Auswahl der wissenschaftlichen Literatur zum Thema „Hardware for Artificial Intelligence“
Geben Sie eine Quelle nach APA, MLA, Chicago, Harvard und anderen Zitierweisen an
Inhaltsverzeichnis
Machen Sie sich mit den Listen der aktuellen Artikel, Bücher, Dissertationen, Berichten und anderer wissenschaftlichen Quellen zum Thema "Hardware for Artificial Intelligence" bekannt.
Neben jedem Werk im Literaturverzeichnis ist die Option "Zur Bibliographie hinzufügen" verfügbar. Nutzen Sie sie, wird Ihre bibliographische Angabe des gewählten Werkes nach der nötigen Zitierweise (APA, MLA, Harvard, Chicago, Vancouver usw.) automatisch gestaltet.
Sie können auch den vollen Text der wissenschaftlichen Publikation im PDF-Format herunterladen und eine Online-Annotation der Arbeit lesen, wenn die relevanten Parameter in den Metadaten verfügbar sind.
Zeitschriftenartikel zum Thema "Hardware for Artificial Intelligence"
Burkert, Andreas. „Hardware for Artificial Intelligence“. ATZ worldwide 121, Nr. 5 (26.04.2019): 8–13. http://dx.doi.org/10.1007/s38311-019-0060-0.
Der volle Inhalt der QuelleBurkert, Andreas. „Hardware for Artificial Intelligence“. ATZelectronics worldwide 14, Nr. 3 (März 2019): 8–13. http://dx.doi.org/10.1007/s38314-019-0026-4.
Der volle Inhalt der QuellePopov, I. „SoC hardware supporting artificial intelligence“. ELECTRONICS: Science, Technology, Business, Nr. 7 (2018): 116–23. http://dx.doi.org/10.22184/1992-4178.2018.178.7.116.123.
Der volle Inhalt der QuelleVerWey, John. „The Other Artificial Intelligence Hardware Problem“. Computer 55, Nr. 1 (Januar 2022): 34–42. http://dx.doi.org/10.1109/mc.2021.3113271.
Der volle Inhalt der QuellePrati, Enrico. „Quantum neuromorphic hardware for quantum artificial intelligence“. Journal of Physics: Conference Series 880 (August 2017): 012018. http://dx.doi.org/10.1088/1742-6596/880/1/012018.
Der volle Inhalt der QuelleYoon, Young Hyun, Dong Hyun Hwang, Jun Hyeok Yang und Seung Eun Lee. „Intellino: Processor for Embedded Artificial Intelligence“. Electronics 9, Nr. 7 (18.07.2020): 1169. http://dx.doi.org/10.3390/electronics9071169.
Der volle Inhalt der QuelleWang, Xiaoyin. „Artificial intelligence enhanced environmental detection system“. Applied and Computational Engineering 66, Nr. 1 (29.05.2024): 156–59. http://dx.doi.org/10.54254/2755-2721/66/20240938.
Der volle Inhalt der QuelleHNATCHUK, YELYZAVETA, YEVHENIY SIERHIEIEV und ALINA HNATCHUK. „USING ARTIFICIAL INTELLIGENCE ACCELERATORS TO TRAIN COMPUTER GAME CHARACTERS“. Computer systems and information technologies, Nr. 1 (21.08.2021): 63–70. http://dx.doi.org/10.31891/csit-2021-3-9.
Der volle Inhalt der QuelleSmith, Adam Leon. „Artificial Intelligence“. ITNOW 64, Nr. 3 (19.08.2022): 47. http://dx.doi.org/10.1093/combul/bwac093.
Der volle Inhalt der QuelleSmith, Adam Leon. „Artificial Intelligence“. ITNOW 64, Nr. 2 (12.05.2022): 65. http://dx.doi.org/10.1093/itnow/bwac065.
Der volle Inhalt der QuelleDissertationen zum Thema "Hardware for Artificial Intelligence"
Orozco, Gabriel Mario. „Artificial intelligence opportunities and an end-do-end data-driven solution for predicting hardware failures“. Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104304.
Der volle Inhalt der QuelleThesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 93-96).
