Book [WS256] "Applications of Independent Component Analysis (ICA) in Pattern Recognition and Image Processing with MATLAB Simulation" [Non-designated product by our company]
【WS256】
Application of Independent Component Analysis in Pattern Recognition and Image Processing using MATLAB
Book [WS256] "Applications of Independent Component Analysis (ICA) in Pattern Recognition and Image Processing with MATLAB Simulation" [Non-designated product by our company] ■□■ Book Content ■□■ In an information-oriented society, the medium of "images" is becoming increasingly prominent. To enable computers to perform highly flexible and reliable image processing, recognition, and understanding similar to human capabilities, a new image processing method that integrates human visual information processing abilities with learning and adaptation capabilities is necessary. This book explains pattern recognition and image processing using Independent Component Analysis (ICA), which has recently gained attention as a new multidimensional signal analysis method. ICA is formulated as a problem of separating independent source signals from mixed signals that overlap and are observed under various conditions. By extracting features that occur independently from images using ICA, it is possible to represent images efficiently. Additionally, compared to traditional Fourier transforms and wavelet transforms, ICA can extract basis functions that are more suitable for images, enabling flexible and highly reliable image processing, recognition, and understanding.
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Book [WS256] "Applications of Independent Component Analysis (ICA) in Pattern Recognition and Image Processing with MATLAB Simulation" [Non-designated product by our company] ■□■ Book Content ■□■ In an information-oriented society, the media of "images" is becoming increasingly prominent. To enable computers to perform image processing, recognition, and understanding with a high degree of flexibility and reliability akin to human capabilities, a new image processing method that integrates human visual information processing abilities, learning capabilities, and adaptability is necessary. This book explains pattern recognition and image processing using Independent Component Analysis (ICA), which has recently gained attention as a new multidimensional signal analysis method. ICA is formulated as a problem of separating independent source signals from mixed signals that overlap and are observed under various conditions. On the other hand, by extracting features that occur independently from images using ICA, it is possible to represent images efficiently. Furthermore, compared to traditional Fourier transforms and wavelet transforms, ICA can extract basis functions that are more suitable for images, enabling flexible and reliable image processing, recognition, and understanding.
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■□■Application■□■ Researchers and engineers related to pattern recognition and image processing
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