Description

The emerging modern mobile robotic systems and intelligent information systems are becoming increasingly ubiquitous and distributed, where it is intended to operate in a highly dynamic and continuously fluctuating societal and economic environments. Moreover, the introduction of autonomous systems has revolutionized wide range of applications like agriculture, healthcare, education, military, industries, and so on. The incorporation of machine learning algorithms will make these autonomous system to become more robust and efficient under diverse societal and environment conditions. This International Conference on Machine Learning and Autonomous Systems [ICMLAS 2021] hosted and organized by Rohini College of Engineering and Technology, Tamilnadu India on 24-25 September 2021 will be an interdisciplinary platform for the researchers to contribute their research works that address the state-of-the-art technologies, development, and methodologies for the futuristic intelligent autonomous system developments and applications.

Call For Papers

Machine Learning

  • Computational learning theory and applications
  • Knowledge discovery and acquisition
  • Cognitive modelling and data analysis techniques
  • Hybrid learning algorithms
  • Data and knowledge representation models
  • Deep learning approaches
  • Mutli-agent systems and learning models
  • Support vector machine
  • Intelligent information retrieval techniques
  • Reinforcement learning approaches
  • Fuzzy-based learning approaches
  • Machine learning for web and social network mining
  • Intelligent feature extraction techniques
  • Mobile data mining and analysis
  • Parallel and distributed learning algorithms
  • Statistical and analytical learning
  • Scalability and reliability of learning algorithms

Autonomous Systems

  • Theoretical foundations for autonomous systems
  • Complex and adaptive autonomous systems
  • Autonomous computing platforms and applications
  • Cognition-inspired autonomous systems
  • Multi-autonomous systems and applications
  • Autonomous algorithms and models
  • Adaptive and autonomous robots
  • Real-time autonomous systems
  • Smart and distributed autonomous systems
  • Autonomous software and operating systems
  • Autonomous sensors and embedded systems
  • Optimization and control algorithms for autonomous systems
  • Novel control models and structures for autonomous systems
  • Learning, adaptation, and estimation methods for autonomous systems
  • Innovative applications of autonomous systems: healthcare, agriculture, industries, military, smart cities, smart home, education, and so on.