Dell's target to provide quality products based on reliability, security, and manageability, has driven Dell Inc. to become one of the largest PC suppliers. The recent developments in Artificial Intelligence (AI) combined with a competitive market situation have encouraged Dell to research new opportunities. Al research and breakthroughs have risen in the last years, bringing along revolutionary technologies and companies that are disrupting all businesses. Over 30 potential concepts for Al integration at Dell Inc. were identified and evaluated to select the ones with the highest potential. The top-most concept consisted of preventing in real time the failure of hardware. This concept was investigated using a data science process. Currently, there exist a number of machine learning tools that automate the last stages of the proposed data science process to create predictive models. The utilized tools vary in functionality and evaluation standards, but also provide other services such as data and model storage and visualization options. The proposed solution utilizes the deep feature synthesis algorithm that automatically generates features from problem-specific data. These engineered features boosted predictive model accuracy by an average of 10% for the AUC and up to 250% in recall for test (out of sample) data. The proposed solution estimates an impact exceeding $407M in the first five years for Dell Inc. and all of the involved suppliers. Conservatively, the direct impact on Dell Inc. is particular to batteries under warranty and is expected to surpass $2.7M during the first five years. The conclusions show a high potential for implementation.
by Mario Orozco Gabriel.
M.B.A.
S.M. in Engineering Systems
Cheng, Chih Kang. „Hardware implementation of the complex Hopfield neural network“. CSUSB ScholarWorks, 1995. https://scholarworks.lib.csusb.edu/etd-project/1016.
Der volle Inhalt der QuelleGRIMALDI, MATTEO. „Hardware-Aware Compression Techniques for Embedded Deep Neural Networks“. Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2933756.
Der volle Inhalt der QuelleBedi, Abhishek. „A generic platform for the evolution of hardware“. Click here to access this resource online, 2009. http://hdl.handle.net/10292/651.
Der volle Inhalt der QuelleMARRONE, FRANCESCO. „Memristor-based hardware accelerators: from device modeling to AI applications“. Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2972305.
Der volle Inhalt der QuelleAl, Rawashdeh Khaled. „Toward a Hardware-assisted Online Intrusion Detection System Based on Deep Learning Algorithms for Resource-Limited Embedded Systems“. University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535464571843315.
Der volle Inhalt der QuelleKumar, Sharad Kumar. „Analysis of Machine Learning Modeling Attacks on Ring Oscillator based Hardware Security“. University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1541759752027838.
Der volle Inhalt der QuelleCONTI, DANIELE. „Neuromorphic systems based on memristive devices - From the material science perspective to bio-inspired learning hardware“. Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2711511.
Der volle Inhalt der QuelleImbulgoda, Liyangahawatte Gihan Janith Mendis. „Hardware Implementation and Applications of Deep Belief Networks“. University of Akron / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=akron1476707730643462.
Der volle Inhalt der QuelleBrink, Stephen Isaac. „Learning in silicon: a floating-gate based, biophysically inspired, neuromorphic hardware system with synaptic plasticity“. Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/50143.
Der volle Inhalt der QuelleBücher zum Thema "Hardware for Artificial Intelligence"
Mishra, Ashutosh, Jaekwang Cha, Hyunbin Park und Shiho Kim, Hrsg. Artificial Intelligence and Hardware Accelerators. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5.
Der volle Inhalt der QuelleAdamatzky, Andrew. Artificial life models in hardware. Dordrecht: Springer, 2009.
Den vollen Inhalt der Quelle findenKropf, Thomas. Introduction to Formal Hardware Verification. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999.
Den vollen Inhalt der Quelle findenBaofu, Peter. The future of post-human computing: A preface to a new theory of hardware, software and the mind. Great Abington, Cambridge, UK: Cambridge International Science Publishing, 2011.
Den vollen Inhalt der Quelle findenJovanović, Aleksandar S. Expert Systems in Structural Safety Assessment: Proceedings of an International Course October 2-4, 1989, Stuttgart, FRG. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989.
Den vollen Inhalt der Quelle findenLee, Bang W. Hardware annealing in analog VLSI neurocomputing. Boston: Kluwer Academic Publishers, 1991.
Den vollen Inhalt der Quelle findenEder, Kerstin. Hardware and Software: Verification and Testing: 7th International Haifa Verification Conference, HVC 2011, Haifa, Israel, December 6-8, 2011, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Den vollen Inhalt der Quelle findenStrous, Leon. Internet of Things. Information Processing in an Increasingly Connected World: First IFIP International Cross-Domain Conference, IFIPIoT 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Poznan, Poland, September 18-19, 2018, Revised Selected Papers. Cham: Springer Nature, 2019.
Den vollen Inhalt der Quelle findenSood, A. K. Active Perception and Robot Vision. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992.
