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AI for emerging verticals : human-robot computing, sensing and networking /
The book comprises 17 chapters dealing with the following subjects: human-robot computing, sensing and networking; deep learning techniques; human manipulation modelling; autonomous robotic grasping; soft end-effectors; artificial intelligence; affective computing; emotion recognition; machine learn...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London, England :
Institution of Engineering and Technology,
2020.
|
| Colección: | IET computing series ;
34 |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 003 | OCoLC | ||
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| 008 | 210312t20202021enk ob 001 0 eng d | ||
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| 019 | |a 1228889765 | ||
| 020 | |a 9781785619830 |q (electronic book) | ||
| 020 | |a 1785619837 |q (electronic book) | ||
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| 035 | |a (OCoLC)1244633872 |z (OCoLC)1228889765 | ||
| 050 | 4 | |a TK6570.M6 |b .A3 2020 | |
| 082 | 0 | 4 | |a 621.38456 |2 23 |
| 049 | |a UAMI | ||
| 245 | 0 | 0 | |a AI for emerging verticals : |b human-robot computing, sensing and networking / |c edited by Muhammad Zeeshan Shakir and Naeem Ramzan. |
| 264 | 1 | |a London, England : |b Institution of Engineering and Technology, |c 2020. | |
| 264 | 4 | |c ©2021 | |
| 300 | |a 1 online resource (385 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a IET computing series ; |v 34 | |
| 504 | |a Includes bibliographical references and index (pages 355-364) | ||
| 505 | 0 | |a Deep learning techniques for modelling human manipulation and its translation for autonomous robotic grasping with soft end-effectors / Visar Arapi, Yujie Zhang, Giuseppe Averta, Cosimo Della Santina, and Matteo Bianchi -- Artificial intelligence for affective computing : an emtion recognition case study / Pablo Arnau-González, Stamos Katsigiannis, Miguel Arevalillo-Herráez, and Naeem Ramzan -- Macine learning-based affect detection within the context of human-horse interaction / Turke Althobaiti, Stamos Katsigiannis, Daune West, Hassan Rabah, and Naeem Ramzan -- Robot intelligence for real-world applications / Elefterios Triantafyllidis, Chuanyu Yang, Christopher McGreavy, Wenbin Hu, and Zhibin Li -- Visual object tracking by quadrotor AR.Drone using artificial neural networks and fuzzy logic controller / Kamel Boudjit, Cherif Larbes and Naeem Ramzan -- Predictive mobility management in cellular networks / Metin Öztürk, Paulo Valente Klaine, Sajjad Hussain, and Muhammad Ali Imran -- Artificial intelligence and data analytics in 5G and beyond-5G wireless networks / Maziar Nekovee, Dehao Wu, Yue Wang and Mehrdad Shariat -- Deep Q-network-based coverage hole detection for future wireless networks / Shahriar Abdullah Al-Ahmed, Muhammad Zeeshan Shakir, and Qasim Zeeshan Ahmed -- Artificial intelligence for localization of ultrawide bandwidth (UWB) sensor nodes / Fuhu Che, Abbas Ahmed, Qasim Zeeshan Ahmed, and Muhammad Zeeshan Shakir -- A cascaded machine learning approach for indoor classification and localization using adaptive feature selection / Mohamed I. AlHajri, Nazar T. Ali and Raed M. Shubair -- EEG-based biometrics : effects of template ageing / Pablo Arnau-González, Stamos Katsigiannis, Miguel Arevalillo-Herráez and Naeem Ramzan -- A machine-learning-driven solution to the problem of perceptual video quality metrics / Stamos Katsigiannis, Hassan Rabah, and Naeem Ramzan -- Multitask learning for autonomous driving / Murtaza Taj and Waseem Abbas -- Machine-learning-enabled ECG monitoring for early detection of hyperkalaemia / Constance Farrell and Muhammad Zeeshan Shakir -- Combining deterministic compressed sensing and machine learning for data reduction in connected health / Hassan Rabah, Slavisa Jovanovic and Naeem Ramzan -- Large-scale distributed and scalable SOM-based architecture for high-dimensional data reduction / Slavisa Jovanovic, Hassan Rabah, and Serge Weber -- Surface water pollution monitoring using the Internet of Things (IoT) and machine learning / Hamza Khurshid, Rafia Mumtaz, Noor Alvi, Faisal Shafait, Sheraz Ahmed, Muhammad Imran Malik, Andreas Dengel, and Quanita Kiran | |
| 520 | |a The book comprises 17 chapters dealing with the following subjects: human-robot computing, sensing and networking; deep learning techniques; human manipulation modelling; autonomous robotic grasping; soft end-effectors; artificial intelligence; affective computing; emotion recognition; machine learning-based affect detection; human-horse interaction; robot intelligence; visual object tracking by quadrotor; artificial neural networks; fuzzy logic controller; predictive mobility management in cellular networks; data analytics; 5G and beyond-5G wireless networks; deep Q-network-based coverage hole detection; localization of ultrawide bandwidth sensor nodes; cascaded machine learning; indoor classification and localization; adaptive feature selection; EEG-based biometrics; template ageing; perceptual video quality metrics; multitask learning for autonomous driving; machine-learning-enabled ECG monitoring; early hyperkalaemia detection; deterministic compressed sensing; data reduction; connected health; large-scale distributed and scalable SOM-based architecture; surface water pollution monitoring; and Internet of Things | ||
| 590 | |a Knovel |b ACADEMIC - General Engineering & Project Administration | ||
| 650 | 0 | |a Cell phone systems. | |
| 650 | 0 | |a Clinical medicine |x Computer programs. | |
| 650 | 0 | |a Detectors. | |
| 650 | 6 | |a Téléphonie cellulaire. | |
| 650 | 7 | |a Cell phone systems |2 fast | |
| 650 | 7 | |a Clinical medicine |x Computer programs |2 fast | |
| 650 | 7 | |a Detectors |2 fast | |
| 650 | 7 | |a 5G mobile communication. |2 inspect | |
| 650 | 7 | |a affective computing. |2 inspect | |
| 650 | 7 | |a cellular radio. |2 inspect | |
| 650 | 7 | |a learning (artificial intelligence) |2 inspect | |
| 650 | 7 | |a medical computing. |2 inspect | |
| 650 | 7 | |a robots. |2 inspect | |
| 650 | 7 | |a sensors. |2 inspect | |
| 700 | 1 | |a Shakir, Muhammad Zeeshan, |e editor. | |
| 700 | 1 | |a Ramzan, Naeem, |e editor. | |
| 776 | 0 | 8 | |i Print version: |z 1785619829 |
| 830 | 0 | |a IET computing series ; |v 34 | |
| 856 | 4 | 0 | |u https://appknovel.uam.elogim.com/kn/resources/kpAIEVHRC1/toc |z Texto completo |
| 938 | |a Askews and Holts Library Services |b ASKH |n AH37411798 | ||
| 938 | |a EBSCOhost |b EBSC |n 2698340 | ||
| 994 | |a 92 |b IZTAP | ||