Добірка наукової літератури з теми "Frontière neurale"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Frontière neurale".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Статті в журналах з теми "Frontière neurale"
Xu Mingliang, 徐明亮, 李芳媛 Li Fangyuan, 刘岳圻 Liu Yueqi, 张瑾慧 Zhang Jinhui, 师亚洲 Shi Yazhou та 何飞 He Fei. "植入式多模态神经接口前沿进展". Chinese Journal of Lasers 50, № 15 (2023): 1507301. http://dx.doi.org/10.3788/cjl221482.
Повний текст джерелаRey, Federica, Bianca Barzaghini, Alessandra Nardini, Matteo Bordoni, Gian Vincenzo Zuccotti, Cristina Cereda, Manuela Teresa Raimondi, and Stephana Carelli. "Advances in Tissue Engineering and Innovative Fabrication Techniques for 3-D-Structures: Translational Applications in Neurodegenerative Diseases." Cells 9, no. 7 (July 7, 2020): 1636. http://dx.doi.org/10.3390/cells9071636.
Повний текст джерелаLiu, Feng, Jianjun Pang, and Zhiwei Xu. "Multi-Objective Optimization of Injection Molding Process Parameters for Moderately Thick Plane Lens Based on PSO-BPNN, OMOPSO, and TOPSIS." Processes 12, no. 1 (December 22, 2023): 36. http://dx.doi.org/10.3390/pr12010036.
Повний текст джерелаJusten, Lennart, Duncan Carlsmith, Susan M. Paskewitz, Lyric C. Bartholomay, and Gebbiena M. Bron. "Identification of public submitted tick images: A neural network approach." PLOS ONE 16, no. 12 (December 2, 2021): e0260622. http://dx.doi.org/10.1371/journal.pone.0260622.
Повний текст джерелаLe Merrer, Erwan, Patrick Pérez, and Gilles Trédan. "Adversarial frontier stitching for remote neural network watermarking." Neural Computing and Applications 32, no. 13 (August 17, 2019): 9233–44. http://dx.doi.org/10.1007/s00521-019-04434-z.
Повний текст джерелаTsionas, Mike, Christopher F. Parmeter, and Valentin Zelenyuk. "Bayesian Artificial Neural Networks for frontier efficiency analysis." Journal of Econometrics 236, no. 2 (October 2023): 105491. http://dx.doi.org/10.1016/j.jeconom.2023.105491.
Повний текст джерелаJin, Ding. "Portfolio Management Based on TMT Sector: Comparative Study between Basic Qualitative and Model-Based Approach." BCP Business & Management 38 (March 2, 2023): 579–91. http://dx.doi.org/10.54691/bcpbm.v38i.3742.
Повний текст джерелаAkter, Mst Shapna, Hossain Shahriar, Reaz Chowdhury, and M. R. C. Mahdy. "Forecasting the Risk Factor of Frontier Markets: A Novel Stacking Ensemble of Neural Network Approach." Future Internet 14, no. 9 (August 25, 2022): 252. http://dx.doi.org/10.3390/fi14090252.
Повний текст джерелаFurber, Steve, and Steve Temple. "Neural systems engineering." Journal of The Royal Society Interface 4, no. 13 (November 28, 2006): 193–206. http://dx.doi.org/10.1098/rsif.2006.0177.
Повний текст джерелаCohen, Avis H. "Neural Regeneration and Transplantation (Frontiers of Clinical Neuroscience Vol. 6)." Trends in Neurosciences 13, no. 2 (February 1990): 77–78. http://dx.doi.org/10.1016/0166-2236(90)90074-k.
Повний текст джерелаДисертації з теми "Frontière neurale"
LANDI, FEDERICO. "Percepire, Ragionare, Agire: la Nuova Frontiera dell’Embodied AI." Doctoral thesis, Università degli studi di Modena e Reggio Emilia, 2022. http://hdl.handle.net/11380/1271185.