Den vollen Inhalt der Quelle findenOman) ICC (Conference : Oman) (1st 2014 Muscat. Intelligent cloud computing: First International Conference, ICC 2014, Muscat, Oman, February 24-26, 2014, Revised selected papers. Cham: Springer, 2015.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Hardware for Artificial Intelligence"
Mishra, Ashutosh, Pamul Yadav und Shiho Kim. „Artificial Intelligence Accelerators“. In Artificial Intelligence and Hardware Accelerators, 1–52. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5_1.
Der volle Inhalt der QuelleYadav, Pamul, Ashutosh Mishra und Shiho Kim. „Neuromorphic Hardware Accelerators“. In Artificial Intelligence and Hardware Accelerators, 225–68. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5_8.
Der volle Inhalt der QuelleLippmann, Bernhard, Matthias Ludwig und Horst Gieser. „Generating Trust in Hardware through Physical Inspection“. In Embedded Artificial Intelligence, 45–59. New York: River Publishers, 2023. http://dx.doi.org/10.1201/9781003394440-5.
Der volle Inhalt der QuelleLiu, Yanli, Bochen Guan, Weiyi Li, Qinwen Xu und Shuxue Quan. „SMOF: Squeezing More Out of Filters Yields Hardware-Friendly CNN Pruning“. In Artificial Intelligence, 242–54. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20497-5_20.
Der volle Inhalt der QuelleBurns, Jeff. „The New Era of AI Hardware“. In From Artificial Intelligence to Brain Intelligence, 55–65. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003338215-4.
Der volle Inhalt der QuelleJhung, Junekyo, Ho Suk, Hyungbin Park und Shiho Kim. „Hardware Accelerators for Autonomous Vehicles“. In Artificial Intelligence and Hardware Accelerators, 269–317. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5_9.
Der volle Inhalt der QuelleKim, Jinhyuk, und Shiho Kim. „Hardware Accelerators in Embedded Systems“. In Artificial Intelligence and Hardware Accelerators, 167–81. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5_6.
Der volle Inhalt der QuelleNedjah, Nadia, und Luiza de Macedo Mourelle. „Hardware Architecture for Genetic Algorithms“. In Innovations in Applied Artificial Intelligence, 554–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11504894_76.
Der volle Inhalt der QuelleDimopoulos, Alexandros, Christos Pavlatos, Ioannis Panagopoulos und George Papakonstantinou. „An Efficient Hardware Implementation for AI Applications“. In Advances in Artificial Intelligence, 35–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11752912_6.
Der volle Inhalt der QuelleAbidi, Taha Yassine, Iyad Dayoub, Elhadj Doguech und Ihsen Alouani. „Federated Learning: Privacy, Security and Hardware Perspectives“. In Advancing Edge Artificial Intelligence, 65–86. New York: River Publishers, 2024. http://dx.doi.org/10.1201/9781003478713-3.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Hardware for Artificial Intelligence"
Dally, William J., C. Thomas Gray, John Poulton, Brucek Khailany, John Wilson und Larry Dennison. „Hardware-Enabled Artificial Intelligence“. In 2018 IEEE Symposium on VLSI Circuits. IEEE, 2018. http://dx.doi.org/10.1109/vlsic.2018.8502368.
Der volle Inhalt der Quelle„Hardware for AI“. In Emerging Topics in Artificial Intelligence (ETAI) 2021, herausgegeben von Giovanni Volpe, Joana B. Pereira, Daniel Brunner und Aydogan Ozcan. SPIE, 2021. http://dx.doi.org/10.1117/12.2606000.
Der volle Inhalt der QuelleDinu, A., und P. L. Ogrutan. „Opportunities of using artificial intelligence in hardware verification“. In 2019 IEEE 25th International Symposium for Design and Technology in Electronic Packaging (SIITME). IEEE, 2019. http://dx.doi.org/10.1109/siitme47687.2019.8990751.
Der volle Inhalt der QuelleFojtik, Rostislav. „USING HARDWARE TO SUPPORT ARTIFICIAL INTELLIGENCE IN EDUCATION“. In 18th International Technology, Education and Development Conference. IATED, 2024. http://dx.doi.org/10.21125/inted.2024.1170.
Der volle Inhalt der QuelleLim, Kah Yee, Joan Hau und Yiqi Tew. „Computer Performance Evaluation for Virtual Classroom with Artificial Intelligence Features“. In International Conference on Digital Transformation and Applications (ICDXA 2021). Tunku Abdul Rahman University College, 2021. http://dx.doi.org/10.56453/icdxa.2021.1008.
