Letteratura scientifica selezionata sul tema "Artifical intelligence"
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Articoli di riviste sul tema "Artifical intelligence":
Motomura, Yoichi. "Future Artificial Intelligence Technology". Proceedings of the Symposium on Evaluation and Diagnosis 2016.15 (2016): 0spec. http://dx.doi.org/10.1299/jsmesed.2016.15.0spec.
Torgautova, B. A., e K. M. Osmonaliyev. "On the issue of criminal liability for acts committed with the use of artificial intelligence for criminal purposes". Eurasian Scientific Journal of Law, n. 1 (6) (19 aprile 2024): 41–47. http://dx.doi.org/10.46914/2959-4197-2024-1-1-41-47.
Belkova, Elena. "Works Created by Artificial Intelligence Technologies". Academic Law Journal 23, n. 2 (12 luglio 2022): 153–60. http://dx.doi.org/10.17150/1819-0928.2022.23(2).153-160.
Larrondo, Manuel Ernesto, e Nicolas Mario Grandi. "Artificial intelligence, algorithms and freedom of expression". Metaverse 2, n. 2 (1 settembre 2021): 11. http://dx.doi.org/10.54517/m.v2i2.1790.
Larrondo, Manuel Ernesto, e Nicolas Mario Grandi. "Artificial intelligence, algorithms and freedom of expression". Metaverse 2, n. 2 (1 settembre 2021): 11. http://dx.doi.org/10.54517/met.v2i2.1790.
Golenkov, V. V., N. A. Gulyakina, V. P. Ivashenko e D. V. Shunkevich. "Intelligent Computer Systems of New Generation and Complex Technology of Their Development, Application and Modernization". Doklady BGUIR 22, n. 2 (16 aprile 2024): 70–79. http://dx.doi.org/10.35596/1729-7648-2024-22-2-70-79.
Xu, Yina. "Editorial". Metaverse 2, n. 2 (30 dicembre 2021): 1. http://dx.doi.org/10.54517/m.v2i2.1867.
Xu, Yina. "Editorial". Metaverse 2, n. 2 (30 dicembre 2021): 1. http://dx.doi.org/10.54517/met.v2i2.1867.
Ferrein, Alexander, e Thomas Meyer. "A Brief Overview of Artificial Intelligence in South Africa". AI Magazine 33, n. 1 (15 marzo 2012): 99–103. http://dx.doi.org/10.1609/aimag.v33i1.2357.
Li, Wanting, Haiyan Liu, Feng Cheng, Yanhua Li, Sijin Li e Jiangwei Yan. "Artificial intelligence applications for oncological positron emission tomography imaging". European Journal of Radiology 134 (gennaio 2021): 109448. http://dx.doi.org/10.1016/j.ejrad.2020.109448.
Tesi sul tema "Artifical intelligence":
Metz, Clément. "Codages optimisés pour la conception d'accélérateurs matériels de réseaux de neurones profonds". Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPAST190.
Neural networks are an important component of machine learning tools because of their wide range of applications (health, energy, defence, finance, autonomous navigation, etc.). The performance of neural networks is greatly influenced by the complexity of their architecture in terms of the number of layers, neurons and connections. But the training and inference of ever-larger networks translates to greater demands on hardware resources and longer computing times. Conversely, their portability is limited on embedded systems with low memory and/or computing capacity.The aim of this thesis is to study and design methods for reducing the hardware footprint of neural networks while preserving their performance as much as possible. We restrict ourselves to convolution networks dedicated to computer vision by studying the possibilities offered by quantization. Quantization aims to reduce the hardware footprint, in terms of memory, bandwidth and computation operators, by reducing the number of bits in the network parameters and activations.The contributions of this thesis consist of a new post-training quantization method based on the exploitation of spatial correlations of network parameters, an approach facilitating the learning of very highly quantized networks, and a method aiming to combine mixed precision quantization and lossless entropy coding.The contents of this thesis are essentially limited to algorithmic aspects, but the research orientations were strongly influenced by the requirement for hardware feasibility of our solutions
Zaccagnino, Gianluca. "Computer Music Algorithms. Bio-inspired and Artificial Intelligence Applications". Doctoral thesis, Universita degli studi di Salerno, 2017. http://hdl.handle.net/10556/2564.
