Artificial Intelligence Annual. / Volume 2022 / / edited by Marco Antonio Aceves-Fernandez, Carlos M. Travieso-González.
Artificial Intelligence (AI) has attracted the attention of many researchers and users alike, and it has become increasingly crucial in our modern society. From cars, smartphones, airplanes, medical equipment, consumer applications, and industrial machines, among others, the impact of AI is notoriou...
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Superior document: | Artificial Intelligence Series ; v.12. |
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TeilnehmendeR: | |
Place / Publishing House: | London : : IntechOpen,, 2022. |
Year of Publication: | 2022 |
Edition: | First edition. |
Language: | English |
Series: | Artificial intelligence (Cambridge, Mass.)
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Physical Description: | 1 online resource (178 pages) |
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245 | 0 | 0 | |a Artificial Intelligence Annual. |n Volume 2022 / |c edited by Marco Antonio Aceves-Fernandez, Carlos M. Travieso-González. |
250 | |a First edition. | ||
264 | 1 | |a London : |b IntechOpen, |c 2022. | |
300 | |a 1 online resource (178 pages) | ||
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490 | 1 | |a Artificial Intelligence Series ; |v v.12. | |
588 | |a Description based on online resource; title from PDF title page (IntechOpen, viewed June 23, 2023). | ||
520 | |a Artificial Intelligence (AI) has attracted the attention of many researchers and users alike, and it has become increasingly crucial in our modern society. From cars, smartphones, airplanes, medical equipment, consumer applications, and industrial machines, among others, the impact of AI is notoriously changing the world we live in and making it better in many areas. However, it is equally important to remember that every progress comes with certain challenges that we as a society must address. | ||
505 | 0 | |a 1. Machine Learning Algorithm-Based Contraceptive Practice among Ever-Married Women in Bangladesh: A Hierarchical Machine Learning Classification Approach -- By Iqramul Haq, Md. Ismail Hossain, Md. Moshiur Rahman, Md. Injamul Haq Methun, Ashis Talukder, Md. Jakaria Habib and Md. Sanwar Hossain 92 -- 2. Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics -- By Michele Bennett, Ewa J. Kleczyk, Karin Hayes and Rajesh Mehta 59 -- 3. Image-Based Crop Leaf Disease Identification Using Convolution Encoder Networks -- By Indira Bharathi and Veeramani Sonai 40 -- 4. Perspective Chapter: Deep Reinforcement Learning for Co-Resident Attack Mitigation in The Cloud -- By Suxia Cui and Soamar Homsi 39 -- 5. Velocity Planning via Model-Based Reinforcement Learning: Demonstrating Results on PILCO for One-Dimensional Linear Motion with Bounded Acceleration -- By Hsuan-Cheng Liao, Han-Jung Chou and Jing-Sin Liu 27 -- 6. Self-Supervised Contrastive Representation Learning in Computer Vision -- By Yalin Bastanlar and Semih Orhan 145 -- 7. Analysis of Brain Computer Interface Using Deep and Machine Learning -- By Nabil Ajali-Hernández and Carlos M. Travieso-Gonzalez 76 -- 8. Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature -- By Kishore Kumar Kamarajugadda and Movva Pavani 56. | |
650 | 0 | |a Artificial intelligence. | |
700 | 1 | |a Travieso-González, Carlos M., |e editor. | |
700 | 1 | |a Aceves-Fernandez, Marco Antonio, |e editor. | |
776 | |z 1-83768-948-2 | ||
830 | 0 | |a Artificial intelligence (Cambridge, Mass.) | |
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