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Littérature scientifique sur le sujet « AI analysis »

Auteur : Grafiati

Publié le 7 juin 2025

Mis à jour le 2 août 2025

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Articles de revues sur le sujet "AI analysis"

Jastržemskis, Rihards, and Pēteris Grabusts. "ANALYSIS OF SYMBOLIC AI AND CONNECTIONIST AI APPROACHES." HUMAN. ENVIRONMENT. TECHNOLOGIES. Proceedings of the Students International Scientific and Practical Conference, no. 28 (September 10, 2024): 44–47. http://dx.doi.org/10.17770/het2024.28.8257.

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This research project aims to conduct a comparative analysis of two prominent paradigms within artificial intelligence: Symbolic AI (also known as classical AI or GOFAI - Good Old-Fashioned AI) and Connectionist AI (also known as neural network-based AI). Both approaches have played significant roles in the development of AI systems, but they differ in their underlying principles, methodologies, and applications. By comparing and contrasting these two approaches, this study seeks to provide insights into their strengths, weaknesses, and suitability for different types of AI tasks.

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H. R, Sindhu Rashmi, Prof Anisha B. S, and Dr Ramakanth Kumar. P. "Smart Document Analysis Using AI-ML." International Journal of Innovative Research in Computer Science & Technology 7, no. 3 (2019): 54–70. http://dx.doi.org/10.21276/ijircst.2019.7.3.6.

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R Leach, A., D. P Dolata, and C. K Prout. "AI in conformational analysis." Journal of Molecular Graphics 5, no. 2 (1987): 107. http://dx.doi.org/10.1016/0263-7855(87)80011-5.

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Lahat, Rotem, Noa Berick, Majd Hajouj, Tali Teitelbaum, and Isaac Shochat. "AIAIAI: AI insights on amassing influence in AI-related publications – an AI-assisted retrospective analysis into AI-related publication." BMJ Health & Care Informatics 32, no. 1 (2025): e101244. https://doi.org/10.1136/bmjhci-2024-101244.

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ObjectivesThis study analyses the trend of artificial intelligence (AI)-related publications in the medical field over the past decade and demonstrates the potential of AI in automating data analysis. We hypothesise exponential growth in AI-related publications, with continuous growth in the foreseeable future.MethodsRetrospective, AI-assisted analysis was conducted using the OpenAI application programming interface for data collection and evaluation. Publications from the top 50 medical journals (Web of Science, Journal Citation Report, 2022) covering 2014 to June 2024. A total of 315 209 pap

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LeCun, Yann. "Artificial Intelligence in Scientific Research: Transforming Data Analysis and Discovery." International Journal of Innovative Computer Science and IT Research 1, no. 01 (2025): 1–9. https://doi.org/10.63665/ijicsitr.v1i01.01.

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Artificial Intelligence (AI) has become a transformative tool in scientific research, reshaping traditional methodologies by enabling advanced data analysis, hypothesis testing, and predictive modeling. The integration of machine learning (ML), deep learning (DL), and natural language processing (NLP) has significantly accelerated discoveries in medicine, physics, chemistry, environmental science, and other disciplines. AI-driven technologies allow researchers to process large datasets, identify complex patterns, and generate predictive insights with unprecedented accuracy and speed. These inn

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Ha, Ju-Hye, Sung-Ji Kim, and Chang-Hoon Oh. "Impact of AI Literacy on AI Ethics: A Scenario-Based Analysis." Journal of Korea Multimedia Society 28, no. 2 (2025): 333–52. https://doi.org/10.9717/kmms.2025.28.2.333.

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Alok, Kumar. "AI-Driven Market Trend Analysis." Journal of Research and Innovation in Technology, Commerce and Management Volume 2, Issue 4 (2025): 2454–61. https://doi.org/10.5281/zenodo.15301748.

