Auswahl der wissenschaftlichen Literatur zum Thema „Hybird Artificial intelligence“
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Zeitschriftenartikel zum Thema "Hybird Artificial intelligence"
Zhang, Nian, Yunpeng Han, Quanshen Si und Guiwu Wei. „A novel method for multi-attribute risk decision-making based on regret theory and hybird information“. Journal of Intelligent & Fuzzy Systems 39, Nr. 5 (19.11.2020): 6955–64. http://dx.doi.org/10.3233/jifs-200081.
Der volle Inhalt der QuelleDouzi, Samira, Feda A. AlShahwan, Mouad Lemoudden und Bouabid El Ouahidi. „Hybrid Email Spam Detection Model Using Artificial Intelligence“. International Journal of Machine Learning and Computing 10, Nr. 2 (Februar 2020): 316–22. http://dx.doi.org/10.18178/ijmlc.2020.10.2.937.
Der volle Inhalt der QuelleChen, Liming, Huansheng Ning, Chris D. Nugent und Zhiwen Yu. „Hybrid Human-Artificial Intelligence“. Computer 53, Nr. 8 (August 2020): 14–17. http://dx.doi.org/10.1109/mc.2020.2997573.
Der volle Inhalt der QuelleAbubakar, A. Mohammed. „Using hybrid SEM – artificial intelligence“. Personnel Review 49, Nr. 1 (19.11.2019): 67–86. http://dx.doi.org/10.1108/pr-06-2017-0180.
Der volle Inhalt der QuelleFeuerecker, Benedikt, Maurice M. Heimer, Thomas Geyer, Matthias P. Fabritius, Sijing Gu, Balthasar Schachtner, Leonie Beyer et al. „Artificial Intelligence in Oncological Hybrid Imaging“. Nuklearmedizin - NuclearMedicine 62, Nr. 05 (Oktober 2023): 296–305. http://dx.doi.org/10.1055/a-2157-6810.
Der volle Inhalt der QuelleGonzález Quirós, José Luis, und David Díaz Pardo de Vera. „Theory of mind: from artificial intelligence to hybrid intelligence“. TECHNO REVIEW. International Technology, Science and Society Review 9, Nr. 2 (18.01.2021): 103–19. http://dx.doi.org/10.37467/gka-revtechno.v9.2816.
Der volle Inhalt der QuelleJarrahi, Mohammad Hossein, Christoph Lutz und Gemma Newlands. „Artificial intelligence, human intelligence and hybrid intelligence based on mutual augmentation“. Big Data & Society 9, Nr. 2 (Juli 2022): 205395172211428. http://dx.doi.org/10.1177/20539517221142824.
Der volle Inhalt der QuelleGudova, M. Yu, E. V. Rubtsova und N. A. Simbirtseva. „Communication Trends in the Post-Literacy Era: From Human Creativity to the Creativity of Artificial Intelligence and Human-Machine Hybrids“. Izvestia Ural Federal University Journal Series 1. Issues in Education, Science and Culture 27, Nr. 2 (2021): 235–49. http://dx.doi.org/10.15826/izv1.2021.27.2.048.
Der volle Inhalt der QuelleFox, Stephen. „Beyond AI: Multi-Intelligence (MI) Combining Natural and Artificial Intelligences in Hybrid Beings and Systems“. Technologies 5, Nr. 3 (22.06.2017): 38. http://dx.doi.org/10.3390/technologies5030038.
Der volle Inhalt der QuelleLukyanova, Ekaterina D. „Artificial Intelligence: Achievements and Postponed Risks“. Sociologicheskaja nauka i social naja praktika 7, Nr. 1 (2019): 142–48. http://dx.doi.org/10.19181/snsp.2019.7.1.6275.
Der volle Inhalt der QuelleDissertationen zum Thema "Hybird Artificial intelligence"
Liu, Ziming. „Méthodes hybrides d'intelligence artificielle pour les applications de navigation autonome“. Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4004.
