Bibliographies thématiques / AI throughput

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Littérature scientifique sur le sujet « AI throughput »

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 throughput"

Wu, Jiajie, Weixing Dai, Claudia T. K. Lo, Lauren W. K. Tsui, and Terence T. W. Wong. "High-throughput, nondestructive, and low-cost histological imaging with deep-learning-assisted UV microscopy." Advanced Imaging 1, no. 2 (2024): 021001. http://dx.doi.org/10.3788/ai.2024.10007.

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Kurowski, Konrad, Sylvia Timme, Melanie Christine Föll, et al. "AI-Assisted High-Throughput Tissue Microarray Workflow." Methods and Protocols 7, no. 6 (2024): 96. http://dx.doi.org/10.3390/mps7060096.

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Immunohistochemical (IHC) studies of formalin-fixed paraffin-embedded (FFPE) samples are a gold standard in oncology for tumor characterization, and the identification of prognostic and predictive markers. However, despite the abundance of archived FFPE samples, their research use is limited due to the labor-intensive nature of IHC on large cohorts. This study aimed to create a high-throughput workflow using modern technologies to facilitate IHC biomarker studies on large patient groups. Semiautomatic constructed tissue microarrays (TMAs) were created for two tumor patient cohorts and IHC stai

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Machek, Ondřej, Tereza Konečná, and Daniela Slamková. "High Throughput 3D Volumes Data Acquisition Using AI." Microscopy and Microanalysis 28, S1 (2022): 3092–93. http://dx.doi.org/10.1017/s1431927622011527.

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Xiao, Qi, Fangfei Zhang, Luang Xu, et al. "High-throughput proteomics and AI for cancer biomarker discovery." Advanced Drug Delivery Reviews 176 (September 2021): 113844. http://dx.doi.org/10.1016/j.addr.2021.113844.

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Salinel, Brandon, Matthew Grudza, Sarah Zeien, et al. "Comparison of segmentation methods to improve throughput in annotating AI-observer for detecting colorectal cancer." Journal of Clinical Oncology 40, no. 4_suppl (2022): 142. http://dx.doi.org/10.1200/jco.2022.40.4_suppl.142.

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142 Background: Colorectal cancer (CRC) is the second leading cause of cancer-related deaths, and its outcome can be improved with better detection of incidental early CRC on routine CT of the abdomen and pelvis (CTAP). AI-second observer (AI) has the potential as shown in our companion abstract. The bottleneck in training AI is the time required for radiologists to segment the CRC. We compared two techniques for accelerating the segmentation process: 1) Sparse annotation (annotating some of the CT slice containing CRC instead of every slice); 2) Allowing AI to perform initial segmentation fol

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Eschemann, Patrick, Astrid Nieße, and Jürgen Sauer. "Prediction of simulated factory layout throughput using artificial intelligence." New Trends in Computer Sciences 2, no. 2 (2024): 101–16. https://doi.org/10.3846/ntcs.2024.22160.

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The use of artificial neural networks for the optimisation of factory layouts is not a common practice, primarily due to the challenge of collecting sufficient layout data to form datasets for artificial intelligence (AI) model training. This paper presents a supervised learning method derived from a PhD thesis that employs neural networks to assess factory layouts. The training data is generated using a random layout algorithm, which is capable of producing numerous layouts. These layouts are then labeled through a discrete event simulation. The combination of layouts and simulation metrics s

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Khaled, Haitham, and Emad Alkhazraji. "AI Optimization-Based Heterogeneous Approach for Green Next-Generation Communication Systems." Sensors 24, no. 15 (2024): 4956. http://dx.doi.org/10.3390/s24154956.

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Traditional heterogeneous networks (HetNets) are constrained by their hardware design and configuration. These HetNets have a limited ability to adapt to variations in network dynamics. Software-defined radio technology has the potential to address this adaptability issue. In this paper, we introduce a software-defined radio (SDR)-based long-term evolution licensed assisted access (LTE-LAA) architecture for next-generation communication networks. We show that with proper design and tuning of the proposed architecture, high-level adaptability in HetNets becomes feasible with a higher throughput

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Xue, Yexiang, Junwen Bai, Ronan Le Bras, et al. "Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery." Proceedings of the AAAI Conference on Artificial Intelligence 31, no. 2 (2017): 4635–42. http://dx.doi.org/10.1609/aaai.v31i2.19087.

