Relevant bibliographies by topics / Cognitive Computing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Cognitive Computing'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Cognitive Computing"

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M, Babul Reddy, and Prof Rahul Pawar. "Cognitive Computing in Cloud Environments." International Journal of Research Publication and Reviews 5, no. 3 (2024): 569–73. http://dx.doi.org/10.55248/gengpi.5.0324.0621.

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Wang, Yingxu, Victor Raskin, Julia Rayz, et al. "Cognitive Computing." International Journal of Software Science and Computational Intelligence 10, no. 1 (2018): 1–14. http://dx.doi.org/10.4018/ijssci.2018010101.

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Cognitive Computing (CC) is a contemporary field of studies on intelligent computing methodologies and brain-inspired mechanisms of cognitive systems, cognitive machine learning and cognitive robotics. The IEEE conference ICCI*CC'17 on Cognitive Informatics and Cognitive Computing was focused on the theme of neurocomputation, cognitive machine learning and brain-inspired systems. This article reports the plenary panel (Part II) in IEEE ICCI*CC'17 at Oxford University. The summary is contributed by distinguished panelists who are part of the world's renowned scholars in the transdisciplinary fi
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Modha, Dharmendra S., Rajagopal Ananthanarayanan, Steven K. Esser, Anthony Ndirango, Anthony J. Sherbondy, and Raghavendra Singh. "Cognitive computing." Communications of the ACM 54, no. 8 (2011): 62–71. http://dx.doi.org/10.1145/1978542.1978559.

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Pagel, Peter, Edy Portmann, and Karin Vey. "Cognitive Computing." Informatik-Spektrum 41, no. 1 (2018): 1–4. http://dx.doi.org/10.1007/s00287-018-1091-4.

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D’Onofrio, Sara, Edy Portmann, Michel Franzelli, and Christoph Bürki. "Cognitive Computing." Informatik-Spektrum 41, no. 2 (2018): 113–22. http://dx.doi.org/10.1007/s00287-018-1095-0.

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Sridharan, Mohan, Gerald Tesauro, and James Hendler. "Cognitive Computing." IEEE Intelligent Systems 32, no. 4 (2017): 3–4. http://dx.doi.org/10.1109/mis.2017.3121554.

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Demirkan, Haluk, Seth Earley, and Robert R. Harmon. "Cognitive Computing." IT Professional 19, no. 4 (2017): 16–20. http://dx.doi.org/10.1109/mitp.2017.3051332.

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Shama, Firdous. "Cognitive Computing." Research and Applications: Emerging Technologies 3, no. 1 (2021): 1–8. https://doi.org/10.5281/zenodo.4730213.

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<em>Cognitive computing is the new wave of Artificial Intelligence (AI), relying on traditional techniques based on expert systems and also exploiting statistics and mathematical models. In particular, cognitive computing systems can be regarded as a &ldquo;more human&rdquo; artificial intelligence. In fact, they mimic human reasoning methodologies, showing special capabilities in dealing with uncertainties and in solving problems that typically entail computation consuming processes. Moreover, they can evolve, exploiting the accumulated experience to learn from the past, both from errors and
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Wang, Yingxu, George Baciu, Yiyu Yao, et al. "Perspectives on Cognitive Informatics and Cognitive Computing." International Journal of Cognitive Informatics and Natural Intelligence 4, no. 1 (2010): 1–29. http://dx.doi.org/10.4018/jcini.2010010101.

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Cognitive informatics is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. Cognitive computing is an emerging paradigm of intelligent computing methodologies and systems based on cognitive informatics that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This article presents a set
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Farrell, Robert G., Jonathan Lenchner, Jeffrey O. Kephjart, et al. "Symbiotic Cognitive Computing." AI Magazine 37, no. 3 (2016): 81–93. http://dx.doi.org/10.1609/aimag.v37i3.2628.