Music is one of the arts that have most benefited from the invention of computers. Originally, the term Computer Music was used in the scientific community to identify the application of information technology in music composition. It began over time to include the theory and application of new or existing technologies in music, such as sound synthesis, sound design, acoustic, psychoacoustic. Thanks to its interdisciplinary nature, Computer Music can be seen as the encounter of different disciplines. In the last years technology has redefined the way individuals can work, communicate, share experiences, constructively debate, and actively participate to any aspect of the daily life, ranging from business to education, from political and intellectual to social, and also in music activity, such as play music, compose music and so on. In this new context, Computer Music has become an emerging research area for the application of Computational Intelligence techniques, such as machine learning, pattern recognition, bio-inspired algorithms and so on. My research activity is concerned with the Bio-inspired and Artificial Intelligence Applications in the Computer Music. Some of the problems I addressed are summarized in the following. Automatic composition of background music for games, films and other human activities: EvoBackMusic. Systems for real-time composition of background music respond to changes of the environment by generating music that matches the current state of the environment and/or of the user. We propose one such a system that we call EvoBackMusic. It is a multiagent system that exploits a feed-forward neural network and a multi-objective genetic algorithm to produce background music. The neural network is trained to learn the preferences of the user and such preferences are exploited by the genetic algorithm to compose the music. The composition process takes into account a set of controllers that describe several aspects of the environment, like the dynamism of both the user and the 2 context, other physical characteristics, and the emotional state of the user. Previous system mainly focus on the emotional aspect. Publications: • Roberto De Prisco, Delfina Malandrino, Gianluca Zaccagnino, Rocco Zaccagnino: ‘‘An Evolutionary Composer for Real-Time Background Music’’. EvoMUSART 2016: 135-151. Interaction modalities for music performances: MarcoSmiles. In this field we considered new interaction modalities during music performances by using hands without the support of a real musical instrument. Exploiting natural user interfaces (NUI), initially conceived for the game market, it is possible to enhance the traditional modalities of interaction when accessing to technology, build new forms of interactions by transporting users in a virtual dimension, but that fully reflects the reality, and finally, improve the overall perceived experience. The increasing popularity of these innovative interfaces involved their adoption in other fields, including Computer Music. We propose a system, named MarcoSmiles, specifically designed to allow individuals to perform music in an easy, innovative, and personalized way. The idea is to design new interaction modalities during music performances by using hands without the support of a real musical instrument. We exploited Artificial Neural Networks to customize the virtual musical instrument, to provide the information for the mapping of the hands configurations into musical notes and, finally, to train and test these configurations. We performed several tests to study the behavior of the system and its efficacy in terms of learning capabilities. Publications: • Roberto De Prisco, Delfina Malandrino, Gianluca Zaccagnino, Rocco Zaccagnino: ‘‘Natural Users Interfaces to support and enhance Real-Time Music Performance’’. AVI 2016. 3 Bio-inspired approach for automatic music composition Here we describe a new bio-inspired approach for automatic music composition in a specific style: Music Splicing System. Splicing systems were introduced by Tom Head (1987) as a formal model of a recombination process between DNA molecules. The existing literature on splicing systems mainly focuses on the computational power of these systems and on the properties of the generated languages; very few applications based on splicing systems have been introduced. We show a novel application of splicing systems to build an automatic music composer. As a result of a performance study we proved that our composer outperforms other meta-heuristics by producing better music according to a specific measure of quality