Der volle Inhalt der QuelleAutonomous driving is a challenging task that has a wide range of applications in the real world. The autonomous driving system can be used in different platforms, such as cars, drones, and robots. These autonomous systems will reduce a lot of human labor and improve the efficiency of the current transportation system. Some autonomous systems have been used in real scenarios, such as delivery robots, and service robots. In the real world, autonomous systems need to build environment representations and localize themselves to interact with the environment. There are different sensors can be used for these objectives. Among them, the camera sensor is the best choice between cost and reliability. Currently, visual autonomous driving has achieved significant improvement with deep learning. Deep learning methods have advantages for environment perception. However, they are not robust for visual localization where model-based methods have more reliable results. To utilize the advantages of both data-based and model-based methods, a hybrid visual odometry method is explored in this thesis. Firstly, efficient optimization methods are critical for both model-based and data-based methods which share the same optimization theory. Currently, most deep learning networks are still trained with inefficient first-order optimizers. Therefore, this thesis proposes to extend efficient model-based optimization methods to train deep learning networks. The Gaussian-Newton and the efficient second-order methods are applied for deep learning optimization. Secondly, the model-based visual odometry method is based on the prior depth information, the robust and accurate depth estimation is critical for the performance of visual odometry module. Based on traditional computer vision theory, stereo vision can compute the depth with the correct scale, which is more reliable than monocular solutions. However, the current two-stage 2D-3D stereo networks have the problems of depth annotations and disparity domain gap. Correspondingly, a pose-supervised stereo network and an adaptive stereo network are investigated. However, the performance of two-stage networks is limited by the quality of 2D features that build stereo-matching cost volume. Instead, a new one-stage 3D stereo network is proposed to learn features and stereo-matching implicitly in a single stage. Thirdly, to keep robust, the stereo network and the dense direct visual odometry module are combined to build a stereo hybrid dense direct visual odometry (HDVO). Dense direct visual odometry is more reliable than the feature-based method because it is optimized with global image information. The HDVO is optimized with the photometric minimization loss. However, this loss suffers noises from the occlusion area, homogeneous texture area, and dynamic objects. This thesis explores removing noisy loss values with binary masks. Moreover, to reduce the effects of dynamic objects, semantic segmentation results are used to improve these masks. Finally, to be generalized for a new data domain, a test-time training method for visual odometry is explored. These proposed methods have been evaluated on public autonomous driving benchmarks, and show state-of-the-art performances
Wen, Chien-Hsien. „Applying artificial intelligence hybrid techniques in wastewater treatment“. Ohio : Ohio University, 1997. http://www.ohiolink.edu/etd/view.cgi?ohiou1184357721.
Der volle Inhalt der QuelleCastorina, Giovanni. „Artificial intelligence based hybrid systems for financial forecasting“. Thesis, University of the West of England, Bristol, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365146.
Der volle Inhalt der QuelleRodic, Daniel. „A Hybrid search heuristic-exhaustive search approach for rule extraction“. Pretoria : [s.n.], 2000. http://upetd.up.ac.za/thesis/available/etd-05292006-110006/.
Der volle Inhalt der QuelleNatsheh, Emad Maher. „Hybrid power systems energy management based on artificial intelligence“. Thesis, Manchester Metropolitan University, 2013. http://e-space.mmu.ac.uk/314015/.
Der volle Inhalt der QuelleAbbas, Syed Murtuza. „Advanced Hybrid Simulation Model based on Phenomenology and Artificial Intelligence“. University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427963095.
Der volle Inhalt der QuelleChhabra, Rupanshi. „Control Power Optimization using Artificial Intelligence for Hybrid Wing Body Aircraft“. Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/56580.
Der volle Inhalt der QuelleMaster of Science
Schlobach, Klaus Stefan. „Knowledge discovery in hybrid knowledge representation systems“. Thesis, King's College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272023.
Der volle Inhalt der QuelleViademonte, da Rosa Sérgio I. (Sérgio Ivan) 1964. „A hybrid model for intelligent decision support : combining data mining and artificial neural networks“. Monash University, School of Information Management and Systems, 2004. http://arrow.monash.edu.au/hdl/1959.1/5159.
Der volle Inhalt der QuelleWakelam, Mark. „Intelligent hybrid approach for integrated design“. Thesis, University of Nottingham, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263942.
Der volle Inhalt der QuelleBücher zum Thema "Hybird Artificial intelligence"
Graña Romay, Manuel, Emilio Corchado und M. Teresa Garcia Sebastian, Hrsg. Hybrid Artificial Intelligence Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13769-3.
