IWANN 2019

Las Palmas de Gran Canaria - Spain 12-14 June

IWANN 2019 Special Session on Real Time Machine learning in Vision and Robotics (RTLVR)

IWANN 2019 Special Session on Real Time Machine learning in Vision and Robotics (RTLVR)

News:

Important dates:

  • February 15, 2019: EXTENDED DEADLINE Submission of papers
  • March 18, 2019: Papers acceptance notification
  • March 26, 2019: Submission of final papers
  • June 12-14: 2017 IWANN Conference

Sponsors:

Aims

Over the last decades there has been an increasing interest in using machine learning and in the last few years, deep learning methods, combined with other vision techniques to create autonomous systems that solve vision problems in different fields. This special session is designed to serve researchers and developers to publish original, innovative and state-of-the art algorithms and architectures for real time applications in the areas of computer vision, image processing, biometrics, virtual and augmented reality, neural networks, intelligent interfaces and biomimetic object-vision recognition.

This special session provides a platform for academics, developers, and industry-related researchers belonging to the vast communities of *Neural Networks*, *Computational Intelligence*, *Machine Learning*, *Deep Learning*, *Biometrics*, *Vision systems*, and *Robotics *, to discuss, share experience and explore traditional and new areas of the computer vision, machine and deep learning combined to solve a range of problems. The objective of the workshop is to integrate the growing international community of researchers working on the application of Machine Learning and Deep Learning Methods in Vision and Robotics to a fruitful discussion on the evolution and the benefits of this technology to the society.

After the success of the special sessions organized for IWANN 2011-2017, we are pleased to organize a new special session in the same line in conjunction with IWANN 2019.


The methods and tools applied to vision and robotics include, but are not limited to, the following:


    The methods and tools applied to vision and robotics include, but are not limited to, the following:
    • Computational Intelligence methods
    • Machine Learning methods
    • Self-adaptation and self-organisation
    • Robust computer vision algorithms (operation under variable conditions, object tracking, behaviour analysis and learning, scene segmentation,,)
    • EConvolutional Neural Networks CNN
    • Recurrent Neural Networks RNN
    • Deep Reinforcement Learning DRL
    • Hardware implementation and algorithms acceleration (GPUs, FPGA,s,.)

    The fields of application can be identified, but are not limited to, the following:

    • Video and Image Processing
    • Video tracking
    • 3D Scene reconstruction
    • 3D Tracking in Virtual Reality Environments
    • 3D Volume visualization
    • Intelligent Interfaces (User-friendly Man Machine Interface)
    • Multi-modal Human Pose Recovery and Behavior Analysis
    • Gesture and posture analysis and recognition
    • Biometric Identification and Recognition
    • Extraction of Biometric Features (fingerprint, iris, face, voice, palm, gait)
    • Surveillance systems
    • Robotic vision
    • Autonomous and Social Robots
    • Industry 4.0
    • IoT and Cyber-physical Systems
    AMLDLVR . 30 October 2019