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Статті в журналах з теми "Multi-scale architecture"
Gao, Shang-Hua, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, and Philip Torr. "Res2Net: A New Multi-Scale Backbone Architecture." IEEE Transactions on Pattern Analysis and Machine Intelligence 43, no. 2 (February 1, 2021): 652–62. http://dx.doi.org/10.1109/tpami.2019.2938758.
Повний текст джерелаJayashankar, Vaishali, Irina A. Mueller, and Susanne M. Rafelski. "Shaping the multi-scale architecture of mitochondria." Current Opinion in Cell Biology 38 (February 2016): 45–51. http://dx.doi.org/10.1016/j.ceb.2016.02.006.
Повний текст джерелаKnolle, Moritz, Georgios Kaissis, Friederike Jungmann, Sebastian Ziegelmayer, Daniel Sasse, Marcus Makowski, Daniel Rueckert, and Rickmer Braren. "Efficient, high-performance semantic segmentation using multi-scale feature extraction." PLOS ONE 16, no. 8 (August 19, 2021): e0255397. http://dx.doi.org/10.1371/journal.pone.0255397.
Повний текст джерелаAkinniyi, Oluwatunmise, Md Mahmudur Rahman, Harpal Singh Sandhu, Ayman El-Baz, and Fahmi Khalifa. "Multi-Stage Classification of Retinal OCT Using Multi-Scale Ensemble Deep Architecture." Bioengineering 10, no. 7 (July 10, 2023): 823. http://dx.doi.org/10.3390/bioengineering10070823.
Повний текст джерелаReyes, J. A., and E. M. Stoudenmire. "Multi-scale tensor network architecture for machine learning." Machine Learning: Science and Technology 2, no. 3 (July 14, 2021): 035036. http://dx.doi.org/10.1088/2632-2153/abffe8.
Повний текст джерелаYang, Lintao, Pietro Liò, Xu Shen, Yuyang Zhang, and Chengbin Peng. "Adaptive multi-scale Graph Neural Architecture Search framework." Neurocomputing 599 (September 2024): 128094. http://dx.doi.org/10.1016/j.neucom.2024.128094.
Повний текст джерелаChuen, Alvin Lim Fang, Khoh Wee How, Pang Ying Han, and Yap Hui Yen. "In-Air Hand Gesture Signature Recognition Using Multi-Scale Convolutional Neural Networks." JOIV : International Journal on Informatics Visualization 7, no. 3-2 (November 30, 2023): 2025. http://dx.doi.org/10.30630/joiv.7.3-2.2359.
Повний текст джерелаLi, Bo, Guofeng Zhou, Wei Ge, Limin Wang, Xiaowei Wang, Li Guo, and Jinghai Li. "A multi-scale architecture for multi-scale simulation and its application to gas–solid flows." Particuology 15 (August 2014): 160–69. http://dx.doi.org/10.1016/j.partic.2013.07.004.
Повний текст джерелаShi, Lu, Xu Chen, Yuqian Xu, Xing Gao, Jialong Lai, and Shusheng Wang. "Towards an Effective Architectural Form: The Composition of Squareness and Roundness Based on Scale Proportion—Evidence from the Yingxian Wooden Pagoda." Buildings 14, no. 5 (May 18, 2024): 1472. http://dx.doi.org/10.3390/buildings14051472.
Повний текст джерелаAlotaibi, Hatim, Masoud Jabbari, Chamil Abeykoon, and Constantinos Soutis. "Numerical Investigation of Multi-scale Characteristics of Single and Multi-layered Woven Structures." Applied Composite Materials 29, no. 1 (January 24, 2022): 405–21. http://dx.doi.org/10.1007/s10443-022-10010-x.
Повний текст джерелаДисертації з теми "Multi-scale architecture"
Olivares, Chauvet Pedro. "Multi-scale analysis of chromosome and nuclear architecture." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/multiscale-analysis-of-chromosome-and-nuclear-architecture(32a7b634-035b-4c6b-83f9-735f83bc73fb).html.
Повний текст джерелаJavalera, Rincón Valeria. "Distributed large scale systems : a multi-agent RL-MPC architecture." Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/393922.
