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ICMV 2020 : The 13th International Conference on Machine Vision

Rome, Italy
Event Date: Nov 02, 2020 - Nov 06, 2020
Submission Deadline: May 25, 2020
Notification of Acceptance: Jun 15, 2020


The emergence of Machine Vision as a ubiquitous platform for innovations has laid the foundation for the rapid growth of the Information. Side-by-side, the use of mobile and wireless devices such as PDA, laptop, and cell phones for accessing the Internet has paved the ways for related technologies to flourish through recent developments. In addition, the Machine Vision Technology is promoting better integration of the digital world with physical environment. This conference serves to foster communication among researchers and practitioners working in a wide variety of scientific areas with a common interest in improving Machine Vision related techniques. 

High quality, original papers are solicited in all areas of Machine Vision. The final program will be the result of a highly selective review process designed to include the best work of its kind in every category. The program will include invited talks as well as oral and poster presentations of refereed papers.

Call For Paper

Topics of interest for submission include, but are not limited to:

Machine Vision, Image Processing, and Pattern Analysis

  • Imaging Sensors
  • Color and Texture Analysis
  • Segmentation
  • Motion and Tracking
  • Stereo Vision
  • Biometrics Recognition
  • Image-Based Modeling
  • Calibration and Geometry
  • Illumination and Reflectance Modeling
  • Soft Computing for Machine Vision
  • Physics-Based Modeling
  • Artificial Intelligence for Machine Vision
  • Video Analysis
  • Face and Gesture Recognition
  • Action and Event Recognition
  • Similarity/Dissimilarity Metrics
  • Machine Learning
  • Performance Evaluation
  • Medical Image Analysis
  • Image and Video Retrieval
  • Structure from Motion
  • Image Registration
  • Image Enhancement
  • Clustering
  • Morphology and Blob Analysis
  • Applications of Machine Vision

Computer Vision and Image Analysis

  • Active Vision
  • Early Vision
  • Feature Extraction
  • Motion Analysis
  • Representation
  • Recognition (2D and 3D)
  • Texture and Colour
  • Scene Understanding
  • Segmentation
  • Shape from X
  • Visual Navigation

Pattern Recognition and Basic Technologies

  • Statistical Pattern Recognition
  • Structural and Syntactic Pattern Recognition
  • Neural Networks
  • Machine Learning and Data Mining
  • Artificial Intelligence and Symbolic Learning
  • Classification and Clustering
  • Feature Selection, Dimensionality Reduction, Manifold Learning
  • Kernel Methods and Support Vector Machines
  • Invariance in Recognition
  • Multiresolution Techniques
  • OCR, Document Analysis and Understanding
  • Information Retrieval

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