Повний текст джерелаThis thesis contributes to the field of Embodied Artificial Intelligence. Embodied AI is a novel research topic at the intersection of Computer Vision and Robotics and takes advantage of recent findings on Deep Neural Networks. Empowered by the so-called "deep revolution", we strive to create intelligent agents able to: perceive the world, reason about Spatio-temporal relationships, and act to reach a pre-defined goal. First, we need to identify a proper strategy to tackle such a complex topic, which entails time series and long-term dependencies on one end and multiple input modalities on the other end. We distinguish three different problems we need to address to build an intelligent agent. We start from the problem of long-term dependencies and sequence modeling, as the agent needs to process data coming from a sequence of time steps acting as previous experience. Then, we consider and tackle a first simple form of interaction with an unknown environment: exploration. In this way, we combine visual and spatial reasoning to perform simple actions such as in-place rotations and moving forward. Finally, we study how to incorporate natural language instructions to guide the agent's navigation towards a goal. Language then becomes a natural interface to communicate with the agent, paving the way to future research and applications. This thesis presents a step-by-step analysis of these features that any intelligent agent should possess. While doing so, we cover a comprehensive overview of the field, theoretical foundations for Embodied AI, state-of-the-art datasets and benchmarks, and practical indications regarding the deployment of the resulting agent in the real world. In the first part of this thesis, we discuss Recurrent Neural Networks (RNNs). RNNs are the most common approach when dealing with time series. IN particular, Long Short-Term Memory (LSTM) is the standard de-facto for many tasks involving sequential inputs and long-term dependencies. As such, they represent an enabling technology for Embodied AI. We introduce a heuristic enhancement of LSTM that brings better results, increased training stability, and reduced convergence time on a set of tasks. In the following, we place the agent in a simulated photorealistic unknown environment. We aim to explore the largest portion of the environment new scene in a fixed amount of time. To that end, we propose two different training setups. The first approach relies on curiosity, where the agent tries to maximize its surprisal during the exploration episode. The second strategy promotes actions likely to produce a high impact (i.e., visual changes) on the environment. We show that exploration is an essential ability of embodied agents and that it can enable a series of downstream tasks such as scene description and coordinate-driven navigation in unknown environments. Then we tackle the recent task of Vision-and-Language Navigation (VLN). In VLN, the agent needs to follow a language-specified instruction to reach a target location in a new environment. With that in mind, we propose two different methods to fuse lingual and visual information: one based on dynamic convolutional filters and the other based on attention. This way, we show that it is possible to include natural language instructions from a human user in the agent reasoning motor. Hence, we enable a series of future research directions and applications. As a final contribution, we discuss how to deploy agents trained in simulation in the real world. While most of our experiments exploit simulation, we show that it is possible to deploy the resulting models on a Low-Cost Robot (LoCoBot) with little effort.
Egilmez, Gokhan. "Road Safety Assessment of U.S. States: A Joint Frontier and Neural Network ModelingApproach." Ohio University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1374854708.
Повний текст джерелаBally-Cuif, Laure. "Developpement de la région met-mésencéphalique du tube neural : rôle du gène Wnt-1." Paris 6, 1994. http://www.theses.fr/1994PA066809.
Повний текст джерелаGiavelli, Francesca. "DeepL: la nuova frontiera della traduzione automatica neurale a confronto con il linguaggio enologico. Uno studio basato sulla traduzione del sito della Cantina di Cesena." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15177/.
Повний текст джерелаSavan, Emanuel-Emil. "Consumer liking and sensory attribute prediction for new product development support : applications and enhancements of belief rule-based methodology." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/consumer-liking-and-sensory-attribute-prediction-for-new-product-development-support-applications-and-enhancements-of-belief-rulebased-methodology(0582be52-a5ce-47da-836d-e30b5506fb41).html.
Повний текст джерелаWu, Hsin-Yun, and 吳欣芸. "CURRENCY BASKET HEDGE — THE COMPARISON BETWEEN EFFICENT FRONTIER AND ARTIFICIAL NEURAL NETWORK." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/40459188698317435140.