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Artificial Intelligence (AI) has changed market trend analysis through real-time scanning and accurate forecasting of trends. AI technologies, such as machine learning, natural language processing (NLP) and big data analytics, allow organizations to uncover trends, take actions and displace the constraints of traditional methods. This research studies AI-oriented methods, including sentiment analysis, deep learning and predictive modeling. It demonstrates the ability of AI to process significant amounts of data, the areas AI might be used and discusses limitations, such as data quality issues,

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HAWALAH, YOUSIF. "Will of AI-Mansour Bin Abi Amir AI-Amri AI-Andalusi: Study and Analysis." Journal of King Abdulaziz University-Educational Sciences 7, no. 1 (1994): 225–66. http://dx.doi.org/10.4197/edu.7-1.11.

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Ibadildin, Nurkhat, Zhaxat Kenzhin, Gaukhar Yeshenkulova, et al. "Artificial intelligence in project management: A bibliometric analysis." Problems and Perspectives in Management 23, no. 2 (2025): 252–64. https://doi.org/10.21511/ppm.23(2).2025.17.

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This study explores the integration of artificial intelligence (AI) into project management through a bibliometric analysis of scholarly publications and patents from 2001 to 2024. The paper aims to identify key trends, emerging applications, and global contributions to this evolving field. The study analyzes 51,752 patents from Lens, 5.5 million scholarly records from Google Scholar, and 436,380 records from Web of Science, providing a comprehensive overview of AI’s impact on project management. The analysis maps the evolution of AI-driven project management practices, focusing on resource al

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Mihail Mateev. "Comparative Analysis on Implementing Embeddings for Image Analysis." Journal of Information Systems Engineering and Management 10, no. 17s (2025): 89–102. https://doi.org/10.52783/jisem.v10i17s.2710.

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This research explores how artificial intelligence enhances construction maintenance and diagnostics, achieving 95% accuracy on a dataset of 10,000 cases. The findings highlight AI's potential to revolutionize predictive maintenance in the industry. The growing adoption of image embeddings has transformed visual data processing across AI applications. This study evaluates embedding implementations in major platforms, including Azure AI, OpenAI's GPT-4 Vision, and frameworks like Hugging Face, Replicate, and Eden AI. It assesses their scalability, accuracy, cost-effectiveness, and integration f

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Thèses sur le sujet "AI analysis"

Kobeissi, Meriana. "A conversational AI Framework for Cognitive Process Analysis." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAS025.

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Les processus métier (BP) sont les piliers fondamentaux des organisations, englobant toute une gamme d'activités structurées visant à atteindre des objectifs organisationnels distincts. Ces processus, caractérisés par une multitude de tâches, d'interactions et de flux de travail, offrent une méthodologie structurée pour superviser les opérations cruciales dans divers secteurs. Une découverte essentielle pour les organisations a été la reconnaissance de la valeur profonde inhérente aux données produites pendant ces processus. L'analyse des processus, une discipline spécialisée, explore ces jour

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Ko, Kai-Chung. "Protocol test sequence generation and analysis using AI techniques." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/29192.

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This thesis addresses two major issues in protocol conformance testing: test sequence generation and test result analysis. For test sequence generation, a new approach based on the constraint satisfaction problem (CSP) techniques, which is widely used in the AI community, is presented. This method constructs a unique test sequence for a given FSM by using an initial test sequence, such as a transition tour or an UIO test sequence, and incrementally generating a set of test subsequences which together represent the constraints imposed on the overall structure of the FSM. The new method not only

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Dissanayake, Lekamlage Dilukshi Charitha Subashini Dissanayake, and Fabia Afzal. "AI-based Age Estimation from Mammograms." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20108.

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Background: Age estimation has attracted attention because of its various clinical and medical applications. There are many studies on human age estimation from biomedical images such as X-ray images, MRI, facial images, dental images etc. However, there is no research done on mammograms for age estimation. Therefore, in our research, we focus on age estimation from mammogram images. Objectives: The purpose of this study is to make an AI-based model for estimating age from mammogram images based on the pectoral muscle segment and check its accuracy. At first, we segment the pectoral muscle fro

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WIEHLER, Lukas. "How can AI regulation be effectively enforced? : comparing compliance mechanisms for AI regulation with a multiple-criteria decision analysis." Doctoral thesis, European University Institute, 2022. http://hdl.handle.net/1814/74805.