Повний текст джерелаEsta tesis describe una metodología para hacer frente a la interacción entre controladores MPC en una arquitectura MPC distribuida. Este enfoque combina las ideas de Inteligencia Artificial Distribuida (DIA) y aprendizaje por refuerzo (RL) con el fin de proporcionar una interacción entre controladores basado en agentes de cooperativos y técnicas de aprendizaje. El objetivo de esta metodología es proporcionar una estructura general para llevar a cabo un control óptimo en entornos de redes distribuidas, donde se encuentran varias dependencias entre subsistemas. Esas dependencias o conexiones corresponden a menudo a variables de control. En ese caso, el control distribuido tiene que ser coherente en ambos subsistemas. Uno de los principales conceptos novedosos de esta arquitectura es el agente negociador. Los agentes negociadores actúan junto con agentes MPC para determinar el valor óptimo de las variables de control compartidas de forma cooperativa utilizando técnicas de aprendizaje (RL). El valor óptimo de esas variables compartidas debe lograr un objetivo común, probablemente diferente de los objetivos específicos de cada agente que está compartiendo la variable. Se consideran dos casos de estudio, en el que la arquitectura propuesta se ha aplicado y probado, una pequeña red de distribución de agua y la red de agua de Barcelona. Los resultados sugieren que este enfoque es una estrategia prometedora cuando el control centralizado no es una opción razonable.
Zhu, Weirong. "Efficient synchronization for a large-scale multi-core chip architecture." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 206 p, 2007. http://proquest.umi.com/pqdweb?did=1362532791&sid=27&Fmt=2&clientId=8331&RQT=309&VName=PQD.
Повний текст джерелаSoler, Vila Paula 1989. "Multi-scale study of the genome architecture and its dynamical facets." Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/668229.
Повний текст джерелаEl desarrollo de métodos experimentales basados en la captura de la conformación cromosómica (3C) ha permitido tener una visión más detallada de la arquitectura genómica. El Hi-C, derivado del 3C, se ha convertido en una técnica de referencia para analizar la estructura tridimensional de la cromatina, así como su relación con el estado funcional celular. Sin embargo, varios aspectos del análisis y la interpretación de los datos de Hi-C siguen siendo un desafío, y pueden ocultar un potencial aún por descubrir. En esta tesis se exploran múltiples niveles de organización estructural de la cromatina. Hemos realizado un estudio integrativo combinando datos de in situ Hi-C con nueve capas epigenéticas y hemos revelado un nuevo compartimento genómico caracterizado por su dinámica y capacidad de transición, enriquecido en cromatina reprimida por polycomb. Este nuevo compartimento intermedio juega un papel importante en la modulación del genoma durante la diferenciación de células B y durante su transformación neoplásica, específicamente en pacientes con leucemia linfocítica crónica (CLL) o con linfoma de células del manto (MCL). Además, hemos desarrollado TADpole, un nuevo método computacional destinado a la detección de la jerarquía de dominios asociados topológicamente (TADs) empleando mapas de interacciones de Hi-C. Hemos demostrado su robustez ante una evaluación técnica y biológica, así como su capacidad de detectar diferencias topológicas en experimentos de capture Hi-C de alta resolución.
Sclaroff, Stanley Edward. "Deformable solids and displacement maps--a multi-scale technique for model recovery and recognition." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/70198.
Повний текст джерелаDuro, Royo Jorge. "Towards Fabrication Information Modeling (FIM) : workflow and methods for multi-scale trans-disciplinary informed design." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101843.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (pages 67-70).
This thesis sets the stage for Fabrication Information Modeling (FIM); a design approach for enabling seamless design-to-production workflows that can derive complex designs fusing advanced digital design technologies associated with analysis, engineering and manufacturing. Present day digital fabrication platforms enable the design and construction of high-resolution and complex material distribution structures. However, virtual-to-physical workflows and their associated software environments are yet to incorporate such capabilities. As preliminary methods towards FIM I have developed four computational strategies for the design and digital construction of custom systems. These methods are presented in this thesis in the context of specific design challenges and include a biologically driven fiber construction algorithm; an anatomically driven shell-to-wearable translation protocol; an environmentally-driven swarm printing system; and a manufacturing-driven hierarchical fabrication platform. I discuss and analyze these four challenges in terms of their capabilities to integrate design across media, disciplines and scales through the concepts of multidimensionality, media-informed computation and trans-disciplinary data in advanced digital design workflows. With FIM I aim to contribute to the field of digital design and fabrication by enabling feedback workflows where materials are designed rather than selected; where the question of how information is passed across spatiotemporal scales is central to design generation itself; where modeling at each level of resolution and representation is based on various methods and carried out by various media or agents within a single environment; and finally, where virtual and physical considerations coexist as equals.
by Jorge Duro Royo.
