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[null,"1.","Record Nr.",null,"UNINA990001854510403321"]
[null,null,"Autore",null,"Gagliardo, Giovanni Battista"]
[null,null,"Titolo",null,"Dell'agricoltura ercolanese memoria di Gio. Battista Gagliardo ... letta nel suddetto R. Istituto nell'adunanza del di 12 aprile 1810. E stampata con decreto del medesimo"]
[null,null,"Pubbl/distr/stampa",null,"Napoli : nella tipografia di Angelo Trani, 1810"]
[null,null,"Descrizione fisica",null,"23, [1] p. ; 8°"]
[null,null,"Disciplina",null,"630"]
[null,null,"Locazione",null,"FAGBC"]
[null,null,"Collocazione",null,"60 MISC. B 93/4"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910741167703321"]
[null,null,"Autore",null,"Zhao Haitao"]
[null,null,"Titolo",null,"Feature Learning and Understanding : Algorithms and Applications / / by Haitao Zhao, Zhihui Lai, Henry Leung, Xianyi Zhang"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020"]
[null,null,"ISBN",null,"3-030-40794-2"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XIV, 291 p. 126 illus., 109 illus. in color.)"]
[null,null,"Collana",null,"Information Fusion and Data Science, , 2510-1528"]
[null,null,"Disciplina",null,"006.31"]
[null,null,"Soggetti",null,"Sociophysics"]
[{"$nulls":4},"Econophysics"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Computational intelligence"]
[{"$nulls":4},"Pattern perception"]
[{"$nulls":4},"Signal processing"]
[{"$nulls":4},"Image processing"]
[{"$nulls":4},"Speech processing systems"]
[{"$nulls":4},"Optical data processing"]
[{"$nulls":4},"Data-driven Science, Modeling and Theory Building"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Pattern Recognition"]
[{"$nulls":4},"Signal, Image and Speech Processing"]
[{"$nulls":4},"Image Processing and Computer Vision"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Chapter1. A Gentle Introduction to Feature Learning -- Chapter2. Latent Semantic Feature Learning -- Chapter3. Principal Component Analysis -- Chapter4. Local-Geometrical-Structure-based Feature Learning -- Chapter5. Linear Discriminant Analysis -- Chapter6. Kernel-based nonlinear feature learning -- Chapter7. Sparse feature learning -- Chapter8. Low rank feature learning -- Chapter9. Tensor-based Feature Learning -- Chapter10. Neural-network-based Feature Learning: Autoencoder -- Chapter11. Neural-network-based Feature Learning: Convolutional Neural Network -- Chapter12. Neural-network-based Feature Learning: Recurrent Neural Network."]
[null,null,null,"Sommario/riassunto","This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. Good features give good models and it is usually not classifiers but features that determine the effectiveness of a model. In this book, readers can find not only traditional feature learning methods, such as principal component analysis, linear discriminant analysis, and geometrical-structure-based methods, but also advanced feature learning methods, such as sparse learning, low-rank decomposition, tensor-based feature extraction, and deep-learning-based feature learning. Each feature learning method has its own dedicated chapter that explains how it is theoretically derived and shows how it is implemented for real-world applications. Detailed illustrated figures are included for better understanding. This book can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence."]