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Award date: 17 June 2022. Supervisor: Professor Andrea Renda (European University Institute)<br>Newly emerging AI regulations need effective and innovative enforcement and compliance mechanisms to assure that fundamental and human rights are protected when using an AI system. This study compares four different compliance mechanisms namely ‘Real-Time and Automated Conformity Assessment’, ‘Standardization and Certification’, ‘Algorithmic Impact Assessment’ and ‘Algorithmic Auditing’ as well as three different assurers of compliance namely deployers, notified bodies and civil society organisation

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Dorrikhteh, Masoud. "A Deep-Learning Approach for Marker-less Stride Parameters Analysis with Two Cameras." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42511.

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Human gait analysis is an essential indicator for physical and neuroglial health of an individual. Recent developments in deep-learning approaches to computer vision make possible new techniques for body segment and joint detection from photos and video frames. In this thesis, we propose a deep learning approach for non-invasive video-based gait analysis using two RGB cameras that would be suitable for routine gait monitoring in senior care and rehabilitation centers. Due to modularity and the low cost of implementation, it is considered an affordable solution for such centers. Furthermore, s

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Daniel, Muzito Kim. "Digitalisation online condition monitoring and AI analysis in a vacuum pump." Thesis, Högskolan i Gävle, Avdelningen för elektronik, matematik och naturvetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-28826.

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Billerudkorsnäs is a good example of an industry that associated with a 24/7 production and where faults lead to downtime in the production process which in its turn generates substantial losses. Sustainability is essential for a prosperous future for Billerudkorsnäs, and with the growth of technologies and digitalization with big data that are in line with the coming Industry 4.0 standard, the company will have the possibility to ensure a sustainable production system. However, to be able to achieve this, it is necessary to implement an intelligent maintenance system into the traditional manu

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Maccarini, Francesco. "Modeling orchestration for computer assisted analysis and human-AI co-creativity." Electronic Thesis or Diss., Université de Lille (2022-....), 2024. http://www.theses.fr/2024ULILB047.

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L'orchestration est l'art de composer pour un ensemble d'instruments, impliquant le mélange et le contraste des timbres instrumentaux pour créer un son orchestral cohérent. Elle exige à la fois une planification artistique de haut niveau des idées musicales et un contrôle précis et minutieux des détails techniques. Chaque partie doit pouvoir être jouée sur l'instrument qui lui est propre et s'accorder avec le reste de l'ensemble.Cette thèse vise à formaliser et à élargir les connaissances sur l'orchestration en la décrivant sous l'angle des mathématiques et de l'informatique, tout en proposant

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Sugianto, Nehemia. "Responsible AI for Automated Analysis of Integrated Video Surveillance in Public Spaces." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/409586.

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Understanding customer experience in real-time can potentially support people’s safety and comfort while in public spaces. Existing techniques, such as surveys and interviews, can only analyse data at specific times. Therefore, organisations that manage public spaces, such as local government or business entities, cannot respond immediately when urgent actions are needed. Manual monitoring through surveillance cameras can enable organisation personnel to observe people. However, fatigue and human distraction during constant observation cannot ensure reliable and timely analysis. Artificial int

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Montecchio, Laura <1995&gt. "Tradizione, Innovazione, Autenticità; un'applicazione di content analysis ai ristoranti della terraferma veneziana." Master's Degree Thesis, Università Ca' Foscari Venezia, 2022. http://hdl.handle.net/10579/20818.

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Il presente lavoro di ricerca comincia con una review della letteratura sull'importanza economica acquisita nei tempi più recenti dalle imprese culturali e creative, fino a focalizzarsi sul settore di interesse, ossia l'industria del gusto. In particolare, l'attenzione si rivolge al settore della ristorazione, dunque alla tipologia di ristoranti leggibili come culture based o imprese culturali, in quanto pongono la cultura al centro del proprio business. Il lavoro empirico comincia con l'ascolto delle interviste poste ai titolari dei ristoranti e mira a rispondere a due research gap ben defin

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MAURO, CESARE. "INDAGINE CEFALOMETRICA ORTODONTICA 3D: DAL FULL SIZE AI FOV RIDOTTI." Doctoral thesis, Università degli Studi di Milano, 2019. http://hdl.handle.net/2434/693229.