S.M.
Krüger, Martin Wolfgang [Verfasser]. "Personalized Multi-Scale Modeling of the Atria: Heterogeneities, Fiber Architecture, Hemodialysis and Ablation Therapy / Martin Wolfgang Krüger." Karlsruhe : KIT Scientific Publishing, 2013. http://www.ksp.kit.edu.
Повний текст джерелаDeserranno, Dimitri. "A Multi-Scale Finite Element Model of the Cardiac Ventricles." Case Western Reserve University School of Graduate Studies / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=case1148984314.
Повний текст джерелаHardy, Clément. "Architectures multi-échelles de type encοdeur-décοdeur pοur la stéréοphοtοmétrie". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMC222.
Повний текст джерелаPhotometric stereo is a technique for 3D surface reconstruction of objects. This field has seen a surge in research interest due to its potential applications in industry. Specifically, photometric stereo can be employed for tasks such as detecting machining defects in mechanical components or facial recognition. This thesis delves into deep learning methods for photometry stero, with a particular focus on training data and network architectures.While neural network over-parameterization is often adequate, the training dataset plays a pivotal role in task adaptation. To generate a highly diverse and extensible training set, we propose a new synthetic dataset. This dataset incorporates a broad spectrum of geometric, textural, lighting, and environmental variations, allowing for the creation of nearly infinite training instances.The second decisive point of a good reconstruction concerns the choice of architecture. The architecture of a network must ensure a good generalization capacity on new data to generate very good results on unseen data. And this, regardless of the application. In particular, for the photometric stereo problem, the challenge is to be able to reconstruct very high-resolution images in order not to lose any details. We therefore propose a multi-scale encoder-decoder architecture to address this problem.We first introduce a convolutional neural network architecture for calibrated photometric stereo, where the lighting direction is known. To handle unconstrained environments, we propose a Transformers-based approach for universal photometric stereo. Lastly, for challenging materials shiny like translucent or shiny surfaces, we introduce a ``weakly calibrated'' approach that assumes only approximate knowledge of the lighting direction.The approaches we have investigated have consistently demonstrated strong performance on standard benchmarks, as evidenced by both quantitative metrics and visual assessments. Our results, particularly the improved accuracy of reconstructed normal maps, represent a significant advancement in photometric stereo
Stephan, André. "Towards a comprehensive energy assessment of residential buildings: a multi-scale life cycle energy analysis framework." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209465.
Повний текст джерелаHowever, most current building energy assessments focus solely on operational energy overlooking other energy uses such as embodied and transport energy. Embodied energy comprises the energy requirements for building materials production, construction and replacement. Transport energy represents the amount of energy required for the mobility of building users.
Decisions based on partial assessments might result in an increased energy demand during other life cycle stages or at different scales of the built environment. Recent studies have shown that embodied and transport energy demands often account for more than half of the total lifecycle energy demand of residential buildings. Current assessment tools and policies therefore overlook more than 50% of the life cycle energy use.
This thesis presents a comprehensive life cycle energy analysis framework for residential buildings. This framework takes into account energy requirements at the building scale, i.e. the embodied and operational energy demands, and at the city scale, i.e. the embodied energy of nearby infrastructures and the transport energy of its users. This framework is implemented through the development, verification and validation of an advanced software tool which allows the rapid analysis of the life cycle energy demand of residential buildings and districts. Two case studies, located in Brussels, Belgium and Melbourne, Australia, are used to investigate the potential of the developed framework.
Results show that each of the embodied, operational and transport energy requirements represent a significant share of the total energy requirements and associated greenhouse gas emissions of a residential building, over its useful life. The use of the developed tool will allow building designers, town planners and policy makers to reduce the energy demand and greenhouse gas emissions of residential buildings by selecting measures that result in overall savings. This will ultimately contribute to reducing the environmental impact of the built environment.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
Книги з теми "Multi-scale architecture"
Docker and Kubernetes for Java Developers: Scale, deploy, and monitor multi-container applications. Packt Publishing, 2017.
