Machine Learning and Visual Perception
Together with Tsinghua University Press
Systematic presentation of machine learning and visual perception.
Extensive implementation of examples to facilitate understanding.
Presentation of advanced theories, fundamentals and new research directions in easy-to-understand ways.
Aims and Scope
Machine Learning and Visual Perception provides an up-to-date overview on the topic, including the PAC model, decision tree, Bayesian learning, support vector machines, AdaBoost, compressive sensing and so on.Both classic and novel algorithms are introduced in classifier design, face recognition, deep learning, time series recognition, image classification, and object detection.
- 24.0 x 17.0 cm
- Approx. x, 190 pages
- 100 Fig. 50 Tables
- Type of Publication:
- Professional Book