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OBJECTIVE CBCT IS ASSOCIATED WITH SIGNIFICANTLY HIGHER RADIATION EXPOSURE,IN PARTICULAR WITH LARGE FIELDS OF VIEW (FOV) THAN CONVENTIONAL X-RAY TECHNIQUES COMMONLY USED IN ORTHODONTICS. THE AIM OF THIS STUDY IS TO DESCRIBE A NEW MEDIUM FOV THREE DIMENSIONAL CEPHALOMETRIC ANALYSIS ON CBCT AND TO COMPARE THIS METHOD FOR ORTHODONTIC SAGITTAL DIAGNOSIS WITH TWO TRADITIONAL BI-DIMENSIONAL ANALYSES. MATERIALS AND METHODS 35 CBCT EXAMS (14 MALE; 21 FEMALE) WITH MEAN AGE 19,37+-11,76 WERE SELECTED FROM THE ARCHIVE OF THE DEPARTMENT OF DENTISTRY OF ARMY MILITARY HOSPITAL, MILAN, ITALY. A MEDIUM FOV THR

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Livres sur le sujet "AI analysis"

Cox, Louis Anthony. AI-ML for Decision and Risk Analysis. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32013-2.

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Karimipour, Hadis, and Farnaz Derakhshan, eds. AI-Enabled Threat Detection and Security Analysis for Industrial IoT. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76613-9.

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Tsikritsēs, Mēnas D. Apokalypsis Iōannou: Keimena kai hermēneies, 1os - 19os ai. : analysis periechomenou. Vikelaia Dēmotikē Vivliothēkē, 2006.

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Freguglia, Paolo. Dalle equipollenze ai sistemi lineari: Il contributo italiano al calcolo geometrico. QuattroVenti, 1992.

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Jansen, J. Studies on fertility in dairy cattle, based on analysis of AI data. [s.n.], 1986.

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Wheeler, Kathryn. How to Use Generative AI to Assist the Analysis of Qualitative Data. SAGE Publications Ltd, 2025. https://doi.org/10.4135/9781036217471.

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1978-, Tao Dacheng, Kacprzyk Janusz, Li Zhu, Izquierdo Ebroul, Wang Haohong, and SpringerLink (Online service), eds. Multimedia Analysis, Processing and Communications. Springer-Verlag Berlin Heidelberg, 2011.

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1966-, Olivier Patrick, and Gapp Klaus-Peter, eds. Representation and processing of spatial expressions. Lawrence Erlbaum Associates, 1998.

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Guoying, Zhao, Cheng Li, Pietikäinen Matti, and SpringerLink (Online service), eds. Machine Learning for Vision-Based Motion Analysis: Theory and Techniques. Springer-Verlag London Limited, 2011.

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Baron, Sheldon. An analysis of the application of AI to the development of intelligent aids for flight crew tasks. National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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Chapitres de livres sur le sujet "AI analysis"

Olson, David L., Desheng Dash Wu, Cuicui Luo, and Majid Nabavi. "Cluster Analysis." In AI for Risks. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4772-6_5.

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Marques, Oge. "Fundamentals of Medical Image Analysis." In AI for Radiology. CRC Press, 2023. http://dx.doi.org/10.1201/9781003110767-4.

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Ermacora, Michele. "Tactical Positioning through Environmental Analysis." In Game AI Uncovered. CRC Press, 2024. http://dx.doi.org/10.1201/9781003324102-19.

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Wang, May Ying, and Pengqi Wang. "AI-Driven Sentiment Analysis." In Chinese Social Media II. Routledge, 2025. https://doi.org/10.4324/9781003596516-11.

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Kapadia, Taher Kutbuddin, Vedangi Nilesh Gupte, Bhaumik Hitesh Thakker, and Tushar Vitthal Sawant. "Malware Analysis Using AI." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-9045-6_22.

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Mangal, Ravi, Nina Narodytska, Divya Gopinath, et al. "Concept-Based Analysis of Neural Networks via Vision-Language Models." In AI Verification. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65112-0_3.