evaluation, and this proved that the proposed system can be seen also as a new valid bio-inspired strategy for automatic music composition. Publications: ▪ Clelia De Felice, Roberto De Prisco, Delfina Malandrino, Gianluca Zaccagnino, Rocco Zaccagnino, Rosalba Zizza: ‘‘Splicing Music Composition’’. Information Sciences Journal, 385: 196 – 215 (2017). ▪ Clelia De Felice, Roberto De Prisco, Delfina Malandrino, Gianluca Zaccagnino, Rocco Zaccagnino, Rosalba Zizza: ‘‘Chorale Music Splicing System: An Algorithmic Music Composer Inspired by Molecular Splicing’’. EvoMusart 2015: 50 – 61. Music and Visualization Here we describe new approaches for learning of harmonic and melodic rules of classic music, by using visualization techniques: VisualMelody and VisualHarmony. Experienced musicians have the ability to understand the structural elements of music compositions. Such an ability is built over time through the study of music theory, the understanding of rules that guide the composition of music, and through countless hours of practice. The learning process is hard, especially for classical music, where the rigidity of the music structures and styles requires great effort to understand, assimilate, and then master the learned notions. In particular, we focused our attention on a specific type of music compositions, namely, music in chorale style (4-voice music). Composing such type of music 4 is often perceived as a difficult task, because of the rules the composer has to adhere to. In this paper we propose a visualization technique that can help people lacking a strong knowledge of music theory. The technique exploits graphic elements to draw the attention on the possible errors in the composition. We then developed two interactive systems, named VisualMelody and VisualHarmony, that employ the proposed visualization techniques to facilitate the understanding of the structure of music compositions. The aim is to allow people to make 4-voice music composition in a quick and effective way, i.e., avoiding errors, as dictated by classical music theory rules. Publications: ▪ Roberto De Prisco, Delfina Malandrino, Donato Pirozzi, Gianluca Zaccagnino, Rocco Zaccagnino: ‘‘Understanding the structure of music compositions: is visualization an effective approach?’’ Information Visualization Journal, 2016. (DOI): 10.1177/1473871616655468 • Delfina Malandrino, Donato Pirozzi, Gianluca Zaccagnino, Rocco Zaccagnino: ‘‘A Color-Based Visualization Approach to Understand Harmonic Structures of Musical Compositions’’. IV 2015: 56-61. • Delfina Malandrino, Donato Pirozzi, Gianluca Zaccagnino, Rocco Zaccagnino: ‘‘Visual Approaches for Harmonic Analysis of 4-part Music: Implementation and Evaluation’’. Major revision – Journal of Visual Languages and Computing, 2016. [edited by Author]
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Södergren, Gunnar. "Exploring Need-based AI Behaviour and its Effect on the Game Experience of Neverwinter Nights". Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2699.
Singleplayer-rollspel är en populär genre bland såväl spelare som utvecklare, med stora titlar såsom Skyrim av Bethesda och Mass Effect 3 av Bioware. På senare tid har utvcklandet av levande och avancerad AI erhållit mycket fokus inom denna typ av spel och stora framsteg har tagits vad gäller att skapa levnadslika och realistiska icke-spelarkaraktärer. Det är dock fortfarande en vanlig förekomst att ickespelarkaraktärer i denna typ av spel saknar en egen agenda eller plan och därför endast står och väntar på att spelaren ska interagera med dem. Denna uppsats har syftat till att implementera ett behovsbaserat system som till viss del liknar det som används i The Sims av Maxis, där icke-spelarkaraktärer blir hungriga, trötta och liknande, och att testa huruvida detta system förhöjer spelupplevelsen. Systemet har implementerats med hjälp av Aurora Toolset till Neverwinter Nights av Bioware och har testats av ett antal personer i en egenskapad modul till spelet. Resultatet har visat, entydigt, att implementationen av detta behovsbaserade system förhöjde spelupplevelsen. Även om systemet, i denna version, är en prototyp, ger det en indikation på att användandet av ett behovsbaserat system kan förhöja spelupplvelsen i ett singeplayer-rollspel.
Toofanee, Mohammud Shaad Ally. "An innovative ecosystem based on deep learning : Contributions for the prevention and prediction of diabetes complications". Electronic Thesis or Diss., Limoges, 2023. https://aurore.unilim.fr/theses/nxfile/default/656b0a1f-2ff2-49c5-bb3e-f34704d6f6b0/blobholder:0/2023LIMO0107.pdf.