Der volle Inhalt der QuelleAdamov, Andrey Anatolievich, und Leonid Konstantinovich Eisymont. „Variants of hardware architectural solutions for artificial intelligence systems“. In 3rd International Conference “Futurity designing. Digital reality problems”. Keldysh Institute of Applied Mathematics, 2020. http://dx.doi.org/10.20948/future-2020-10.
Der volle Inhalt der QuelleRomero, A., C. Heras, M. Vega, J. Naranjo, C. Vázquez und A. Preciado. „Intelligent Open-Hardware ECG Platform for the Heart Patients Control and Diagnosis“. In Artificial Intelligence and Applications. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.674-144.
Der volle Inhalt der QuelleAttri, Anant, Sandhya Verma, Shweta Pandey, Yerrolla Chanti, Mansi Sahu und Rajat Balyan. „Exhilarating Growth in Education Through Artificial Intelligence“. In 2023 International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security (iQ-CCHESS). IEEE, 2023. http://dx.doi.org/10.1109/iq-cchess56596.2023.10391474.
Der volle Inhalt der QuelleSingh, Vinayak, Abhiranjan Dixit, Shweta Pandey, Bura Vijay Kumar, Vikrant Pachouri und Mansi Sahu. „Role of Artificial Intelligence in Criminal Investigation“. In 2023 International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security (iQ-CCHESS). IEEE, 2023. http://dx.doi.org/10.1109/iq-cchess56596.2023.10391288.
Der volle Inhalt der QuelleBurguete-Lopez, Arturo, Maksim Makarenko, Qizhou Wang, Fedor Getman und Andrea Fratalocchi. „Artificial-Intelligence Empowered Universal Metrology Optical Camera“. In CLEO: Applications and Technology. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/cleo_at.2023.jtu2a.25.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Hardware for Artificial Intelligence"
Lohn, Andrew, und Micah Musser. AI and Compute: How Much Longer Can Computing Power Drive Artificial Intelligence Progress? Center for Security and Emerging Technology, Januar 2022. http://dx.doi.org/10.51593/2021ca009.
Der volle Inhalt der QuelleMusser, Micah, Rebecca Gelles, Catherine Aiken und Andrew Lohn. “The Main Resource is the Human”. Center for Security and Emerging Technology, April 2023. http://dx.doi.org/10.51593/20210071.
Der volle Inhalt der QuelleRuvinsky, Alicia, Timothy Garton, Daniel Chausse, Rajeev Agrawal, Harland Yu und Ernest Miller. Accelerating the tactical decision process with High-Performance Computing (HPC) on the edge : motivation, framework, and use cases. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42169.
Der volle Inhalt der Quelleanis, sehab. Artificial Intelligence. ResearchHub Technologies, Inc., August 2023. http://dx.doi.org/10.55277/researchhub.agwfnyrw.
Der volle Inhalt der QuelleRoberts, Kamie. Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile. Gaithersburg, MD: National Institute of Standards and Technology, 2024. http://dx.doi.org/10.6028/nist.ai.600-1.
Der volle Inhalt der QuelleNovak, Jr, Simmons Gordon S., Porter Robert F., Kumar Bruce W., Causey Vipin und Robert L. Artificial Intelligence Project. Fort Belvoir, VA: Defense Technical Information Center, Januar 1990. http://dx.doi.org/10.21236/ada230793.
Der volle Inhalt der QuelleGuerreiro, Joao, Sergio Rebelo und Pedro Teles. Regulating Artificial Intelligence. Cambridge, MA: National Bureau of Economic Research, November 2023. http://dx.doi.org/10.3386/w31921.
Der volle Inhalt der QuelleCwik, Cynthia, Paul Grimm, Maura Grossman und Toby Walsh. Artificial Intelligence and the Courts: Artificial Intelligence Trustworthiness, and Litigation. American Association for the Advancement of Science, September 2022. http://dx.doi.org/10.1126/aaas.adf0786.
Der volle Inhalt der QuelleKaranicolas, Michael, und Mallory Knodel. Artificial Intelligence and the Courts: Artificial Intelligence and Bias - An Evaluation. American Association for the Advancement of Science, September 2022. http://dx.doi.org/10.1126/aaas.adf0788.
Der volle Inhalt der QuelleFirth-Butterfield, Kay, und Karen Silverman. Artificial Intelligence and the Courts: Artificial Intelligence - Foundational Issues and Glossary. American Association for the Advancement of Science, September 2022. http://dx.doi.org/10.1126/aaas.adf0782.
Der volle Inhalt der Quelle