Повний текст джерела元智大學
管理研究所
96
Life insurance companies in Taiwan enjoy better returns for their investment abroad. These investment in foreign currency are therefore subject to exchange risk and substantial FX volatility when insurances move their massive currency position from one to another, thus it is required by the Central Bank that these overseas positions are 100% FX-hedged. Another main cause for fluctuating returns is the swinging hedging cost by which total return for foreign investment in late 2006 was effectively overtaken by domestic one. Currency Basket Hedge was then developed for FX-risk-aversion and the pursuit of lower hedging cost. Based on the model of Constant Tracking Error, this research aims to identify, by using two models constructed, the optimal weighting of each composite in a currency basket. Results from respective models are then compared for effectiveness in hedging and cost level. The data sources include historical daily closing price and forward closing price within a given time frame (by using the Back-Propagation Network to forecast). The former assumes the historical price movement is identical to the one for the future, whereas the latter assumes what is forecast by the Back-Propagation Network is the same vis-à-vis the future price movement. Also, this research uses NNTool within the Matlab Package, as it is more suitable for users who are not familiar with computer programming, which will also enable the concepts of Back-Propagation Network to better comprehended. This research shows that both models serve the objectives reasonably well, yet they have different advantages in the two objectives and portfolio managers can choose accordingly for the set-up of currency basket hedging.
raganato, alessandro. "New frontiers in supervised word sense disambiguation: building multilingual resources and neural models on a large scale." Doctoral thesis, 2018. http://hdl.handle.net/11573/1066474.
Повний текст джерелаGorricha, Jorge Manuel Lourenço. "Visualization of clusters in geo-referenced data using three-dimensional self-organizing maps." Master's thesis, 2010. http://hdl.handle.net/10362/2631.
Повний текст джерелаThe Self-Organizing Map (SOM) is an artificial neural network that performs simultaneously vector quantization and vector projection. Due to this characteristic, the SOM is an effective method for clustering analysis via visualization. The SOM can be visualized through the output space, generally a regular two-dimensional grid of nodes, and through the input space, emphasizing the vector quantization process. Among all the strategies for visualizing the SOM, we are particularly interested in those that allow dealing with spatial dependency, linking the SOM to the geographic visualization with color. One possible approach, commonly used, is the cartographic representation of data with label colors defined from the output space of a two-dimensional SOM. However, in the particular case of geo-referenced data, it is possible to consider the use of a three-dimensional SOM for this purpose, thus adding one more dimension in the analysis. In this dissertation is presented a method for clustering geo-referenced data that integrates the visualization of both perspectives of a three dimensional SOM: linking its output space to the cartographic representation through a ordered set of colors; and exploring the use of frontiers among geo-referenced elements, computed according to the distances in the input space between their Best Matching Units.
Книги з теми "Frontière neurale"
Zheng, Xiaoxiang, ed. Neural Interface: Frontiers and Applications. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2050-7.
Повний текст джерелаWu, Lingfei, Peng Cui, Jian Pei, and Liang Zhao, eds. Graph Neural Networks: Foundations, Frontiers, and Applications. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6054-2.
Повний текст джерелаLevy, Steven. Artificial life: A report from the frontier where computers meet biology. New York: Vintage Books, 1993.
Знайти повний текст джерелаMarkellos, Raphael N. Robust estimation of nonlinear production frontiers and efficiency: A neural network approach. Loughborough: Loughborough University, Department of Economics, 1997.
Знайти повний текст джерелаDoidge, Norman. The brain that changes itself: Stories of personal triumph from the frontiers of brain science. London: Penguin Books, 2008.
Знайти повний текст джерелаNeural Frontiers. MDPI, 2023. http://dx.doi.org/10.3390/books978-3-0365-9765-2.
Повний текст джерелаZheng, Xiaoxiang. Neural Interface: Frontiers and Applications. Springer, 2019.
Знайти повний текст джерелаZheng, Xiaoxiang. Neural Interface: Frontiers and Applications. Springer, 2019.
Знайти повний текст джерелаRuthazer, Edward S., and Takao K. Hensch, eds. Frontiers in Neural Circuits - Editors’ Pick 2021. Frontiers Media SA, 2021. http://dx.doi.org/10.3389/978-2-88971-643-2.
Повний текст джерелаGraph Neural Networks: Foundations, Frontiers, and Applications. Springer, 2023.
Знайти повний текст джерелаЧастини книг з теми "Frontière neurale"
Spaanenburg, L., and W. J. Jansen. "Networked Neural Systems." In The Frontiers Collection, 231–42. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22093-2_16.
Повний текст джерелаSun, Xiaoan, Sui Huang, and Ningyuan Wang. "Neural Interface: Frontiers and Applications." In Advances in Experimental Medicine and Biology, 167–206. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2050-7_7.