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Zhao, Ningsheng, Jia Yuan Yu, Krzysztof Dzieciolowski, and Trang Bui. "Error Analysis of Shapley Value-Based Model Explanations: An Informative Perspective." In AI Verification. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65112-0_2.

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Takahashi, Takeshi, and Tao Ban. "Android Application Analysis Using Machine Learning Techniques." In AI in Cybersecurity. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98842-9_7.

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Kumar, Devender, Jyoti Batra, and Anjana Sharma. "Data Collection and Analysis for Humanitarian Action." In AI for Humanitarianism. CRC Press, 2025. https://doi.org/10.1201/9781003479109-2.

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Mehta, Meera, and Shivani Arora. "Sentiment Analysis of Social Media." In AI-Based Data Analytics. Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781032614083-5.

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Actes de conférences sur le sujet "AI analysis"

Casalicchio, Emiliano, and Alberto Cotumaccio. "AI-CRAS: AI-driven Cloud Service Requirement Analysis and Specification." In 2024 IEEE International Conference on Cloud Engineering (IC2E). IEEE, 2024. http://dx.doi.org/10.1109/ic2e61754.2024.00009.

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Prasad, Potu Ram, Mutyala Uday Kiran, and V. Subapriya. "AI Integrated Holistic Resume Analysis." In 2025 International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2025. https://doi.org/10.1109/iciccs65191.2025.10985728.

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Hübler, Bastian, and Volker Göhler. "EDUSENSE-AI: AI-POWERED ATTENTION AND EMOTION ANALYSIS FOR DIGITAL EDUCATION." In 17th annual International Conference of Education, Research and Innovation. IATED, 2024. https://doi.org/10.21125/iceri.2024.1550.

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Shashanka, R., Anisha Devi, K. Lakith Gowda, S. Kushal, and V. Ravi Kumar. "VisioGuide: An AI for Visually Impaired." In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE, 2025. https://doi.org/10.1109/icsadl65848.2025.10932984.

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Valles, Antonio, and Rebecca David. "Kairos for AI: Analysis, Projections, Pathfinding." In 2025 6th International Conference on Artificial Intelligence, Robotics and Control (AIRC). IEEE, 2025. https://doi.org/10.1109/airc64931.2025.11077554.

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Hu, Boyue Caroline, Divya Gopinath, Corina S. Păsăreanu, Nina Narodytska, Ravi Mangal, and Susmit Jha. "Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study)." In 2025 IEEE/ACM 4th International Conference on AI Engineering – Software Engineering for AI (CAIN). IEEE, 2025. https://doi.org/10.1109/cain66642.2025.00027.

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Zhao, Ziang. "Analysis on Coherent Memory Systems Within AI Training Workloads." In International Conference on Data Analysis and Machine Learning. SCITEPRESS - Science and Technology Publications, 2024. https://doi.org/10.5220/0013514800004619.

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Bardhiya, Himanshu S., Mutyala Pavitra, Ashutosh Bagde, and Vansh A. Bardhiya. "Harvest Helper: AI-Driven Crop Selection Model." In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE, 2025. https://doi.org/10.1109/icsadl65848.2025.10933125.

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Singh, Davinder, Joideep Banerjee, and Lionel Jayaraj. "Enhancing Game Development Process Using AI: A Comparative Analysis of Image Generative AI." In 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE). IEEE, 2024. https://doi.org/10.1109/metroxraine62247.2024.10796123.

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Mehta, Yukta, Aishwarya Ashok, Deepthi Desharaju, Padhmavathy Cebolu Srinivasan, Sowmya Manchikanti, and Jerry Gao. "Smart City AI Traffic Cloud - City Traffic Analysis and Monitoring Using AI Models." In 2025 IEEE Conference on Artificial Intelligence (CAI). IEEE, 2025. https://doi.org/10.1109/cai64502.2025.00185.

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Rapports d'organisations sur le sujet "AI analysis"

Seals, Corinne. Discourse Analysis and Conversation Analysis with AI. Instats Inc., 2025. https://doi.org/10.61700/4f3zvrvnoadmc1815.

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This two-day workshop provides a comprehensive introduction to discourse and conversation analysis, equipping participants with advanced tools and methodologies for analyzing language's role in shaping social realities. Led by Corinne Seals, attendees will gain practical experience with software like NVivo, TranscriberAG, and ELAN to enhance their research capabilities in interpreting complex linguistic data.