In the year 2021, estimations indicated that approximately 537 million individuals were affected by diabetes, a number anticipated to escalate to 643 million by the year 2030 and further to 783 million by 2045. Diabetes, characterized as a persistent metabolic ailment, necessitates unceasing daily care and management. In the context of Mauritius, as per the most recent report by the International Diabetes Federation, the prevalence of diabetes, specifically Type 2 Diabetes (T2D), stood at 22.6% of the population in 2021, with projections indicating a surge to 26.6% by the year 2045. Amidst this alarming trend, a concurrent advancement has been observed in the realm of technology, with artificial intelligence techniques showcasing promising capabilities in the spheres of medicine and healthcare. This doctoral dissertation embarks on the exploration of the intersection between artificial intelligence and diabetes education, prevention, and management.We initially focused on exploring the potential of artificial intelligence (AI), more specifically, deep learning, to address a critical complication linked to diabetes – Diabetic Foot Ulcer (DFU). The emergence of DFU poses the grave risk of lower limb amputations, consequently leading to severe socio-economic repercussions. In response, we put forth an innovative solution named DFU-HELPER. This tool serves as a preliminary measure for validating the treatment protocols administered by healthcare professionals to individual patients afflicted by DFU. The initial assessment of the proposed tool has exhibited promising performance characteristics, although further refinement and rigorous testing are imperative. Collaborative efforts with public health experts will be pivotal in evaluating the practical efficacy of the tool in real-world scenarios. This approach seeks to bridge the gap between AI technologies and clinical interventions, with the ultimate goal of improving the management of patients with DFU.Our research also addressed the critical aspects of privacy and confidentiality inherent in handling health-related data. Acknowledging the extreme importance of safeguarding sensitive information, we delved into the realm of Peer-to-Peer Federated Learning. This investigation specifically found application in our proposal for the DFU-Helper tool discussed earlier. By exploring this advanced approach, we aimed to ensure that the implementation of our technology aligns with privacy standards, thereby fostering a trustworthy and secure environment for healthcare data management.Finally, our research extended to the development of an intelligent conversational agent designed to offer round-the-clock support for individuals seeking information about diabetes. In pursuit of this goal, the creation of an appropriate dataset was paramount. In this context, we leveraged Natural Language Processing techniques to curate data from online media sources focusing on diabetes-related content
Lajoie, Isabelle. "Apprentissage de représentations sur-complètes par entraînement d’auto-encodeurs". Thèse, 2009. http://hdl.handle.net/1866/3768.
Progress in the machine learning domain allows computational system to address more and more complex tasks associated with vision, audio signal or natural language processing. Among the existing models, we find the Artificial Neural Network (ANN), whose popularity increased suddenly with the recent breakthrough of Hinton et al. [22], that consists in using Restricted Boltzmann Machines (RBM) for performing an unsupervised, layer by layer, pre-training initialization, of a Deep Belief Network (DBN), which enables the subsequent successful supervised training of such architecture. Since this discovery, researchers studied the efficiency of other similar pre-training strategies such as the stacking of traditional auto-encoder (SAE) [5, 38] and the stacking of denoising auto-encoder (SDAE) [44]. This is the context in which the present study started. After a brief introduction of the basic machine learning principles and of the pre-training methods used until now with RBM, AE and DAE modules, we performed a series of experiments to deepen our understanding of pre-training with SDAE, explored its different proprieties and explored variations on the DAE algorithm as alternative strategies to initialize deep networks. We evaluated the sensitivity to the noise level, and influence of number of layers and number of hidden units on the generalization error obtained with SDAE. We experimented with other noise types and saw improved performance on the supervised task with the use of pepper and salt noise (PS) or gaussian noise (GS), noise types that are more justified then the one used until now which is masking noise (MN). Moreover, modifying the algorithm by imposing an emphasis on the corrupted components reconstruction during the unsupervised training of each different DAE showed encouraging performance improvements. Our work also allowed to reveal that DAE was capable of learning, on naturals images, filters similar to those found in V1 cells of the visual cortex, that are in essence edges detectors. In addition, we were able to verify that the learned representations of SDAE, are very good characteristics to be fed to a linear or gaussian support vector machine (SVM), considerably enhancing its generalization performance. Also, we observed that, alike DBN, and unlike SAE, the SDAE had the potential to be used as a good generative model. As well, we opened the door to novel pre-training strategies and discovered the potential of one of them : the stacking of renoising auto-encoders (SRAE).
Libri sul tema "Artifical intelligence":
Baruque, Bruno, Bernabe Dorronsoro, José A. Gámez, Edurne Barrenechea, Alicia Troncoso, Mikel Galar e José M. Puerta. Advances in Artificial Intelligence: 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015 Albacete, Spain, November ... Springer, 2015.
Capitoli di libri sul tema "Artifical intelligence":
Korf, Richard. "Artificial Intelligence Search Algorithms". In Algorithms and Theory of Computation Handbook, Second Edition, Volume 2, 1–23. Chapman and Hall/CRC, 2009. http://dx.doi.org/10.1201/9781584888215-c22.
"Mind and machine—artificial intelligence". In Diving Into the Bitstream, 208–26. Routledge, 2012. http://dx.doi.org/10.4324/9780203153277-15.
"Computational Intelligence on Medical Imaging with Artificial Neural Networks". In Computational Intelligence in Medical Imaging, 15–40. Chapman and Hall/CRC, 2009. http://dx.doi.org/10.1201/9781420060614-5.
"Deformable Organisms: An Artificial Life Framework for Automated Medical Image Analysis". In Computational Intelligence in Medical Imaging, 447–88. Chapman and Hall/CRC, 2009. http://dx.doi.org/10.1201/9781420060614-19.
"Application of Artificial Intelligence to Predictive Microbiology Rosa Marı´a Garcı´a-Gimeno, Ce´sar Herva´s-Martinez",. In Novel Food Processing Technologies, 631–50. CRC Press, 2004. http://dx.doi.org/10.1201/9780203997277-33.
"of comprehension involved, as well as of processes of production, has been under-taken by cognitive psychologists, and workers in artificial intelligence concerned with the computer simulation of production and comprehension. From the per-spective of CLS, the most important result of work on comprehension is the stress which has been placed upon its active nature: you do not simply ‘decode’ an utter-ance, you arrive at an interpretation through an active process of matching fea-tures of the utterance at various levels with representations you have stored in your long-term memory. These representations are prototypes for a very diverse collection of things – the shapes of words, the grammatical forms of sentences, the typical structure of a narrative, the properties of types of object and person, the expected sequence of events in a particular situation type, and so forth. Some of these are linguistic, and some of them are not. Anticipating later discussion, let us refer to these prototypes collectively as ‘members’ resources’, or MR for short. The main point is that comprehension is the outcome of interactions between the utterance being interpreted, and MR. Not surprisingly, cognitive pyschology and artificial intelligence have given little attention to the social origins or significance of MR. I shall argue later that attention to the processes of production and comprehension is essential to an under-standing of the interrelations of language, power and ideology, and that this is so because MR are socially determined and ideologically shaped, though their ‘common sense’ and automatic character typically disguises that fact. Routine and unselfconscious resort to MR in the ordinary business of discourse is, I shall sug-gest, a powerful mechanism for sustaining the relations of power which ultimately underlie them." In Pragmatics and Discourse, 133. Routledge, 2005. http://dx.doi.org/10.4324/9780203994597-8.
"possible expenditure of whatever resource (time, money, energy . . . ) it takes. Efficiency with respect to relative goals is a matter of striking a balance between degree of achievement and expenditure. In the special case where the expenditure is fixed – say all the time available is going to be spent anyhow – efficiency con-sists in achieving the goal to the highest possible degree. Most discussions of information processing, whether in experimental psycho-logy or in artificial intelligence, have been concerned with the realisation of abso-lute goals. ‘Problem solving’ has become the paradigm of information processing. The problems considered have a fixed solution; the goal of the information-processing device is to find this solution; efficiency consists in finding it at the minimal cost. However, not all cognitive tasks fit this description; many tasks con-sist not in reaching an absolute goal, but in improving on an existing state of affairs. Hence, cognitive efficiency may have to be characterised differently for dif-ferent devices. Simpler information-processing devices, whether natural, such as a frog, or artificial, such as an electronic alarm system, process only very specific informa-tion: for example, metabolic changes and fly movements for frogs, noises and other vibrations for alarm systems. Their information-processing activity consists in mon-itoring changes in the values of a few variables. They could be informally described as engaged in answering a few set questions: ‘Is there a fly-like object within reach?’, ‘Is there a large body moving in the room?’ More complex information-processing devices, by contrast, can define and monitor new variables or formu-late and answer new questions. For the simpler devices, efficiency consists in answering their set questions at the minimal processing cost. Efficiency cannot be so easily defined for more com-plex devices such as human beings. For such devices, efficient information pro-cessing may involve formulating and trying to answer new questions despite the extra processing costs incurred. Formulating and answering specific questions must then be seen as subservient to a more general and abstract goal. It is in relation to this general goal that the efficiency of complex information-processing devices must be characterised. On the general goal of human cognition, we have nothing better to offer than rather trivial speculative remarks. However, these remarks have important and non-trivial consequences. It seems that human cognition is aimed at improving the individual’s knowledge of the world. This means adding more information, infor-mation that is more accurate, more easily retrievable, and more developed in areas of greater concern to the individual. Information processing is a permanent life-long task. An individual’s overall resources for information processing are, if not quite fixed, at least not very flexible. Thus, long-term cognitive efficiency consists in improving one’s knowledge of the world as much as possible given the avail-able resources. What, then, is short-term cognitive efficiency – efficiency, say, in the way your mind spends the next few seconds or milliseconds? This is a more concrete question, and one that is harder to answer. At every moment, many different cog-nitive tasks could be performed, and this for two reasons: first, human sensory". In Pragmatics and Discourse, 153. Routledge, 2005. http://dx.doi.org/10.4324/9780203994597-24.
"he need never have made himself before she spoke. What she expects, rightly, is that her utterance will act as a prompt, making him recall parts of the book that he had previously forgotten, and construct the assumptions needed to understand the allusion. In both these examples Mary makes assumptions about what assumptions are, or will be, manifest to Peter. Peter trusts that the assumptions he spontaneously makes about the church and about Sense and Sensibility, which help him understand Mary’s utterances, are those she expected him to make. To communicate success-fully, Mary had to have some knowledge of Peter’s cognitive environment. As a result of their successful communication, their mutual cognitive environment is enlarged. Note that symmetrical co-ordination and mutual knowledge do not enter into the picture at all. The most fundamental reason for adopting the mutual-knowledge framework, as for adopting the code model, is the desire to show how successful communi-cation can be guaranteed, how there is some failsafe algorithm by which the hearer can reconstruct the speaker’s exact meaning. Within this framework the fact that communication often fails is explained in one of two ways: either the code mech-anism has been imperfectly implemented, or there has been some disruption due to ‘noise’. A noiseless, well-implemented code mechanism should guarantee per-fect communication. In rejecting the mutual-knowledge framework, we abandon the possibility of using a failsafe algorithm as a model of human communication. But since it is obvious that the communication process takes place at a risk, why assume that it is governed by a failsafe procedure? Moreover, if there is one conclusion to be drawn from work on artificial intelligence, it is that most cognitive processes are so complex that they must be modelled in terms of heuristics rather than failsafe algorithms. We assume, then, that communication is governed by a less-than-perfect heuristic. On this approach, failures in communication are to be expected: what is mysterious and requires explanation is not failure but success. As we have seen, the notion of mutual manifestness is not strong enough to salvage the code theory of communication. But then, this was never one of our aims. Instead of taking the code theory for granted and concluding that mutual knowledge must therefore exist, we prefer to look at what kind of assumptions people are actually in a position to make about each other’s assumptions, and then see what this implies for an account of communication. Sometimes, we have direct evidence about other people’s assumptions: for instance, when they tell us what they assume. More generally, because we mani-festly share cognitive environments with other people, we have direct evidence about what is manifest to them. When a cognitive environment we share with other people is mutual, we have evidence about what is mutually manifest to all of us. Note that this evidence can never be conclusive: the boundaries of cogni-tive environments cannot be precisely determined, if only because the threshold between very weakly manifest assumptions and inaccessible ones is unmarked. From assumptions about what is manifest to other people, and in particular about what is strongly manifest to them, we are in a position to derive further",. In Pragmatics and Discourse, 151. Routledge, 2005. http://dx.doi.org/10.4324/9780203994597-22.
Atti di convegni sul tema "Artifical intelligence":
Celik, Anil, e Burak Yildirim. "Turkish Profanity Detection Enhanced by Artificial Intelligence". In 2020 28th Signal Processing and Communications Applications Conference (SIU). IEEE, 2020. http://dx.doi.org/10.1109/siu49456.2020.9302119.
Kjellgren, Alexander, Per Kettil, Mats Karlsson e Rasmus Rempling. "Opportunities in Civil Projects with Artificial Intelligence". In IABSE Symposium, Istanbul 2023: Long Span Bridges. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2023. http://dx.doi.org/10.2749/istanbul.2023.0022.
Chao, Chian-Hsueng. "Ethics Issues in Artificial Intelligence". In 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2019. http://dx.doi.org/10.1109/taai48200.2019.8959925.
Terenzi, Benedetta, Valeria Menchetelli, Giacomo Pagnotta e Ludovica Avallone. "Connection between AI and product design - Potentials and critical issues in the text-to-image software-assisted design experience". In Intelligent Human Systems Integration (IHSI 2024) Integrating People and Intelligent Systems. AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1004511.
Lukic, Bojan, Jasper Sprockhoff, Alexander Ahlbrecht, Siddhartha Gupta e Umut Durak. "Iterative Scenario-Based Testing in an Operational Design Domain for Artificial Intelligence Based Systems in Aviation". In ASIM Workshop STS/GMMS/EDU 2023. ARGESIM Publisher Vienna, 2023. http://dx.doi.org/10.11128/arep.21.a2108.
Wang, Chi-Shiang, Hung-Chun Chne e Jung-Hsien Chiang. "Discovering What You Cared by Intelligent Recommender System". In 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2019. http://dx.doi.org/10.1109/taai48200.2019.8959944.
Winters, R. Michael, Ankur Kalra e Bruce N. Walker. "Hearing Artificial Intelligence: Sonification Guidelines & Results From a Case-study in Melanoma Diagnosis". In ICAD 2019: The 25th International Conference on Auditory Display. Newcastle upon Tyne, United Kingdom: Department of Computer and Information Sciences, Northumbria University, 2019. http://dx.doi.org/10.21785/icad2019.021.
Lee, Chang-Shing, Mei-Hui Wang, Yi-Lin Tsai, Rin-Pin Chang, Lian-Chao Li, Noriko Takese, Shion Yamamoto e Naoyuki Kubota. "FML-based Intelligent Agent for Robotic e-Learning and Entertainment Application". In 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2019. http://dx.doi.org/10.1109/taai48200.2019.8959880.
Mu, Shenglin, Satoru Shibata, Tomonori Yamamoto, Kanya Tanaka, Shota Nakashima e Tung-kuan Liu. "Experimental Study on Speed Control of Ultrasonic Motor using Intelligent IMC-PID Control". In 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2019. http://dx.doi.org/10.1109/taai48200.2019.8959888.
Huang, Han-Chun, e Pou-Jen Ku. "Intelligent technology enhances the friendliness of the pharmacy care service : Identification in drug prescription". In 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2019. http://dx.doi.org/10.1109/taai48200.2019.8959839.