Повний текст джерелаRueckert, Ulrich. "Digital Neural Network Accelerators." In The Frontiers Collection, 181–202. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-18338-7_12.
Повний текст джерелаPaul, Dorothy H. "Neural Phylogeny — Its Use in Studying Neural Circuits." In Frontiers in Crustacean Neurobiology, 537–46. Basel: Birkhäuser Basel, 1990. http://dx.doi.org/10.1007/978-3-0348-5689-8_67.
Повний текст джерелаLin, Eugene, and Shih-Jen Tsai. "Machine Learning in Neural Networks." In Frontiers in Psychiatry, 127–37. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9721-0_7.
Повний текст джерелаSpaanenburg, Lambert, and Suleyman Malki. "Digital Neural Networks for New Media." In The Frontiers Collection, 331–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23096-7_16.
Повний текст джерелаWatanabe, Masataka. "Neural Manipulation for Causal Investigation of Consciousness." In The Frontiers Collection, 61–85. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-91138-6_3.
Повний текст джерелаFilk, Thomas. "The Quantum-like Behavior of Neural Networks." In The Frontiers Collection, 553–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92192-7_30.
Повний текст джерелаWu, Lingfei, Peng Cui, Jian Pei, Liang Zhao, and Le Song. "Graph Neural Networks." In Graph Neural Networks: Foundations, Frontiers, and Applications, 27–37. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6054-2_3.
Повний текст джерелаKatz, Jennifer, Bryan Keenan, and Evan Y. Snyder. "Culture and Manipulation of Neural Stem Cells." In Frontiers in Brain Repair, 13–22. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-5819-8_2.
Повний текст джерелаТези доповідей конференцій з теми "Frontière neurale"
Rakovic, Dejan. "Quantum-informational bases and frontiers of psychosomatic integrative medicine." In 2014 12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL 2014). IEEE, 2014. http://dx.doi.org/10.1109/neurel.2014.7011473.
Повний текст джерелаGraves, Alex. "Plenary talks: Frontiers in recurrent neural network research." In 2017 International Joint Conference on Neural Networks (IJCNN). IEEE, 2017. http://dx.doi.org/10.1109/ijcnn.2017.7965820.
Повний текст джерелаWu, Lingfei, Peng Cui, Jian Pei, Liang Zhao, and Xiaojie Guo. "Graph Neural Networks: Foundation, Frontiers and Applications." In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3534678.3542609.
Повний текст джерелаJi, Shuiwang, Meng Liu, Yi Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Zhao Xu, and Haiyang Yu. "Frontiers of Graph Neural Networks with DIG." In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3534678.3542624.
Повний текст джерелаWu, Lingfei, Peng Cui, Jian Pei, Liang Zhao, and Xiaojie Guo. "Graph Neural Networks: Foundation, Frontiers and Applications." In KDD '23: The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3580305.3599560.
Повний текст джерелаGong, Zheng, Carmine Ventre, and John O'Hara. "The efficient hedging frontier with deep neural networks." In ICAIF'21: 2nd ACM International Conference on AI in Finance. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3490354.3494392.
Повний текст джерелаZhang, Duzhen, Tielin Zhang, Shuncheng Jia, Qingyu Wang, and Bo Xu. "Recent Advances and New Frontiers in Spiking Neural Networks." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/790.
Повний текст джерелаBaran, Timothy M. "Improved tissue optical property extraction at short source-detector separations using neural networks." In Frontiers in Optics. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/fio.2022.fth3b.2.
Повний текст джерелаAshtiani, Farshid, Mohamad Hossein Idjadi, Ting-Chen Hu, Stefano Grillanda, David Neilson, Mark Earnshaw, Mark Cappuzzo, Rose Kopf, Alaric Tate, and Andrea Blanco-Redondo. "Neural nonlinearity using a surface normal photodetector for diffractive optical neural networks." In Frontiers in Optics. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/fio.2023.fw6e.2.
Повний текст джерелаGreene, Joseph, Yujia Xue, Jeffrey Alido, Alex Matlock, Guorong Hu, Kivilcim Kiliç, Ian Davison, and Lei Tian. "Pupil Engineering in Miniscopes for extended depth-of-field Neural Imaging." In Frontiers in Optics. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/fio.2022.fth3d.4.
Повний текст джерела