Year: 2008
Type: editorial
Abstract: Computational Vision and Machine Learning have become synergistic fields of research.Modern machine learning techniques have improved the state of the art in computer vision and catalized re-thinking of key problems, such as recognition and tracking.In turn, vision has broadened the scope of machine learning, offering rich new challenges and highlighting the importance of representations.This special issue contains 15 papers at the intersection of vision and learning, most firmly rooted in both areas.The topics span a range of computer vision topics, from object recognition and tracking to lower-level visual tasks such as feature detection and finding contours and segments.The machine learning methods include discriminative and generative models, as well as both parametric and non-parametric representations.Since databases are proving to be crucial for progress in both machine learning and computer vision, we
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,090
OpenAlex ID: W2603796439