evolving intelligent systems
Granular computing and case-based reasoning
Sampling theory, transforms; data compression and coding
Cybersecurity and biometrics
Computer vision and image understanding
Real-time pattern recognition for financial data engineering
Multisensory information fusion and sensor networking systems
Data mining and knowledge discovery
Applications in medical imaging and health informatics
Modelling, control and fault diagnosis for engineering systems
Intelligent software and hardware implementation of machine intelligence systems
The objectives of IJMISSP are to establish effective communications between researchers and developers to create awareness and propel the development of complex intelligent machines. It aims to benchmark, evaluate and standardise new research ideas and methods having high impact on industrial and scientific applications.
Readership
IJMISSP provides a vehicle to help professionals, engineers, academics and researchers working in the field of machine intelligence and data science to disseminate knowledge on the state-of-the-art techniques and their evaluations, benchmarking and standardisation, mainly when applied to real-world artificial intelligence and sensory signal processing problems. The journal serves as a unique forum to integrate interdisciplinary research work involving computer scientists working in the areas of machine learning and computer vision, and electrical and electronic engineers working in sensory processing and fusion information systems. It aims to develop advanced machine learning techniques and intelligent systems with fast and robust performance for dealing with large-scale and/or complex sensory data.
Contents
IJMISSP publishes original regular papers, short papers, technical reports and case studies on the design, development, evaluation and testing of machine intelligence and sensory signal processing techniques, specifically for building robust and scalable intelligent systems to cope with large-scale data with uncertainties. Special Issues devoted to important and emerging topics in machine intelligence and signal processing will also be published.
This journal is yet to be included in any lists or directories.
Editor in Chief
Nguyen, Hien Duy, La Trobe University, Australia (h.nguyen5latrobe.edu.au)
Advisory Board
Pedrycz, Witold, University of Alberta, Canada
Associate Editors
Chamroukhi, Faicel, University of Caen, France
Jones, Andrew, University of Queensland, Australia
McLachlan, Geoffrey, University of Queensland, Australia
Nguyen, TrungTin, Inria Grenoble-Rhône-Alpes, France
A few essentials for publishing in this journal
Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
Conference papers may only be submitted if the paper has been completely re-written (more details available here) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
Briefs and research notes are not published in this journal.
All our articles go through a double-blind review process.
All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
There are no charges for publishing with Inderscience, unless you require your article to be Open Access (OA). You can find more information on OA here.
Submission process
All articles for this journal must be submitted using our online submissions system.