Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Saduf Afzal"'
Autor:
M. Arif Wani, Saduf Afzal
Publikováno v:
International Journal of Intelligent Computing and Cybernetics. 11:386-403
Purpose Many strategies have been put forward for training deep network models, however, stacking of several layers of non-linearities typically results in poor propagation of gradients and activations. The purpose of this paper is to explore the use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d5bfc5247b5723862fe7b48a45339be
https://doi.org/10.1108/ijicc-06-2017-0070
https://doi.org/10.1108/ijicc-06-2017-0070
Publikováno v:
Studies in Big Data ISBN: 9789811367939
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::949055c563bc262546129269979959e2
https://doi.org/10.1007/978-981-13-6794-6
https://doi.org/10.1007/978-981-13-6794-6
Publikováno v:
Studies in Big Data ISBN: 9789811367939
Machine learning systems, with shallow or deep architectures, have ability to learn and improve with experience. The process of machine learning begins with the raw data which is used for extracting useful information that helps in decision-making. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17f94aa31a5e2163856f6753999e5371
https://doi.org/10.1007/978-981-13-6794-6_1
https://doi.org/10.1007/978-981-13-6794-6_1
Publikováno v:
Studies in Big Data ISBN: 9789811367939
The use of supervised and unsupervised deep learning models has grown at a fast rate due to their success with learning of complex problems. High-performance computing resources, availability of huge amounts of data (labeled and unlabeled) and state-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aeef31e2adc894116ab22ecbff76c081
https://doi.org/10.1007/978-981-13-6794-6_2
https://doi.org/10.1007/978-981-13-6794-6_2
Publikováno v:
Studies in Big Data ISBN: 9789811367939
Training supervised deep learning networks involves obtaining model parameters using labeled dataset to allow the network to map an input data to a class label. The labeled dataset consists of training examples, where each example is a pair of an inp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b737267659fe98591878aef88b9bb4b
https://doi.org/10.1007/978-981-13-6794-6_3
https://doi.org/10.1007/978-981-13-6794-6_3
Publikováno v:
Studies in Big Data ISBN: 9789811367939
The recognition of handwritten digits is a well-researched problem and has many applications in real life. The important applications include automatic reading of addresses on postal envelopes, automated form processing, automated processing of handw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd2ceefc83fd181a565c1f330c40430d
https://doi.org/10.1007/978-981-13-6794-6_8
https://doi.org/10.1007/978-981-13-6794-6_8
Publikováno v:
Studies in Big Data ISBN: 9789811367939
Fingerprint recognition refers to the process of identifying or confirming the identity of an individual by comparing two fingerprints. Fingerprint recognition is one of the most researched and reliable biometric techniques for identification and aut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::253160f281f061f6b8158a57c3ccb363
https://doi.org/10.1007/978-981-13-6794-6_7
https://doi.org/10.1007/978-981-13-6794-6_7
Publikováno v:
Studies in Big Data ISBN: 9789811367939
The three main challenging problems in face recognition, i.e., recognizing a face with different expressions, recognizing a face under different lighting conditions, and recognizing a face in different poses are considered here. In recent years, Conv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d8f4325c896ad48244e31d5bc7adf1c
https://doi.org/10.1007/978-981-13-6794-6_6
https://doi.org/10.1007/978-981-13-6794-6_6
Publikováno v:
Studies in Big Data ISBN: 9789811367939
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::503cb93484b6e10bd7c3d957c0611fe0
https://doi.org/10.1007/978-981-13-6794-6_5
https://doi.org/10.1007/978-981-13-6794-6_5
This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks