Relevant bibliographies by topics / AI fabric

Contents

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

Academic literature on the topic 'AI fabric'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "AI fabric"

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Derek Asir Muthurajan Caleb. "AI-Driven Smart Fabric Provisioning: Transforming Network Automation through Intelligent Orchestration and Dynamic Testing." Journal of Computer Science and Technology Studies 7, no. 3 (2025): 783–90. https://doi.org/10.32996/jcsts.2025.7.3.85.

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The evolution of modern data centers demands innovative approaches to fabric provisioning, particularly when integrating new switches, hosts, and storage into existing infrastructures. This article introduces a Smart Fabric Provisioning solution powered by Agentic AI that transforms traditional manual processes into automated, intelligent workflows. By creating dynamic full-mesh fabrics with simulated environments, the solution addresses critical challenges in solution qualification and resource utilization during proof-of-concept phases. The AI-driven approach enables logical link manipulatio
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D, Sujatha. "AI Based Fabric Inspection System." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 4866–69. https://doi.org/10.22214/ijraset.2025.71305.

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Textile industry continues to face challenges in ensuring consistent fabric quality due to its reliance on manual inspection processes. This study introduces an AI-driven automated fabric inspection system designed to detect surface defects in real time using deep learning and computer vision techniques. The system is built around a Raspberry Pi 5 platform integrated with TensorFlow and a Pi Camera module. A convolutional neural network (CNN) model processes captured images to identify defects, prompting the system to halt fabric movement and activate a pump-based liquid applicator for marking
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Siva Prasad Nandi. "Serverless databases: Architectural evolution, implementation strategies, and future directions in cloud-native data management." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 567–74. https://doi.org/10.30574/wjarr.2025.26.2.1591.

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The evolution of modern data centers demands innovative approaches to fabric provisioning, particularly when integrating new switches, hosts, and storage into existing infrastructures. This article introduces a Smart Fabric Provisioning solution powered by Agentic AI that transforms traditional manual processes into automated, intelligent workflows. By creating dynamic full-mesh fabrics with simulated environments, the solution addresses critical challenges in solution qualification and resource utilization during proof-of-concept phases. The AI-driven approach enables logical link manipulatio
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Petrak, Slavenka, Maja Mahnić Naglić, Martina Glogar, and Antoneta Tomljenović. "Assessment of Textile Material Properties and the Impact of Digital Ink-Jet Fabric Printing on 3D Simulation as a Sustainable Method for Garment Prototyping." Sustainability 17, no. 4 (2025): 1388. https://doi.org/10.3390/su17041388.

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In the context of sustainable fashion, this paper presents research on the impact of property assessment methods of textile materials and pigment digital printing on the mechanical properties of fabrics and their 3D simulation in the development of digital prototypes for clothing design. Six woven fabrics, with and without a textile ink-jet print, were tested using a KES-FB measuring system and digitized using SEDDI Textura AI technology. The determined mechanical parameters were used for 3D draping simulations based on Cusick Drape Meter method, as well as for the simulation of frilly women’s
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Tu, Yi-Fan, Mei-Ying Kwan, and Kit-Lun Yick. "A Systematic Review of AI-Driven Prediction of Fabric Properties and Handfeel." Materials 17, no. 20 (2024): 5009. http://dx.doi.org/10.3390/ma17205009.

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Artificial intelligence (AI) is revolutionizing the textile industry by improving the prediction of fabric properties and handfeel, which are essential for assessing textile quality and performance. However, the practical application and translation of AI-predicted results into real-world textile production remain unclear, posing challenges for widespread adoption. This paper systematically reviews AI-driven techniques for predicting these characteristics by focusing on model mechanisms, dataset diversity, and prediction accuracy. Among 899 papers initially identified, 39 were selected for in-
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Sandhya, NC, Nihal Mathew Sashikumar, M. Priyanka, Sebastian Maria Wenisch, and Kunaraj Kumarasamy. "Automated Fabric Defect Detection and Classification: A Deep Learning Approach." Textile & Leather Review 4 (December 14, 2021): 315–35. http://dx.doi.org/10.31881/tlr.2021.24.

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A computer-based intelligent visual inspection system plays a major role in evaluating the quality of textile fabrics and its demand is continuously increasing in the textile industry, especially when the quality of textile is to be considered. In this paper, we propose an AI-based automated fabric defect detection algorithm which utilizes pre-trained deep neural network models for classifying possible fabric defects. The fabric images are enhanced by pre-processing at various levels using conventional image processing techniques and they are used to train the networks. The Deep Convolutional
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Ms Shital K Dhamal, Dr Chandani Joshi, Dr D.S Chouhan. "Fabric Defect Analysis In Textile Manufacturing: Evaluating Methods For Generic And Jacquard Fabrics." Tuijin Jishu/Journal of Propulsion Technology 44, no. 3 (2023): 3534–41. http://dx.doi.org/10.52783/tjjpt.v44.i3.2064.

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Regarding maintaining product quality and satisfying customer expectations, fabric defect analysis is vital in textile manufacturing. This research provides a comprehensive assessment of many techniques used for analyzing and pinpointing flaws in standard and Jacquard textiles. This study considers machine vision systems and AI-based algorithms as two examples of cutting-edge automation alongside more conventional human inspection procedures. Manual inspection techniques are extensively reviewed in the first section, with particular emphasis on these techniques' inherent subjectivity and resou
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Li, Yun Feng, Li Qian Huang, and Jian Yong Yu. "Study on the Pore Structure of Cotton-Like Polyester Knitted Fabrics." Advanced Materials Research 821-822 (September 2013): 270–73. http://dx.doi.org/10.4028/www.scientific.net/amr.821-822.270.

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Porous structure of fabric has a significant impact on the fabric functions such as air permeability, water transport and heat retention. In this article, six knitted fabrics with different blend ratio of cotton-like modified polyester fiber and cotton fiber were prepared. Pore sizes and its distribution of the fabrics were measured by CFP-1100-AI pore diameter tester. Porosity of the fabrics was obtained by three ways respectively, namely loop model method, image method and density method. The results show that the pore diameter of blended knitted fabrics presents an asymmetric distribution,
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Mahnić Naglić, Maja, Slavenka Petrak, and Antoneta Tomljenović. "Analysis of Woven Fabric Mechanical Properties in the Context of Sustainable Clothing Development Process." Polymers 17, no. 15 (2025): 2013. https://doi.org/10.3390/polym17152013.

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This paper presents research in the field of computer-aided 3D clothing design, focusing on an investigation of three methods for determining the mechanical properties of woven fabrics and their impact on 3D clothing simulations in the context of sustainable apparel development. Five mechanical parameters were analyzed: tensile elongation in the warp and weft directions, shear stiffness, bending stiffness, specific weight, and fabric thickness. These parameters were integrated into the CLO3D CAD software v.2025.0.408, using data obtained via the KES-FB system, the Fabric Kit protocol, and the
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Oluwatosin Oladayo Aramide. "Architecting highly resilient AI Fabrics: A Blueprint for Next-Gen Data Centers." World Journal of Advanced Engineering Technology and Sciences 8, no. 1 (2023): 529–39. https://doi.org/10.30574/wjaets.2023.8.1.0049.

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The fast-growing advancement in AI technologies has resulted in huge loads on the data center architecture resulting in the need to create extremely resistant, and fault-tolerant AI fabrics. This paper looks at AI design principles and technologies necessitated in the construction of fault-tolerant AI infrastructures that can support complex, data-heavy workloads. The major technologies of VXLAN EVPN, RDMA and ultra-low latency interconnect like RoCEv2, NV Link and PCIe Gen5 are paramount to high availability, low latency and high throughput. This article reviews industrial best practice by ob
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Dissertations / Theses on the topic "AI fabric"

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TASI-YA-TING and 蔡雅婷. "The Transformation of Fabric Art in Atayal Aborigines—The Field Survey on Ren-ai Village of Nantou County." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/23607341169481413242.

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碩士<br>大葉大學<br>造形藝術學系碩士班<br>96<br>The traditional weaving of Atayal plays an important role in the aboriginal weaving culture, and also valuable resource on developing tribal characters. The fact that weaving activity has been very popular until present, results from promotion and teaching of the craft in tribes. Government has strongly promoted aboriginal weaving crafts, and imported braiders for table use or braiders stand in these years. This not only results in the spread of this work, but also the downfall of the traditional weaving skills. The evolvement of this handcraft in Atayal is a n
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PIZZO, Federica. "Estensione della definizione di Malattia di Fabry in base ai dati ottenuti dallo studio dell'attività enzimatica e degli aplotipi genetici." Doctoral thesis, 2011. http://hdl.handle.net/10447/95123.

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Books on the topic "AI fabric"

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Hechler, Eberhard, Maryela Weihrauch, and Yan Wu. Data Fabric and Data Mesh Approaches with AI. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9253-2.

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Roidi, Vittorio. La fabbrica delle notizie: Piccola guida ai quotidiani italiani. Laterza, 2001.

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Loreti, Leon Lorenzo. Ceramiche artistiche Molaroni: Storia della fabbrica dal 1880 ai giorni nostri. Mariotti, 1998.

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Horiuchi, Izuho. Kasuri: Ai to shiro no orinasu sekai = Kasuri. Horiuchi Izuho, 1988.

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Nurchis, Federica. Alberto Martini (1931-1965): Da Longhi ai Maestri del colore. Ledizioni, 2016.

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Zhaoxia, Guo, and Leung Yung-sun, eds. Optimizing decision making in the apparel supply chain using artificial intelligence (AI): From production to retail. Woodhead Publishing Ltd, 2013.

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Badesi, Licia. La Camera del lavoro di Como: Dai CLN aziendali ai consigli unitari di fabbrica 1945-1970. Nuoveparole, 2000.

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Carrisi, Giuseppe. La fabbrica delle prostitute: Un viaggio nel mercato criminale del sesso, dai villaggi della Nigeria ai marciapiedi italiani. Newton Compton, 2011.

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Lorenzi, Nello. Lettere ai familiari (1913-1917): Epistolario di un giovane soldato valdarnese. (a cura di Carlo Fabbri e Dante Priore). Comuni di Pian Di Sco' e Terranuova Bracciolini, 1996.

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Silvia, Paoli, Mangano Tancredi, Agostini Giampietro, Giusti Francesco, and Castello sforzesco, eds. Ex fabrica: Identità e mutamenti ai confini della metropoli : Giampietro Agostini, Francesco Giusti, Tancredi Mangano : nuove acquisizioni del Civico archivio fotografico di Milano. Silvana, 2006.

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Book chapters on the topic "AI fabric"

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Hechler, Eberhard, Maryela Weihrauch, and Yan Wu. "Data Fabric Architecture Patterns." In Data Fabric and Data Mesh Approaches with AI. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9253-2_10.

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Hechler, Eberhard, Maryela Weihrauch, and Yan Wu. "AI for Entity Resolution." In Data Fabric and Data Mesh Approaches with AI. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9253-2_8.

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Molchanov, Pavlo A. "Artificial Intelligence in Vision Systems: AI Fabric." In Artificial Insect-Inspired Vision for Autonomous Systems. River Publishers, 2025. https://doi.org/10.1201/9788770047074-6.

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Hechler, Eberhard, Maryela Weihrauch, and Yan Wu. "Data Fabric Within an Enterprise Architecture." In Data Fabric and Data Mesh Approaches with AI. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9253-2_11.

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Hechler, Eberhard, Maryela Weihrauch, and Yan Wu. "Terminology: Data Fabric and Data Mesh." In Data Fabric and Data Mesh Approaches with AI. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9253-2_2.