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High-throughput materials discovery involves the rapid synthesis, measurement, and characterization of many different but structurally related materials. A central problem in materials discovery, the phase map identification problem, involves the determination of the crystal structure of materials from materials composition and structural characterization data. We present Phase-Mapper, a novel solution platform that allows humans to interact with both the data and products of AI algorithms, including the incorporation of human feedback to constrain or initialize solutions. Phase-Mapper is comp

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Angelino, Antimo. "Data & AI for Industrial Application." Advances in Machine Learning & Artificial Intelligence 5, no. 4 (2024): 01–07. https://doi.org/10.33140/amlai.05.04.05.

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The use of Artificial Intelligence in the Industry can lead to recovery of efficiency for industrial processes (such as reduce scrap and rework rate, increase throughput time), and this can carry competitive advantages. Nevertheless, to correctly deploy artificial intelligence projects it is needed to have connectivity and quality data. Both are enabling factors for AI projects, and industries must put in place processes to reach them before to start the AI journey

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Devi Rahmayanti. "Analysis of AI-Driven Modulation for Cognitive Cellular Networks : DNN Approach." International Journal of Mechanical, Electrical and Civil Engineering 1, no. 4 (2024): 86–101. https://doi.org/10.61132/ijmecie.v1i4.138.

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Objective: analyze the modulation scheme that can intelligently select the appropriate modulation model for service conditions to obtain a high Signal to Noise Ratio, as well as throughput efficiency on wireless networks through the DNN approach. Method: this study uses simulations with the Python language, through AI-Driven on BPSK, QPSK, 16-QAM, and 64-QAM modulation, to determine the SNR and Quality of Service (QoS) produced, both through conventional approaches and Deep Neuro Network (DNN). Researh Finding: AI-Driven modulation used for Cognitive Cellular Networks (CCN), through Deep Neuro

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Thèses sur le sujet "AI throughput"

Lai, Yen-Chi, and 賴彥齊. "High Throughput Hardware Implementation for Deep Learning AI Accelerator." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/jn7a98.

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碩士<br>國立中興大學<br>電機工程學系所<br>106<br>In this thesis, a high-throughput hardware accelerator for deep learning network is proposed. Since deep learning operation requires high data access from DRAM, we design a high data reuse architecture to reduce the data access directly from external DRAM and provide pipeline design to achieve high throughput design requirements. The architecture proposed in this thesis uses 8-bit precision computing, 128-bit bus, and parallel processing with 16 sets of processing units (PE) can achieve real-time operation at 125MHZ operating frequency and 4GOPS throughput, wh

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Livres sur le sujet "AI throughput"

DiMatteo, Larry A., Cristina Poncibò, and Michel Cannarsa, eds. The Cambridge Handbook of Artificial Intelligence. Cambridge University Press, 2022. http://dx.doi.org/10.1017/9781009072168.

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The technology and application of artificial intelligence (AI) throughout society continues to grow at unprecedented rates, which raises numerous legal questions that to date have been largely unexamined. Although AI now plays a role in almost all areas of society, the need for a better understanding of its impact, from legal and ethical perspectives, is pressing, and regulatory proposals are urgently needed. This book responds to these needs, identifying the issues raised by AI and providing practical recommendations for regulatory, technical, and theoretical frameworks aimed at making AI com

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Natale, Simone. Deceitful Media. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190080365.001.0001.

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Artificial intelligence (AI) is often discussed as something extraordinary, a dream—or a nightmare—that awakens metaphysical questions on human life. Yet far from a distant technology of the future, the true power of AI lies in its subtle revolution of ordinary life. From voice assistants like Siri to natural language processors, AI technologies use cultural biases and modern psychology to fit specific characteristics of how users perceive and navigate the external world, thereby projecting the illusion of intelligence. Integrating media studies, science and technology studies, and social psyc

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Voth, Ben. Invitation to Debate. Bloomsbury Academic, 2025. https://doi.org/10.5040/9798881843113.

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This comprehensive introductory textbook gives students the framework and tools to become great debaters and use those skills to further civil and respectful responses on contentious topics. Focusing on core concepts and skills of research, reasoning, and argumentation with a special focus on debate rhythms, the book builds students’ ability to express ideas and respectfully dissent, ultimately improving their individual resilience in adverse circumstances and encouraging the emergence of communal values in society. An Invitation to Debate takes students on a step-by-step preparation of case r

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Hall, Richard A. Robots in Popular Culture. Greenwood, 2021. http://dx.doi.org/10.5040/9798216009559.

