AI Bibliography

List Resources

Displaying 1 - 20 of 81
Parameters
Order by:

Ascending
Descending
Use all checked: 
Use all displayed: 
Use all in list: 
Agadakos, I., Agadakos, N., Polakis, J., & Amer, M. R. 2020, Chameleons' oblivion: Complex-valued deep neural networks for protocol-agnostic rf device fingerprinting. Paper presented at 2020 IEEE European Symposium on Security and Privacy (EuroS&P).  
10/4/21, 4:22 PM
Aggarwal, A., Chauhan, A., Kumar, D., Mittal, M., & Verma, S. (2020). Classification of fake news by fine-tuning deep bidirectional transformers based language model. EAI Endorsed Transactions on Scalable Information Systems Online First; EAI: Ghent, Belgium.  
10/28/20, 1:54 PM
Amir, O. (2017). Intelligent information sharing to support loosely-coupled teamwork. Unpublished PhD thesis.  
9/14/21, 4:12 PM
Amir, O., Grosz, B. J., Gajos, K. Z., & Gultchin, L. (2019). Personalized change awareness: Reducing information overload in loosely-coupled teamwork. Artificial Intelligence, 275, 204–233.  
9/14/21, 4:04 PM
Baker, S., & Xiang, W. (2023). Artificial intelligence of things for smarter healthcare: A survey of advancements, challenges, and opportunities. IEEE Communications Surveys & Tutorials.  
7/11/23, 2:30 PM
Balzarini, R., & Jambon, F. 2018, From map to sky: An empirical study on visual strategies of expert pilots. Paper presented at Eye Tracking for Spatial Research, Proceedings of the 3rd International Workshop.  
10/15/20, 4:15 PM
Bender, E. A. (1996). Mathematical methods in artificial intelligence. IEEE Computer Society Press.  
1/25/22, 10:26 AM
Borgefalk, G., & de Leon, N. 2019, The ethics of persuasive technologies in pervasive industry platforms: The need for a robust management and governance framework. Paper presented at International Conference on Persuasive Technology.  
9/21/20, 2:40 PM
Brynjolfsson, E., & Mitchell, T. (2017). What can machine learning do? workforce implications. Science, 358(6370), 1530–1534.  
11/16/22, 3:54 PM
Buisson, J., Belloir, N., & others. 2020, Digitalization in next generation c2: Research agenda from model-based engineering perspective. Paper presented at 2020 IEEE 15th International Conference of System of Systems Engineering (SoSE).  
12/6/21, 1:02 PM
Burian, B. K., Kochan, J. A., Mosier, K. L., & Fischer, U. (2017). Autonomous, context-sensitive, task management systems and decision support tools ii Contextual constraints and information sources. NASA Study.  
10/15/20, 4:52 PM
Chakraborty, A. (2020). Technology to combat cyber attacks by artificial intelligence. International Journal of Progressive Research in Science and Engineering, 1(3), 149–153.  
9/21/20, 2:29 PM
D"uring, S., Koenig, R., Khean, N., Elshani, D., Galanos, T., & Chronis, A. (2022). Machine learning, artificial intelligence, and urban assemblages. Machine Learning and the City: Applications in Architecture and Urban Design, 445–452.  
8/30/22, 10:57 AM
Davis, P. K., & Bracken, P. (2021). Artificial intelligence for wargaming and modeling. The Journal of Defense Modeling and Simulation, 15485129211073126.  
6/24/22, 11:47 AM
de Laat, M., Joksimovic, S., & Ifenthaler, D. (2020). Artificial intelligence, real-time feedback and workplace learning analytics to support in situ complex problem-solving A commentary. The International Journal of Information and Learning Technology.  
11/12/20, 1:21 PM
Demir, M., McNeese, N. J., Johnson, C., Gorman, J. C., Grimm, D., & Cooke, N. J. 2019, Effective team interaction for adaptive training and situation awareness in human-autonomy teaming. Paper presented at 2019 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA).  
9/20/21, 2:37 PM
Dimara, E., Zhang, H., Tory, M., & Franconeri, S. (2021). The unmet data visualization needs of decision makers within organizations. IEEE transactions on visualization and computer graphics.  
6/13/22, 12:38 PM
Donath, J. (2020). Ethical issues in our relationship with artificial entities. Oxford University Press Oxford, UK.  
8/21/22, 10:14 AM
Elonheimo, T. (2021). Comprehensive security approach in response to russian hybrid warfare. Strategic Studies Quarterly, 15(3).  
9/21/21, 2:27 PM
Fernando, T., Denman, S., Sridharan, S., & Fookes, C. (2018). Learning temporal strategic relationships using generative adversarial imitation learning. arXiv preprint arXiv:1805.04969.  
1/4/22, 5:40 AM
1 - 20  |  21 - 40  |  41 - 60  |  61 - 80  |  81 - 81
WIKINDX 6.7.0 | Total resources: 1621 | Username: -- | Bibliography: WIKINDX Master Bibliography | Style: American Psychological Association (APA)