Der volle Inhalt der QuelleCorchado, Emilio, Manuel Graña Romay und Alexandre Manhaes Savio, Hrsg. Hybrid Artificial Intelligence Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13803-4.
Der volle Inhalt der QuelleCorchado, Emilio, Ajith Abraham und Witold Pedrycz, Hrsg. Hybrid Artificial Intelligence Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-87656-4.
Der volle Inhalt der QuelleCorchado, Emilio, Xindong Wu, Erkki Oja, Álvaro Herrero und Bruno Baruque, Hrsg. Hybrid Artificial Intelligence Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02319-4.
Der volle Inhalt der QuellePolycarpou, Marios, André C. P. L. F. de Carvalho, Jeng-Shyang Pan, Michał Woźniak, Héctor Quintian und Emilio Corchado, Hrsg. Hybrid Artificial Intelligence Systems. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07617-1.
Der volle Inhalt der QuelleSanjurjo González, Hugo, Iker Pastor López, Pablo García Bringas, Héctor Quintián und Emilio Corchado, Hrsg. Hybrid Artificial Intelligent Systems. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86271-8.
Der volle Inhalt der QuelleGarcía Bringas, Pablo, Hilde Pérez García, Francisco Javier Martínez de Pisón, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero et al., Hrsg. Hybrid Artificial Intelligent Systems. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15471-3.
Der volle Inhalt der QuelleMartínez-Álvarez, Francisco, Alicia Troncoso, Héctor Quintián und Emilio Corchado, Hrsg. Hybrid Artificial Intelligent Systems. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32034-2.
Der volle Inhalt der Quellede la Cal, Enrique Antonio, José Ramón Villar Flecha, Héctor Quintián und Emilio Corchado, Hrsg. Hybrid Artificial Intelligent Systems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61705-9.
Der volle Inhalt der QuelleCorchado, Emilio, Václav Snášel, Ajith Abraham, Michał Woźniak, Manuel Graña und Sung-Bae Cho, Hrsg. Hybrid Artificial Intelligent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28942-2.
Der volle Inhalt der QuelleBuchteile zum Thema "Hybird Artificial intelligence"
Quiza, Ramón, Omar López-Armas und J. Paulo Davim. „Artificial Intelligence Tools“. In Hybrid Modeling and Optimization of Manufacturing, 39–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28085-6_3.
Der volle Inhalt der QuelleAbraham, Ajith. „Hybrid Artificial Intelligence Systems“. In Advances in Soft Computing, XVI. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74972-1_1.
Der volle Inhalt der QuelleHerrero, Álvaro, und Emilio Corchado. „Visualisation, Artificial Intelligence, and Security“. In Mobile Hybrid Intrusion Detection, 3–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18299-0_2.
Der volle Inhalt der QuelleAzizi, Aydin. „Hybrid Artificial Intelligence Optimization Technique“. In Applications of Artificial Intelligence Techniques in Industry 4.0, 27–47. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2640-0_4.
Der volle Inhalt der QuelleWang, Guan, Weidong Wang und Dian Li. „A Hybrid Pattern Knowledge Graph-Based API Recommendation Approach“. In Artificial Intelligence, 465–76. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20503-3_37.
Der volle Inhalt der QuelleGuan, Bochen, Yanli Liu, Jinnian Zhang, William A. Sethares, Fang Liu, Qinwen Xu, Weiyi Li und Shuxue Quan. „Hybrid Domain Convolutional Neural Network for Memory Efficient Training“. In Artificial Intelligence, 227–39. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-93046-2_20.
Der volle Inhalt der QuelleSu, Yuxin, Ziling Miao und Hong Liu. „Audio-Visual Multi-person Keyword Spotting via Hybrid Fusion“. In Artificial Intelligence, 327–38. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20500-2_27.
Der volle Inhalt der QuelleNolle, Lars, Frederic Stahl und Tarek El-Mihoub. „On Explanations for Hybrid Artificial Intelligence“. In Artificial Intelligence XL, 3–15. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-47994-6_1.
Der volle Inhalt der QuelleSchuchter, Florian, Katharina Bause und Albert Albers. „Intelligent Data Analytics with Artificial Intelligence for Hybrid Engine Restart“. In Proceedings, 61–72. Wiesbaden: Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-37011-4_6.