Знайти повний текст джерелаSingapore's Building Stock: Approaches to a Multi-Scale Documentation and Analysis of Transformations Including Recommendations for Future-Oriented Administration. Hirmer Verlag GmbH, 2016.
Знайти повний текст джерелаHaaland, Randi, and Gunnar Haaland. Prehistoric Figurines in Sudan. Edited by Timothy Insoll. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199675616.013.005.
Повний текст джерелаAchmadi, Amanda, Paul Walker, and Soon-Tzu Speechley, eds. Architectural Encounters in Asia Pacific. Bloomsbury Publishing Plc, 2024. http://dx.doi.org/10.5040/9781350421394.
Повний текст джерелаDorrian, Mark, and Adrian Hawker. Metis : On the Surface. University of Edinburgh, 2024. http://dx.doi.org/10.2218/ed.9781836450153.
Повний текст джерелаMacKenzie, Lisa. An t-Eilean (The Island). University of Edinburgh, 2024. http://dx.doi.org/10.2218/ed.9781836450214.
Повний текст джерелаPang, Changhyun, Chanseok Lee, Hoon Eui Jeong, and Kahp-Yang Suh. Skin and dry adhesion. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0022.
Повний текст джерелаЧастини книг з теми "Multi-scale architecture"
Gassara, Amal, Ismael Bouassida Rodriguez, and Mohamed Jmaiel. "Towards a Multi-scale Modeling for Architectural Deployment Based on Bigraphs." In Software Architecture, 122–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39031-9_11.
Повний текст джерелаChaudhary, Priyanshu, Nischay Dhankhar, Amit Singhal, and K. P. S. Rana. "Multi-scale Architecture for High Performance RSVP Classification." In Lecture Notes in Electrical Engineering, 443–51. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2508-3_32.
Повний текст джерелаHofmann, Jaco. "Multi-Chip Dataflow Architecture for Massive Scale Biophyscially Accurate Neuron Simulation." In Real-Time Multi-Chip Neural Network for Cognitive Systems, 23–47. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339205-2.
Повний текст джерелаYan, Xingang, Weiwen Jiang, Yiyu Shi, and Cheng Zhuo. "MS-NAS: Multi-scale Neural Architecture Search for Medical Image Segmentation." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 388–97. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59710-8_38.
Повний текст джерелаDabral, Tanmaya Shekhar, Amala Sanjay Deshmukh, and Aruna Malapati. "A Multi-scale Convolutional Neural Network Architecture for Music Auto-Tagging." In Advances in Intelligent Systems and Computing, 757–64. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1592-3_60.
Повний текст джерелаRen, Jian, Jin Xie, and Zhong Jin. "Hierarchical Multi-scale Architecture Search for Self-supervised Monocular Depth Estimation." In Lecture Notes in Computer Science, 447–61. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-02444-3_34.
Повний текст джерелаDoroodian, Sareh, Nima Ghaemian, and Mohsen Sharifi. "Analysis of Core-Level Scale-Out Efficiency for OpenMP Programs on Multi-core Processors." In High Performance Architecture and Grid Computing, 322–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22577-2_44.
Повний текст джерелаSaad, Muhammad Muneeb, Mubashir Husain Rehmani, and Ruairi O’Reilly. "A Self-attention Guided Multi-scale Gradient GAN for Diversified X-ray Image Synthesis." In Communications in Computer and Information Science, 18–31. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-26438-2_2.
Повний текст джерелаLi, Kaijiang, Yi Qin, Peisen Wang, Chunyi Guo, Junqi Wang, Ruiyang Jia, and Wenfeng Jiang. "DAMS: Document Image Steganography with Dual Attention Multi-scale Encoder-Decoder Architecture." In Lecture Notes in Computer Science, 118–31. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-8490-5_9.
Повний текст джерелаZhang, He. "A Hierarchical Dataflow Architecture for Large-Scale Multi-FPGA Biophysically Accurate Neuron Simulation." In Real-Time Multi-Chip Neural Network for Cognitive Systems, 143–61. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339205-6.
