Könyv Sparse Representation, Modeling and Learning in Visual Recognition Hong Cheng

Sparse Representation, Modeling and Learning in Visual Recognition

Theory, Algorithms and Applications

Szerző: Hong Cheng
Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten
Küldés 8-11 napon belül
36 174 Ft
This unique text/reference presents a comprehensive review of the state of the art in sparse represe...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2016
oldal
257
EAN
9781447172512
ISBN
1447172515
Enbook ID
15175295
Súly
4161
Méretek
155 x 235 x 14

Teljes leírás

This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition; covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers; discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning; includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book.

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