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Robots in Popular Culture: Androids and Cyborgs in the American Imagination seeks to provide one go-to reference for the study of the most popular and iconic robots in American popular culture. In the last 10 years, technology and artificial intelligence (AI) have become not only a daily but a minute-by-minute part of American life—more integrated into our lives than anyone would have believed even a generation before. Americans have long known the adorable and helpful R2-D2 and the terrible possibilities of Skynet and its army of Terminators. Throughout, we have seen machines as valuable alli

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Denham Smith, Dina, and Alicia A. Grandey. Emotionally Charged. Oxford University PressNew York, 2025. https://doi.org/10.1093/oso/9780197750155.001.0001.

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Abstract Leaders are confronted with more emotional demands than ever, due to changes in the way people work, who they work with, and why they work. Emotionally Charged provides a comprehensive guide to help leaders and those who support them appreciate and navigate these exceptional new emotional demands. Each chapter equips readers with evidence-based insights and tools for building and applying the advanced emotional skills for effective leadership today, from regulating emotions in yourself and others to navigating emotionally charged work events effectively. Throughout the book, the autho

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McTurk, Clare, and Dimitri Koumbis. Fashion Buying. Bloomsbury Publishing Plc, 2025. https://doi.org/10.5040/9781350280601.

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What do fashion buyers do? How do they think? What does forecasting trends or planning a range actually entail? How can they shape the future of fashion? Featuring new interviews and analysis of the most up-to-date industry figures and trends, this 3rd edition has all you need to get up-to-speed on the people, processes and practicalities of buying in the fashion industry today. Illustrated with colour diagrams and fashion photographs, five to-the-point chapters break down the key areas of fashion buying: the role of the buyer; buying inspiration; suppliers and sourcing; range and merchandise

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Chapitres de livres sur le sujet "AI throughput"

Hamidon, Munirah Hayati, and Tofael Ahamed. "High-Throughput Plant Phenotyping Techniques in Controlled Environments." In IoT and AI in Agriculture. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1263-2_11.

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Parveen, Shugufta, Sajad Un Nabi, Zarka Nabi, et al. "High-throughput Phenomics and AI in Plant Disease Diagnosis." In Conventional to Emerging Advances in Plant Disease Diagnosis and Pathogen Detection. CRC Press, 2025. https://doi.org/10.1201/9781003474036-13.

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Bonfietti, Alessio, Michele Lombardi, Michela Milano, and Luca Benini. "Throughput Constraint for Synchronous Data Flow Graphs." In Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01929-6_4.

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Rusakov, Victor A. "On the Regularity of the Bias of Throughput Estimates on Traffic Averaging." In Brain-Inspired Cognitive Architectures for Artificial Intelligence: BICA*AI 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65596-9_51.

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Ghodasara, Raj, Hitesh Vora, and Aniket Nargundkar. "Reduction of Throughput Time in Digital Publishing Using AI-Based Smart Systems." In Intelligent Strategies for ICT. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1260-1_17.

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Zhiri, Mohamed Amine, Hana Krichene, Chiara Sandionigi, and Sébastien Pillement. "HT-NoC: Reconfigurable High Throughput Network-on-Chip for AI Dataflow Accelerators." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-87995-1_2.

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Bhulania, Paurush, M. R.Tripathy, and Ayoub Khan. "High-Throughput and Low-Latency Reconfigurable Routing Topology for Fast AI MPSoC Architecture." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3067-5_48.

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Cao, Lu, Verena Schwach, and Fons Verbeek. "A Survey of AI Utilisation in High-Throughput Screening Systems Using Stem Cell Models." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65522-7_51.

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Bondani, Isabella, Gianluca Bacchiega, and Robert Radu. "Developing an Automated Microfluidic Platform for High-Throughput Cell Screening of Chemical Sensitivities Using AI-Based Image Analysis." In Ambient Assisted Living. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63913-5_18.

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Blanco-Filgueira, Beatriz, Tamara Delgado, Andrea Gregores Coto, et al. "Synthetic Data for AI-Powered Ultrafast Laser Based Micro-structuring Method Description." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-86489-6_6.

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Abstract High-power ultrashort pulse lasers (USPLs) represent a sustainable alternative for industrial surface processing. Laser Surface Texturing (LST) allows modification of surface properties such as mechanical, chemical or optical properties. The adoption of USPLs in industry will enable the surface functionalization of large 3D parts through the LST process. However, a real exploitation of USPLs still faces limitations related to high processing resolution, quality, productivity, and the need for expert knowledge in laser micro-structuring strategies. It is crucial to increase maturity, r

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Actes de conférences sur le sujet "AI throughput"

Hirata-Miyasaki, Eduardo, Soorya Pradeep, Ziwen Liu, et al. "Mapping cell state dynamics with AI-enabled live cell imaging." In High-Throughput Biophotonics: Imaging, Spectroscopy, and Beyond X, edited by Keisuke Goda and Kevin K. Tsia. SPIE, 2025. https://doi.org/10.1117/12.3051857.