Повний текст джерелаТези доповідей конференцій з теми "Multi-scale architecture"
Huang, Boqiang, Jiayu Ying, Ruizhi Lyu, Nadine S. Schaadt, Barbara M. Klinkhammer, Peter Boor, Johannes Lotz, Friedrich Feuerhake, and Dorit Merhof. "Utnetpara: A Hybrid CNN-Transformer Architecture with Multi-Scale Fusion for Whole-Slide Image Segmentation." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1–5. IEEE, 2024. http://dx.doi.org/10.1109/isbi56570.2024.10635778.
Повний текст джерелаZhu, Jingwen, Yaxuan Xing, Hongxia Ye, and Feng Wang. "A Subsurface Architecture Detection Method Based on Multi-Source Remote Sensing Data Combined with a Two-Scale Model." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 6807–10. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642206.
Повний текст джерелаMichalatos, Panagiotis, and Andrew Payne. "Working with Multi-scale Material Distributions." In ACADIA 2013: Adaptive Architecture. ACADIA, 2013. http://dx.doi.org/10.52842/conf.acadia.2013.043.
Повний текст джерелаYu, Bo Yang, Tomonori Honda, Syed Zubair, Mostafa H. Sharqawy, and Maria C. Yang. "Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-35032.
Повний текст джерелаHambley, Christopher J., Andrew R. Mills, Visakan Kadirkamanathan, Tony J. Dodd, William Bradley, and Robin Shirtcliffe. "Customer-oriented architecture refinement in multi-criteria synthesis of large-scale system architectures." In 2017 IEEE International Systems Engineering Symposium (ISSE). IEEE, 2017. http://dx.doi.org/10.1109/syseng.2017.8088291.
Повний текст джерелаKim, Won Shik, Ho-Youl Jung, and Jae Hun Choi. "Automatic CAC Voxel Classification with Multi-scale CNN Architecture." In 2019 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2019. http://dx.doi.org/10.1109/ictc46691.2019.8939821.
Повний текст джерелаXu, Yadong, Heiko Aydt, and Michael Lees. "SEMSim: A Distributed Architecture for Multi-scale Traffic Simulation." In 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation (PADS). IEEE, 2012. http://dx.doi.org/10.1109/pads.2012.40.
Повний текст джерелаCioflan, Cristian, and Radu Timofte. "MS-RANAS: Multi-Scale Resource-Aware Neural Architecture Search." In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021. http://dx.doi.org/10.1109/icra48506.2021.9561565.
Повний текст джерелаSmith, Mitchell T., Michael R. Starke, Madhu Chinthavali, and Leon M. Tolbert. "Architecture for Utility-Scale Multi-Chemistry Battery Energy Storage." In 2019 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2019. http://dx.doi.org/10.1109/ecce.2019.8912309.
Повний текст джерелаGassara, Amal, Ismael Bouassida Rodriguez, and Mohamed Jmaiel. "A multi-scale modeling approach for software architecture deployment." In SAC 2015: Symposium on Applied Computing. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2695664.2695721.
Повний текст джерелаЗвіти організацій з теми "Multi-scale architecture"
Taufique, Mohammad Fuad Nur, Isabella Johanna van Rooyen, Sudipta Biswas, Michael Mcmurtrey, Mathew Swisher, Mark Messner, Srinivas Aditya Mantri, et al. MDDC Multi-Length Scale Data Architecture Contribution Report – PNNL, INL, ANL, LANL and ORNL. Office of Scientific and Technical Information (OSTI), September 2023. http://dx.doi.org/10.2172/2478116.
Повний текст джерелаSkjellum, Anthony, Hong Yuan, and Yoginder S. Dandass. A Multi-Time Scale Morphable Software Milieu for Polymorphous Computing Architectures (PCA) - Composable, Scalable Systems. Fort Belvoir, VA: Defense Technical Information Center, October 2004. http://dx.doi.org/10.21236/ada427345.
Повний текст джерелаWozniakowska, P., D. W. Eaton, C. Deblonde, A. Mort, and O. H. Ardakani. Identification of regional structural corridors in the Montney play using trend surface analysis combined with geophysical imaging, British Columbia and Alberta. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/328850.
Повний текст джерелаAtkinson, Dan, and Alex Hale, eds. From Source to Sea: ScARF Marine and Maritime Panel Report. Society of Antiquaries of Scotland, September 2012. http://dx.doi.org/10.9750/scarf.09.2012.126.
Повний текст джерела