Aims & Scope

Computer vision is concerned with defining how machines interpret the meaning of images and videos which are used widely in our daily life. Machine learning is the study of algorithms and statistical models. The integration of Computer Vision and Machined Learning is not only to enable computers to gain a high level of understanding based on videos and digital images, but also aimed at the discovery of various forms of interactions and interrelationships between systems through diverse mechanisms of machine learning.

Computer Vision and Machine Learning (CVML) focuses on the research and development of computer vision and machine learning involved in recognition, deep learning, convolutional neural networks, machine perception, remote sensing, motion analysis, robotics and a wide range of learning methods applied to a variety of learning problems from information systems and bioinformatics to computer vision, robotics, and security of engineering, mathematics, cognitive sciences, and method applications. We welcome all articles of new ideas, design alternatives, implementations and case studies related to all the aspects of computer vision and machine learning.