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IBM Research is engaged in a research program in symbiotic cognitive computing to investigate how to embed cognitive computing in physical spaces. This article proposes 5 key principles of symbiotic cognitive computing. We describe how these principles are applied in a particular symbiotic cognitive computing environment and in an illustrative application.
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Dissertations / Theses on the topic "Cognitive Computing"

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Püschel, Georg, and Frank J. Furrer. "Cognitive Computing: Collected Papers." Technische Universität Dresden, 2015. https://tud.qucosa.de/id/qucosa%3A28990.

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Cognitive Computing' has initiated a new era in computer science. Cognitive computers are not rigidly programmed computers anymore, but they learn from their interactions with humans, from the environment and from information. They are thus able to perform amazing tasks on their own, such as driving a car in dense traffic, piloting an aircraft in difficult conditions, taking complex financial investment decisions, analysing medical-imaging data, and assist medical doctors in diagnosis and therapy. Cognitive computing is based on artificial intelligence, image processing, pattern recognition, r
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Peniak, Martin. "GPU computing for cognitive robotics." Thesis, University of Plymouth, 2014. http://hdl.handle.net/10026.1/3052.

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This thesis presents the first investigation of the impact of GPU computing on cognitive robotics by providing a series of novel experiments in the area of action and language acquisition in humanoid robots and computer vision. Cognitive robotics is concerned with endowing robots with high-level cognitive capabilities to enable the achievement of complex goals in complex environments. Reaching the ultimate goal of developing cognitive robots will require tremendous amounts of computational power, which was until recently provided mostly by standard CPU processors. CPU cores are optimised for s
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Riera, Villanueva Marc. "Low-power accelerators for cognitive computing." Doctoral thesis, Universitat Politècnica de Catalunya, 2020. http://hdl.handle.net/10803/669828.

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Deep Neural Networks (DNNs) have achieved tremendous success for cognitive applications, and are especially efficient in classification and decision making problems such as speech recognition or machine translation. Mobile and embedded devices increasingly rely on DNNs to understand the world. Smartphones, smartwatches and cars perform discriminative tasks, such as face or object recognition, on a daily basis. Despite the increasing popularity of DNNs, running them on mobile and embedded systems comes with several main challenges: delivering high accuracy and performance with a small memory an
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Kazilas, Panagiotis. "Augmenting MPI Programming Process with Cognitive Computing." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-88913.

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Cognitive Computing is a new and quickly advancing technology. In thelast decade Cognitive Computing has been used to assist researchers in theirendeavors in many different scientific fields such as Health &amp; medicine,Education, Marketing, Psychology and Financial Services. On the otherhand, Parallel programming is a more complex concept than sequentialprogramming. The additional complexity of Parallel Programming isintroduced by its nature that requires implementations of more complexalgorithms and it introduces additional concepts to the developers, namelythe communication between the pro
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McArthur, Robert James. "Computing with meaning by operationalising socio-cognitive semantics." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16571/1/Robert_McArthur_Thesis.pdf.

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This thesis is motivated by the desire to provide technological solutions to enhance human awareness in information processing tasks. The need is pressing. Paradoxically, as information piles up people become less and less aware due to perceived scarce cognitive resources. As a consequence, specialisations become ever more specialised, projects and individuals in organisations become ever more insular. Technology can enhance awareness by informing the individual about what is happening outside their speciality. Systems which can assist people in these ways need to make sense of human com
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McArthur, Robert James. "Computing with meaning by operationalising socio-cognitive semantics." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16571/.

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This thesis is motivated by the desire to provide technological solutions to enhance human awareness in information processing tasks. The need is pressing. Paradoxically, as information piles up people become less and less aware due to perceived scarce cognitive resources. As a consequence, specialisations become ever more specialised, projects and individuals in organisations become ever more insular. Technology can enhance awareness by informing the individual about what is happening outside their speciality. Systems which can assist people in these ways need to make sense of human com
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Marojevic, Vuk. "Computing resource management in software-defined and cognitive radios." Doctoral thesis, Universitat Politècnica de Catalunya, 2010. http://hdl.handle.net/10803/78033.

