25/09/2019 15:24:04

SS01 – Special Session on Applications of Machine Learning in Computer Vision


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 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 this special session is to integrate the growing international community of researchers working on the application of Machine Learning and Deep Learning Methods in Computer Vision to a fruitful discussion on the evolution and the benefits of this technology to the society.


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,,,,) 
  • Registration methods
  • Extraction of Biometric Features (fingerprint, iris, face, voice, palm, gait)
  • Convolutional 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-camera and RGB-D camera systems 
  • Multi-modal Human Pose Recovery and Behavior Analysis
  • Gesture and posture analysis and recognition 
  • Human body reconstruction
  • Biometric Identification and Recognition 
  • Extraction of Biometric Features (fingerprint, iris, face, voice, palm, gait)
  • Surveillance systems
  • Autonomous and Social Robots
  • Robotic vision
  • Industry 4.0
  • IoT and Cyber-physical Systems
  • Data visualization

Session Chairs

  • Jose Garcia Rodriguez, University of Alicante (Spain)
  • Alexandra Psarrou, University of Westminster (UK)
  • Jorge Azorin Lopez, University of Alicante (Spain)


Prof. Jose Garcia-Rodriguez,

Dpt. Computer Technology , University of Alicante. PO Box. 99. 03080  Alicante (Spain)

email: jgarcia@dtic.ua.es  website: http://www.dtic.ua.es/~jgarcia/