Автор: Rama Chellappa, Sergios Theodoridis
Издательство: Academic Press
Год: 2018
Страниц: 459
Язык: английский
Формат: pdf (true)
Размер: 36.7 MB
The last 5 years, although in a historical perspective appear to be a short period, in the context of science, engineering, and technology were very dense in terms of results and ideas. The availability of massive data, which we refer to as Big Data, together with advances in Machine Learning and affordable GPUs, has opened up new areas and opportunities. In particular, the application of deep learning networks to problems such as face/object detection, object recognition, face verification/recognition has demonstrated superior performance that was not thought possible just a few years back. We are at a time when “caffe,” the software for implementing deep networks, is probably used more than FFT! We take comfort that the basic module in caffe is convolution, the basic building block of signal and image processing.
While one cannot argue against the impressive performance of deep learning methods for a wide variety of problems and time-tested concepts such as statistical models and inference, the role of geometry and physics will continue to be relevant and may even enhance the performance and generalizability of deep learning networks. Likewise, the power of nonlinear devices, hierarchical computing structures, and optimization strategies that are central to deep learning methodologies will inspire new solutions to many problems in signal and image processing.
Academic Press Library in Signal Processing, Volume 6: Image and Video Processing and Analysis and Computer Vision is aimed at university researchers, post graduate students and R&D engineers in the industry, providing a tutorial-based, comprehensive review of key topics and technologies of research in both image and video processing and analysis and computer vision. The book provides an invaluable starting point to the area through the insight and understanding that it provides.
With this reference, readers will quickly grasp an unfamiliar area of research, understand the underlying principles of a topic, learn how a topic relates to other areas, and learn of research issues yet to be resolved.
- Presents a quick tutorial of reviews of important and emerging topics of research
- Explores core principles, technologies, algorithms and applications
- Edited and contributed by international leading figures in the field
- Includes comprehensive references to journal articles and other literature upon which to build further, more detailed knowledge
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