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Jang, Daisung. Using AI for Data Analysis in R. Instats Inc., 2025. https://doi.org/10.61700/f4fcdsmuu2e5q1584.

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This seminar explores how generative AI can enhance data analysis and visualization within R, enabling researchers to automate tasks and conduct more sophisticated analyses. Participants will gain practical skills in integrating generative AI with R, improving research productivity and helping with the interpretation and reporting of research results.

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Silver, Christina. Using Generative AI for Qualitative Analysis. Instats Inc., 2023. http://dx.doi.org/10.61700/qs6nzkddi20lw469.

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This comprehensive workshop is aimed at equipping researchers with the skills to utilize AI appropriately in their qualitative analysis. Covering a range of topics from understanding AI software tools to ethical considerations and troubleshooting, this seminar provides a unique opportunity to enhance research capabilities and gain a competitive edge in the academic field.

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Maerz, Seraphine. Using AI for Text Analysis: Advanced Applications. Instats Inc., 2024. https://doi.org/10.61700/nqumt3vu2zq3k1816.

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This one-day workshop provides an advanced exploration of AI-driven text analysis, focusing on the application and fine-tuning of open-source large language models to enhance research across various academic disciplines. Participants will gain practical skills in setting up local environments and employing sophisticated AI methodologies, empowering them to conduct independent and impactful text analysis while ensuring data security and privacy.

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Maerz, Seraphine. Using AI for Text Analysis in R. Instats Inc., 2024. http://dx.doi.org/10.61700/ti5uexui5ilrd1663.

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This one-day workshop provides a basic introduction to using artificial intelligence for text analysis. Tailored for researchers across a variety of social and health science fields, participants will gain practical skills in building text corpuses, topic modeling, and using ChatGPT, Copilot, and other Large Language Models (LLMs) in R, while addressing ethical considerations and validation techniques for AI-driven research.

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Schoeberl, Christian, Autumn Toney, and James Dunham. Identifying AI Research. Center for Security and Emerging Technology, 2023. http://dx.doi.org/10.51593/20220030.

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The choice of method for surfacing AI-relevant publications impacts the ultimate research findings. This report provides a quantitative analysis of various methods available to researchers for identifying AI-relevant research within CSET’s merged corpus, and showcases the research implications of each method.

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Chou, Daniel. Counting AI Research. Center for Security and Emerging Technology, 2022. http://dx.doi.org/10.51593/20220010.

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Tracking the output of a country’s researchers can inform assessments of its innovativeness or assist in evaluating the impact of certain funding initiatives. However, measuring research output is not as straightforward as it may seem. Using a detailed analysis that includes Chinese-language research publications, this data brief reveals that China's lead in artificial intelligence research output is greater than many English-language sources suggest.

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Gehlhaus, Diana, Joanne Boisson, Sara Abdulla, Jacob Feldgoise, Luke Koslosky, and Dahlia Peterson. China’s AI Workforce. Center for Security and Emerging Technology, 2022. http://dx.doi.org/10.51593/20220003.

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U.S. policies on artificial intelligence education and the AI workforce must grow, cultivate, attract, and retain the world’s best and brightest. Given China’s role as a producer of AI talent, understanding its AI workforce could provide important insight. This report provides an analysis of the AI workforce demand in China using a novel dataset of 6.8 million job postings. It then outlines potential implications along with future reports in this series.

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Imbrie, Andrew, James Dunham, Rebecca Gelles, and Catherine Aiken. Mainframes: A Provisional Analysis of Rhetorical Frames in AI. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20190046.

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Are great powers engaged in an artificial intelligence arms race? This issue brief explores the rhetorical framing of AI by analyzing more than 4,000 English-language articles over a seven-year period. Among its findings: a growing number of articles frame AI development as a competition, but articles using the competition frame represent a declining proportion of articles about AI.

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Andy Blunk, Andy Blunk. AI analysis of soil pH with a smartphone camera. Experiment, 2024. http://dx.doi.org/10.18258/65479.

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