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Alexandropoulos, I., V. Rentoula, D. Fragkos, N. Gkatzios, and H. Koumaras. "An AI-Assisted User-Intent 6G System for Dynamic Throughput Provision." In 2024 IEEE 29th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). IEEE, 2024. https://doi.org/10.1109/camad62243.2024.10942858.

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Nassar, Ali W., Hesham ALy, and Hesham M. ElBadawy. "Cell Throughput Prediction Using AI Models: Insights from the O-RAN Framework." In 2024 6th Novel Intelligent and Leading Emerging Sciences Conference (NILES). IEEE, 2024. http://dx.doi.org/10.1109/niles63360.2024.10753234.

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Zhou, Peifang, Bachir Berkane, Vlad Druz, and Mark Rollins. "A High-Throughput Implementation of the MUSIC Algorithm Using AMD Versal AI Engine." In 2025 IEEE 33rd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). IEEE, 2025. https://doi.org/10.1109/fccm62733.2025.00051.

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B, Pabitha, Vani V, and Shridhar Sanshi. "Performance Evaluation of Wireless Health and Remote Monitoring Network Throughput Under Varying Conditions Using NetSim." In 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit). IEEE, 2024. https://doi.org/10.1109/globalaisummit62156.2024.10947878.

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Padmanabhan, Viswa N., Devarapalli Sai Phani Deekshitha, and Mabel Nirmala Joseph. "AI-Driven Plant Classification and Cultivation Optimization using High-Throughput Image Acquisition for Plant Phenotyping." In 2025 7th International Conference on Inventive Material Science and Applications (ICIMA). IEEE, 2025. https://doi.org/10.1109/icima64861.2025.11073966.

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Balaji, S. Muthu, B. Chandana, Vaseem Ahmed Qureshi, and S. Naga Jyothi. "Designing and Developing a Dependable and High-Throughput Model with Enhanced DNN Using ABC Algorithm." In 2024 1st International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI). IEEE, 2024. https://doi.org/10.1109/icscai61790.2024.10866096.

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Reddy, Uma, Yagateela Pandu Rangaiah, Amandeep Nagpal, Himanshu Rai Goyal, Mandapati Venkata Rama Sundari, and K. Adnan. "Enabling Rapid Data Transfer in Medical IoT Systems with a High-Throughput PRESENT Cipher Hardware Framework." In 2024 1st International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI). IEEE, 2024. https://doi.org/10.1109/icscai61790.2024.10866677.

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Sahni, Subal, Ankur Aggarwal, Nadav Bergstein, et al. "Photonic Fabric for Memory and Compute Disaggregation." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.w3d.1.

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Photonic Fabric Appliance offers a pathway to bypass the bounded memory to compute ratio found in commercially available GPUs, offering improvements in throughput, energy efficiency and latency, laying the foundation for future-proof AI hardware.

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Komoda, K., P. Jiang, H. Han, et al. "Hybrid-AI Grasp Planning System that Integrates Rule-Based and DNN-Based Methods for Throughput Improvement of Picking Robots." In 2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2024. http://dx.doi.org/10.1109/aim55361.2024.10636988.

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Rapports d'organisations sur le sujet "AI throughput"

Skolnick, Jeffrey, Mu Gao, Ada Sedova, Jerry Parks, and Jianlin Cheng. High throughput, accurate gene annotation through AI and HPC-enabled structural analysis. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2222578.

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Mauel, Michael, James Andreson, and Jeffry Levesque. Final Report: Developing ML/AI Methods for High-Throughput Characterization of Multiple-Sensor Streams of Tokamak Dynamics for High-Speed Control. Office of Scientific and Technical Information (OSTI), 2025. https://doi.org/10.2172/2520504.

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Tabassi, Elham. AI Risk Management Framework. National Institute of Standards and Technology, 2023. http://dx.doi.org/10.6028/nist.ai.100-1.

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As directed by the National Artificial Intelligence Initiative Act of 2020 (P.L. 116-283), the goal of the AI RMF is to offer a resource to the organizations designing, developing, deploying, or using AI systems to help manage the many risks of AI and promote trustworthy and responsible development and use of AI systems. The Framework is intended to be voluntary, rights-preserving, non-sector specific, and use-case agnostic, providing flexibility to organizations of all sizes and in all sectors and throughout society to implement the approaches in the Framework. The AI RMF is intended to be pr

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Rochelle, Jeremy. Review of Guidance from Seven States on AI in Education. Digital Promise, 2024. http://dx.doi.org/10.51388/20.500.12265/204.