Der volle Inhalt der QuelleAverkin, Alexey. „Hybrid Intelligent Systems Based on Fuzzy Logic and Deep Learning“. In Artificial Intelligence, 3–12. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33274-7_1.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Hybird Artificial intelligence"
Tang, Shijie, und Donglei Zhang. „Railway freight volume forecast based on Hybird Algorithms“. In 2022 3rd International Conference on Electronic Communication and Artificial Intelligence (IWECAI). IEEE, 2022. http://dx.doi.org/10.1109/iwecai55315.2022.00061.
Der volle Inhalt der QuelleFan, Wangwei, Chenghu Du und Li Liu. „CA-FashionNet: Light-Weight Hybird Model for Fashion Style Classification“. In 2023 2nd International Conference on Artificial Intelligence, Human-Computer Interaction and Robotics (AIHCIR). IEEE, 2023. http://dx.doi.org/10.1109/aihcir61661.2023.00041.
Der volle Inhalt der QuelleHung, Che-Lun, Ren-You Yan und Hsiao-Hsi Wang. „Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm“. In 2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD). IEEE, 2016. http://dx.doi.org/10.1109/snpd.2016.7515962.
Der volle Inhalt der QuelleWilliams, Jessica, Rhyse Bendell, Stephen Fiore und Florian Jentsch. „Artificial Social Intelligence in Action: Lessons Learned from Human-Agent Hybrid Search and Rescue“. In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004190.
Der volle Inhalt der QuelleVillata, Serena. „Artificial Argumentation for Humans“. In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/818.
Der volle Inhalt der QuelleHenshaw, P. D., und A. B. Todtenkopf. „Artificial Intelligence Applications Of Fast Optical Memory Access“. In Optical and Hybrid Computing, herausgegeben von Harold H. Szu. SPIE, 1986. http://dx.doi.org/10.1117/12.964029.
Der volle Inhalt der QuelleCasasent, David. „Scene Analysis Research: Optical Pattern Recognition And Artificial Intelligence“. In Optical and Hybrid Computing, herausgegeben von Harold H. Szu. SPIE, 1986. http://dx.doi.org/10.1117/12.964030.
Der volle Inhalt der QuelleKalam, Shams, Sidqi A. Abu-Khamsin, Mohammad Rasheed Khan, Asiya Abbasi, Abdul Asad und Rizwan Ahmed Khan. „Data Driven Intelligent Modeling to Estimate Adsorption of Methane Gas in Shales“. In International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-22101-ms.
Der volle Inhalt der QuelleRupprecht, Patrick, und Walter Mayrhofer. „Hybrid Intelligence - An Approach towards the Symbiosis of Artificial and Human Creativity and Interaction in the Design and Innovation Process in SMEs“. In 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1004718.
Der volle Inhalt der QuelleGrünbichler, Rudolf, und Raphael Krebs. „Using AI in SMEs to Prevent Corporate Insolvencies: Identification of Frequently Used Algorithms Based on a Literature Review“. In Seventh International Scientific-Business Conference LIMEN Leadership, Innovation, Management and Economics: Integrated Politics of Research. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2021. http://dx.doi.org/10.31410/limen.s.p.2021.27.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Hybird Artificial intelligence"
Reifman, J., T. Y. C. Wei, J. E. Vitela, C. A. Applequist und T. M. Chasensky. Prodiag--a hybrid artificial intelligence based reactor diagnostic system for process faults. Office of Scientific and Technical Information (OSTI), März 1996. http://dx.doi.org/10.2172/224950.
Der volle Inhalt der QuellePerdigão, Rui A. P. Earth System Dynamic Intelligence - ESDI. Meteoceanics, April 2021. http://dx.doi.org/10.46337/esdi.210414.
Der volle Inhalt der QuellePerdigão, Rui A. P. Earth System Dynamic Intelligence with Quantum Technologies: Seeing the “Invisible”, Predicting the “Unpredictable” in a Critically Changing World. Meteoceanics, Oktober 2021. http://dx.doi.org/10.46337/211028.
Der volle Inhalt der QuelleDavies, Will. Improving the engagement of UK armed forces overseas. Royal Institute of International Affairs, Januar 2022. http://dx.doi.org/10.55317/9781784135010.
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