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Our research aims at contributing to the evolution of modern wireless communications and to the development of software-defined radio (SDR) and cognitive radio, in particular. It promotes a general resource management framework that facilitates the integration of computing and radio resource management. This dissertation discusses the need for computing resource management in software-defined and cognitive radios and introduces an SDR computing resource management framework with cognitive capabilities. The hard real-time computing requirements of software-defined digital signal processing chai
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Zhang, Chi. "Apply on Instance of IBM Watson Cognitive Computing System." Thesis, KTH, Industriell ekologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-203999.

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Smart Cities concern a variety of domains such as information, data, energy, transport, health, etc. The ‘Information Age’, which shifts from the Industrial Revolution to information computerisation, accesses to large volumes of data explored by sophisticated computer based analytics. ICT solutions interconnect businesses and customers through the cloud while driving the global economy and development of Smart Cities. This MSc thesis aims to investigate connections between Smart Cities and cloud-based Cognitive Computing, then demonstrate with instances how the combination of Watson cognitive
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Goettel, Colby. "A Cognitive Approach to Predicting Academic Success in Computing." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/6732.

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This research examines the possible correlations between a computing student's learning preference and their academic success, as well as their overall satisfaction with their major. CS and IT seniors at BYU were surveyed about their learning preferences and satisfaction with their major. The research found that IT students who are more reflective in their learning preference tend to have higher grades in their major. Additionally, it found that student age and their parents' education level were significant players in their academic success. However, there were no correlations found between m
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Cattinelli, I. "INVESTIGATIONS ON COGNITIVE COMPUTATION AND COMPUTATIONAL COGNITION." Doctoral thesis, Università degli Studi di Milano, 2011. http://hdl.handle.net/2434/155482.

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This Thesis describes our work at the boundary between Computer Science and Cognitive (Neuro)Science. In particular, (1) we have worked on methodological improvements to clustering-based meta-analysis of neuroimaging data, which is a technique that allows to collectively assess, in a quantitative way, activation peaks from several functional imaging studies, in order to extract the most robust results in the cognitive domain of interest. Hierarchical clustering is often used in this context, yet it is prone to the problem of non-uniqueness of the solution: a different permutation of the same i
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Books on the topic "Cognitive Computing"

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Haun, Matthias. Cognitive Computing. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44075-9.

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Portmann, Edy, and Sara D'Onofrio, eds. Cognitive Computing. Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-27941-7.

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Mallick, Pradeep Kumar, Prasant Kumar Pattnaik, Amiya Ranjan Panda, and Valentina Emilia Balas, eds. Cognitive Computing in Human Cognition. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48118-6.

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Masood, Adnan, and Adnan Hashmi. Cognitive Computing Recipes. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4106-6.

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Xu, Ruifeng, Cheng Cai, and Liang-Jie Zhang, eds. Cognitive Computing – ICCC 2021. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96419-1.

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Xiao, Jing, Zhi-Hong Mao, Toyotaro Suzumura, and Liang-Jie Zhang, eds. Cognitive Computing – ICCC 2018. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94307-7.

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Xu, Ruifeng, Jianzong Wang, and Liang-Jie Zhang, eds. Cognitive Computing – ICCC 2019. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23407-2.

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Yang, Yujiu, Lei Yu, and Liang-Jie Zhang, eds. Cognitive Computing – ICCC 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59585-2.

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Yang, Yujiu, Xiaohui Wang, and Liang-Jie Zhang, eds. Cognitive Computing – ICCC 2022. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-23585-6.

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Pan, Xiuqin, Ting Jin, and Liang-Jie Zhang, eds. Cognitive Computing – ICCC 2023. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-51671-9.

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Book chapters on the topic "Cognitive Computing"

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Kumar, Rohit. "Cognitive Computing." In Machine Learning and Cognition in Enterprises. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-3069-5_7.