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As Artificial Intelligence within education becomes increasingly important, Digital Promise reviewed the guidance documents released by seven states—California, North Carolina, Ohio, Oregon, Virginia, Washington state, and West Virginia—on how to approach artificial intelligence (AI) in education. Throughout this report we summarize the overall themes and considerations that each guidance document covers.

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Perk, Shimon, Maricarmen Garcia, Alexander Panshin, et al. Avian Influenza Virus H9N2: Characterization and Control Strategies. United States Department of Agriculture, 2007. http://dx.doi.org/10.32747/2007.7709882.bard.

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Control of Avian Influenza (AI) infection is a highly topical subject of major economicimportance for the worldwide poultry industry at the national level and for international trade.H9N2 viruses are endemic in poultry throughout Asia and the Middle East, causing major losses inproduction. Moreover, these viruses pose wider threats since they have been isolated from bothswine and humans. At the same time, study of the AI viruses affords an opportunity to explore anumber of problems of intriguing scientific interest. The overall goal of this project was to developa sound control strategy for av

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bin Ahsan, Wahid. Designing a Sustainable Future: Insights from Don Norman at Userhub Reunion 2023. Userhub, 2023. http://dx.doi.org/10.58947/bsnf-dmpl.

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This report summarizes the discussion session featuring renowned design expert Don Norman and moderated by Wahid bin Ahsan during the Userhub Reunion 2023 event in Dhaka, Bangladesh. The dialogue focused on the evolving landscape of design and the responsibility of designers in creating a better world. Key topics included the circular economy, plastic waste reduction, noise pollution, sustainable agriculture, ethical design considerations for digital products, and the influence of AI on the design industry. Don Norman stressed the importance of a holistic approach that considers ecological sys

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Burstein, Jill, Geoffrey LaFlair, Antony Kunnan, and Alina von Davier. A Theoretical Assessment Ecosystem for a Digital-First Assessment - The Duolingo English Test. Duolingo, 2022. http://dx.doi.org/10.46999/kiqf4328.

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The Duolingo English Test is a groundbreaking, digitalfirst, computeradaptive measure of English language proficiency for communication and use in Englishmedium settings. The test measures four key English language proficiency constructs: Speaking, Writing, Reading, and Listening (SWRL), and is aligned with the Common European Framework of Reference for Languages (CEFR) proficiency levels and descriptors. As a digitalfirst assessment, the test uses “humanintheloop AI” from end to end for test security, automated item generation, and scoring of testtaker responses. This paper presents a

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Goodwin, Sarah, Yigal Attali, Geoffrey LaFlair, et al. Duolingo English Test - Writing Construct. Duolingo, 2023. http://dx.doi.org/10.46999/arxn5612.

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Assessments, especially those used for high-stakes decision making, draw on evidence-based frameworks. Such frameworks inform every aspect of the testing process, from development to results reporting. The frameworks that language assessment professionals use draw on theory in language learning, assessment design, and measurement and psychometrics in order to provide underpinnings for the evaluation of language skills including speaking, writing, reading, and listening. This paper focuses on the construct, or underlying trait, of writing ability. The paper conceptualizes the writing construct

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Ramirez Rufino, Smeldy, Manuel Rodriguez Porcel, and Orlando Perez Richiez. Drones in Construction: Unpacking the Value that Drone Technologies Bring to the Construction Sector Across Latin America. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0004748.

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The use of drone technology in capital projects is an emerging area that holds promise for growth. Drones are becoming more widely available, and regulatory bodies are gradually allowing their use on a larger scale. With the development of software solutions that can effectively utilize data, drones are increasingly being used throughout the entire lifecycle of capital projects, including smaller infrastructure projects. The benefits of using drones in construction projects are numerous and include providing an unparalleled record of all activities, reducing planning and survey costs, increasi

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Sayers, Dave, Rui Sousa-Silva, Sviatlana Höhn, et al. The Dawn of the Human-Machine Era: A forecast of new and emerging language technologies. Open Science Centre, University of Jyväskylä, 2021. http://dx.doi.org/10.17011/jyx/reports/20210518/1.

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New language technologies are coming, thanks to the huge and competing private investment fuelling rapid progress; we can either understand and foresee their effects, or be taken by surprise and spend our time trying to catch up. This report scketches out some transformative new technologies that are likely to fundamentally change our use of language. Some of these may feel unrealistically futuristic or far-fetched, but a central purpose of this report - and the wider LITHME network - is to illustrate that these are mostly just the logical development and maturation of technologies currently i

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