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Tong, Shuo, and Han Liu. "MFAR-VTON: Multi-scale Fabric Adaptive Registration for Image-Based Virtual Try-On." In AI-generated Content. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-7587-7_12.

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Hechler, Eberhard, Maryela Weihrauch, and Yan Wu. "Data Fabric and Data Mesh Research Areas." In Data Fabric and Data Mesh Approaches with AI. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9253-2_17.

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Hechler, Eberhard, Maryela Weihrauch, and Yan Wu. "Key Data Fabric and Data Mesh Capabilities." In Data Fabric and Data Mesh Approaches with AI. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9253-2_5.

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Hechler, Eberhard, Maryela Weihrauch, and Yan Wu. "Data Fabric and Data Mesh Business Benefits." In Data Fabric and Data Mesh Approaches with AI. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9253-2_4.

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Hechler, Eberhard, Maryela Weihrauch, and Yan Wu. "Automated Data Fabric and Data Mesh Aspects." In Data Fabric and Data Mesh Approaches with AI. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9253-2_14.

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Conference papers on the topic "AI fabric"

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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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Quinnell, Eric. "Tesla Transport Protocol Over Ethernet (TTPoE): A New Lossy, Exa-Scale Fabric for the Dojo AI Supercomputer." In 2024 IEEE Hot Chips 36 Symposium (HCS). IEEE, 2024. http://dx.doi.org/10.1109/hcs61935.2024.10664947.

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Bhargava, Pavan, Sidney Buchbinder, Ðorđe Gluhović, et al. "A UCIe Optical I/O Retimer Chiplet for AI Scale-up Fabrics." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.th4b.3.

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We demonstrate a UCIe Optical I/O Retimer for scale-up AI fabrics. It achieves 1.024Tbps of bidirectional bandwidth per optical port from one package to another, delivering an aggregate bandwidth of 8.192Tbps.
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Verdone, Chiara, Matteo Gravina, Grazia Casavecchia, Rodolfo Belfiore, and Benedetta Di Millo. "Explainable AI Approach for Cardiac Involvement Detection in Anderson-Fabry Disease." In 14th International Conference on Data Science, Technology and Applications. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013653700003967.

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Sugumari, G., and Narsimhulu Dunna. "Numerical study on heat conduction model for multi-layered heat resistant thermal protection fabric." In AI POWERED TECHNOLOGY INTEGRATION FOR SUSTAINABILITY (AI-PTIS-2024). AIP Publishing, 2025. https://doi.org/10.1063/5.0279459.

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Michalski, Marek. "Switching Fabric Control with AI and ML Support." In 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 2024. http://dx.doi.org/10.1109/percomworkshops59983.2024.10503100.

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Long, Audrey, Daniel Choi, and Joel Coffman. "Using Amazon Managed Blockchain for ePHI An Analysis of Hyperledger Fabric and Ethereum." In 2022 IEEE World AI IoT Congress (AIIoT). IEEE, 2022. http://dx.doi.org/10.1109/aiiot54504.2022.9817198.

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Kim, Young Woo, and Myeong-Hoon Oh. "Performance Evaluation of Fabric-Attached Memory Pool for AI Applications." In 2021 International Conference on Electronics, Information, and Communication (ICEIC). IEEE, 2021. http://dx.doi.org/10.1109/iceic51217.2021.9369733.

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"Keynote Talk: Rethinking Network Fabric Architectures for Distributed AI/ML Platforms." In 2024 17th IEEE/ACM International Workshop on Network on Chip Architectures (NoCArc). IEEE, 2024. http://dx.doi.org/10.1109/nocarc64615.2024.10749926.

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Chen, Yixin, Wenying Qiu, Xiaohao Wang, and Min Zhang. "Tactile Rendering of Fabric Textures Based on Texture Recognition." In 2019 IEEE 2nd International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS). IEEE, 2019. http://dx.doi.org/10.1109/nsens49395.2019.9293989.

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