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El Namaki, M. S. S. "Cognitive Computing." In Neo Strategic Management. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37208-7_20.

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Velankar, Makarand R., Parikshit N. Mahalle, and Gitanjali R. Shinde. "Cognitive Computing." In Innovations in Sustainable Technologies and Computing. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0452-1_5.

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Haun, Matthias. "Prolog als Motivation." In Cognitive Computing. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44075-9_1.

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Haun, Matthias. "Grundlagen." In Cognitive Computing. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44075-9_2.

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Haun, Matthias. "Vorgehensmodell: Brainware Engineering." In Cognitive Computing. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44075-9_3.

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Haun, Matthias. "Konzeptionalisierung: Naturanaloge Modelle." In Cognitive Computing. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44075-9_4.

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Haun, Matthias. "Implementierung: Kognitive Techniken." In Cognitive Computing. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44075-9_5.

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Haun, Matthias. "Validierung: Kognitive Anwendungen." In Cognitive Computing. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44075-9_6.

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Haun, Matthias. "Epilog als Ausblick und Motivation." In Cognitive Computing. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44075-9_7.

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Conference papers on the topic "Cognitive Computing"

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Shaik, Iliyas Ali, Ansar Hussain Shaik, P. Athahar, and B. Rasheeda Begum. "Cognitive Computing in English Language Classrooms." In 2024 IEEE 6th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA). IEEE, 2024. https://doi.org/10.1109/icccmla63077.2024.10871285.

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M.V.N, Nagalakshmi, Y. V. N. Sai Sri Charan, Ahmed Read Al-Tameemi, Hawraa Ali Sabah, Ahmed KatebJumaah Al-Nussairi, and Reshma Rajendra Sawant. "Cognitive Computing in Customer Service Automation." In 2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63760.2024.10910809.

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Sikarwar, Shailendra Singh, Rachna Rathore, Shivam Upadhyay, Ankita Lakra, Soumya M, and Sumit Miglani. "Cognitive Computing with Deep Neural Networks." In 2024 4th International Conference on Advancement in Electronics & Communication Engineering (AECE). IEEE, 2024. https://doi.org/10.1109/aece62803.2024.10911585.

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G M, Harshitha, Pawan Madanan, Shital Agrawal, Muralidhar L B, Sundarapandiyan Natarajan, and Venkata Purnakumari Pechetty. "Cognitive Computing for Marketing Decision Support." In 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). IEEE, 2024. https://doi.org/10.1109/ic3tes62412.2024.10877640.

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Manoharan, Geetha, Pravin D. Sawant, J. Vanitha, Melanie Lourens, R. Anusuya, and Indira Bhati. "Cognitive Computing for HR Decision-Making." In 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). IEEE, 2024. https://doi.org/10.1109/ic3tes62412.2024.10877480.

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Ciftcioglu, Ozer, and Michael S. Bittermann. "Generic cognitive computing for cognition." In 2015 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2015. http://dx.doi.org/10.1109/cec.2015.7256942.

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Sheu, Phillip. "Semantic computing and cognitive computing/informatics." In 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2017. http://dx.doi.org/10.1109/icci-cc.2017.8109801.

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Farhat, Nabil H., and Haroon Babri. "Cognitive neural networks: collective computing with diverse attractors." In OSA Annual Meeting. Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.mii1.

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Nearly all neural networks for pattern recognition being dealt with today are associative classifier or identifier networks that are not cognitive. To be cognitive a net must be able to distinguish, on its own, between familiar and unfamiliar or novel sensory signals present at its input, and this can not be done by associative classifiers. It will be argued and shown that, to be truly cognitive, a network must be nonlinear and dynamic and able to manifest bifurcation. This means it should be able to carry out phase space computations with more than one type of attractor and to switch between
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Wang, Guoyin, and Qinghua Zhang. "Granular Computing based cognitive computing." In 2009 8th IEEE International Conference on Cognitive Informatics (ICCI). IEEE, 2009. http://dx.doi.org/10.1109/coginf.2009.5250774.

