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Deep learning
edited by Venu Govindaraju (University at Buffalo, Buffalo, NY, United States), Arni S.R. Srinivasa Rao (Medical College of Georgia, Augusta, Georgia, United States), C.R. Rao (AIMSCS, University of Hyderabad Campus, Hyderabad, India).
- Edition
- -
- ISBN/ISSN
- 9780443184307
- Collation
- xv, 252 pages : illustrations (some color) ; 24 cm.
- Series Title
- Handbook of statistics
- Call Number
- -
Urinary stents : current state and future perspectives
This open access book provides a concise overview of a range of aspects related to urinary stents. Sections within the work cover clinical and recent technological advancements in the field. Chapters feature detailed coverage of the different surgical, pharmacological and palliative treatments currently available. Insight is also given on current limitations of urinary stents and how these can …
- Edition
- -
- ISBN/ISSN
- 9783031044847
- Collation
- XV, 457 p
- Series Title
- -
- Call Number
- 006.31 CUR u
XxAI - beyond explainable AI : International Workshop, Held in Conjunction wi…
Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and …
- Edition
- -
- ISBN/ISSN
- 9783031040832
- Collation
- x; 397 PG; ill.
- Series Title
- Lecture Notes in Computer Science
- Call Number
- 006.3 XXA x
Metalearning : applications to automated machine learning and data mining
This open access book offers a comprehensive and thorough introduction to almost all aspects of metalearning and automated machine learning (AutoML), covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ensembles and workflows, and also how this knowledge can be used to select, combine, compose, adapt and configure both algorithms and models to yield …
- Edition
- Second Edition
- ISBN/ISSN
- 9783030670245
- Collation
- xii, 346p. : ill,
- Series Title
- -
- Call Number
- 006.31 MET m
Machine learning for cyber physical systems
This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze…
- Edition
- -
- ISBN/ISSN
- 9783662584859
- Collation
- VII, 136 p.
- Series Title
- Technologien für die intelligente Automation
- Call Number
- 006.31 MAN m
On the path to AI : law's prophecies and the conceptual foundations of the ma…
This open access book explores machine learning and its impact on how we make sense of the world. It does so by bringing together two ‘revolutions’ in a surprising analogy: the revolution of machine learning, which has placed computing on the path to artificial intelligence, and the revolution in thinking about the law that was spurred by Oliver Wendell Holmes Jr in the last two decades of …
- Edition
- -
- ISBN/ISSN
- 9783030435820
- Collation
- xxii, 147p. : ill.
- Series Title
- -
- Call Number
- 006.3 GRA o
Learning to understand remote sensing images
With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the rem…
- Edition
- -
- ISBN/ISSN
- 9783038976851
- Collation
- IX, 416 p.
- Series Title
- -
- Call Number
- 005.133 WAN l
Efficient learning machines : theories, concepts, and applications for engine…
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networ…
- Edition
- -
- ISBN/ISSN
- 9781430259909
- Collation
- xix, 268p. : ill.
- Series Title
- -
- Call Number
- 006.31 AWA e
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