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Nahamoo, David. "Cognitive computing journey." In the first workshop. ACM Press, 2014. http://dx.doi.org/10.1145/2567634.2567646.

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Reports on the topic "Cognitive Computing"

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Debenedictis, Erik, Fredrick Rothganger, James Bradley Aimone, et al. Cognitive Computing for Security. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1234812.

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Karlin, I., and A. Bertsch. Livermore Computing Integrates Advanced Cognitive Simulation Resource. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1643766.

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Pasupuleti, Murali Krishna. Quantum Cognition: Modeling Decision-Making with Quantum Theory. National Education Services, 2025. https://doi.org/10.62311/nesx/rrvi225.

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Abstract Quantum cognition applies quantum probability theory and mathematical principles from quantum mechanics to model human decision-making, reasoning, and cognitive processes beyond the constraints of classical probability models. Traditional decision theories, such as expected utility theory and Bayesian inference, struggle to explain context-dependent reasoning, preference reversals, order effects, and cognitive biases observed in human behavior. By incorporating superposition, interference, and entanglement, quantum cognitive models offer a probabilistic framework that better accounts
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Pasupuleti, Murali Krishna. Augmented Human Intelligence: Converging Generative AI, Quantum Computing, and XR for Enhanced Human-Machine Synergy. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv525.

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Abstract: Augmented Human Intelligence (AHI) represents a paradigm shift in human-AI collaboration, leveraging Generative AI, Quantum Computing, and Extended Reality (XR) to enhance cognitive capabilities, decision-making, and immersive interactions. Generative AI enables real-time knowledge augmentation, automated creativity, and adaptive learning, while Quantum Computing accelerates AI optimization, pattern recognition, and complex problem-solving. XR technologies provide intuitive, immersive environments for AI-driven collaboration, bridging the gap between digital and physical experiences.
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Pasupuleti, Murali Krishna. Neural Computation and Learning Theory: Expressivity, Dynamics, and Biologically Inspired AI. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv425.

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Abstract: Neural computation and learning theory provide the foundational principles for understanding how artificial and biological neural networks encode, process, and learn from data. This research explores expressivity, computational dynamics, and biologically inspired AI, focusing on theoretical expressivity limits, infinite-width neural networks, recurrent and spiking neural networks, attractor models, and synaptic plasticity. The study investigates mathematical models of function approximation, kernel methods, dynamical systems, and stability properties to assess the generalization capa
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Jefferson, Brian. Reviewing Information Technology, Surveillance, and Race in the US. Just Tech, Social Science Research Council, 2022. http://dx.doi.org/10.35650/jt.3033.d.2022.

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The past decade has been marked by a growing awareness of the potential harms of personal computing. This recent development was spurred by a surge of news reports, films, and studies on the unforeseen side effects of constantly using networked devices. As a result, the public has become increasingly aware of the cognitive, ideological, and psychological effects associated with the constant use of personal computing devices. Alongside these revelations, a growing chorus of activists, journalists, organizers, and scholars have turned attention to surveillance technology-related matters of a dif
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Fang, Mei Lan, Judith Sixsmith, Jacqui Morris, et al. AgeTech, Ethics and Equity: Towards a Cultural Shift in AgeTech Ethical Responsibility. University of Dundee, 2023. http://dx.doi.org/10.20933/100001292.

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Population ageing is a global phenomenon which presents major challenges for the provision of care at home and in the community (ONS, 2018). Challenges include the human and economic costs associated with increasing numbers of older people with poor physical and mental health, loneliness, and isolation challenges (Mihalopoulos et al., 2020). The global ageing population has led to a growth in the development of technology designed to improve the health, well-being, independence, and quality of life of older people across various settings (Fang, 2022). This emerging field, known as “AgeTech,” r
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