-
crossref
D. Owen-Newns, L. Jaurigue, J. Robertson, A. Adair 等
2024-12-20T18:55:55Z
置信度 0.70
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Ting Ye, Jiang Wang, Kai Li, Tianshi Gao 等
2021-10-07T04:24:31Z
置信度 0.70
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Alexey V. Popov, Konstantin S. Sayarkin, Anton A. Zhilenkov
2018-03-19T18:04:56Z
置信度 0.70
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crossref
Gulin Wang, Ziliang Ren, Qieshi Zhang, Jun Cheng
2025-03-21T19:01:35Z
置信度 0.70
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Joo-Heon Shin, David Smith, Waldemar Swiercz, Kevin Staley 等
2010-11-10T20:53:44Z
置信度 0.70
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crossref
2025-08-27T14:32:12Z
置信度 0.70
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crossref
Yajie Chen, S. Hall, L. McDaid, O. Buiu 等
2008-07-18T11:27:21Z
置信度 0.70
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crossref
Moorthy Agoramoorthy, K. Ananthajothi, M. Amanullah
2025-06-27T13:00:10Z
置信度 0.70
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Lulin Ye, Chi Zhou, Hong Peng, Jun Wang 等
2024-07-04T16:33:02Z
置信度 0.70
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Regina Esi Turkson, Sichao Liu, Edward Y. Baagyere, Moses J. Eghan
2020-04-17T00:46:56Z
置信度 0.70
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crossref
Raphaela Kreiser, Matteo Cartiglia, Julien N.P. Martel, Jorg Conradt 等
2018-05-04T22:00:05Z
置信度 0.70
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Spiking Neural Networks (SNNs) become popular due to excellent energy efficiency, yet facing challenges for effective model training. Recent works improve this by introducing knowledge distillation (KD) techniques, with the pre-trained artificial neural networ…
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Xu Liu, Na Xia, Jinxing Zhou, Jingyuan Xu 等
2026-03-17T22:57:26Z
置信度 0.70
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crossref
Yuchen Wang, Xiaobin Wang, Hong Qu, Ya Zhang 等
2021-09-20T21:27:41Z
置信度 0.70
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Abstract Complex biological systems evolved to control dynamics in the presence of noisy and often unpredictable inputs. The staple example is locomotor control, which is vital for survival. Control of locomotion results from interactions between multiple syst…
preprints
Yuriy Pryyma, Sergiy Yakovenko
2024
置信度 0.74
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Jingxin Liu, Zikai Song, Xihang Qiu, Ran Cai 等
2025-12-05T00:33:45Z
置信度 0.70
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crossref
Liping Wang, Xiyu Liu, Minghe Sun, Yuzhen Zhao
2023-05-09T17:27:02Z
置信度 0.70
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crossref
Chris Yakopcic, Nayim Rahman, Tanvir Atahary, Md. Zahangir Alom 等
2019-11-25T14:13:36Z
置信度 0.70
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crossref
T. Eswarlal, Francis H. Shajin, Rajesh Kumar Singh, T. Senthil Prakash
2024-09-18T13:02:59Z
置信度 0.70
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crossref
Li-Ye Niu, Ying Wei, Yue Liu
2023-04-24T10:57:45Z
置信度 0.70
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crossref
Zhengshan Dong, Wude He, Yongcheng Zhou
2026-07-29T19:03:01Z
置信度 0.70
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Abstract In the face of the increasing complex electromagnetic environment and new radar system, it is difficult to extract radar emitter characteristics based on manual mode to meet requirements of modern cognitive electronic warfare. In order to improve the …
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LI Wei, Zhu Wei-gang, Pang Hong-feng, Zhao Hong-yu
2021-05-24T17:11:38Z
置信度 0.70
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Dynamique et computations dans les réseaux de neurones récurrents : influence des potentiels d’action et de la variabilité Les neurones du cerveau forment des réseaux qui sont le substrat du comportement et de l’exécution de calculs. Les modèles de réseaux neu…
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Ljubica Cimeša
2026-04-08T11:52:14Z
置信度 0.70
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ABSTRACT Most sensory stimuli are temporal in structure. How action potentials encode the information incoming from sensory stimuli remains one of the central research questions in neuroscience. Although there is evidence that the precise timing of spikes repr…
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Muhammad Yaqoob, Volker Steuber, Borys Wróbel
2023-11-17T15:35:19Z
置信度 0.70
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crossref
Stylianos Kampakis
2013-02-08T23:02:21Z
置信度 0.70
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crossref
Ankur Gupta, Lyle N. Long
2009-08-05T14:59:01Z
置信度 0.70
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crossref
Barna Zajzon, Renato Duarte, Abigail Morrison
2018-10-19T22:25:09Z
置信度 0.70
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Yesmine Abdennadher, Giovanni Perin, Riccardo Mazzieri, Jacopo Pegoraro 等
2025-09-16T17:32:27Z
置信度 0.70
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Elisabetta Polidori, Giovanni Camisa, Alireza Mesri, Giorgio Ferrari 等
2022-12-05T23:43:02Z
置信度 0.70
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William Severa, Felix Wang, Yang Ho, Fred Rothganger 等
2025-06-27T13:58:23Z
置信度 0.70
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crossref
Mena Nagiub, Thorsten Beuth, Ganesh Sistu, Heinrich Gotzig 等
2025-10-21T17:07:00Z
置信度 0.70
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crossref
Christian Holberg, Cristopher Salvi
2025-11-03T11:20:56Z
置信度 0.70
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Antonio Galves, Eva Löcherbach, Christophe Pouzat
2024-10-16T16:03:00Z
置信度 0.70
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crossref
Lanting Cao, Baohua Xu, Jiabin Yuan, Yuqian Zhou
2026-08-10T19:18:08Z
置信度 0.70
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crossref
T. Senthil Prakash, G. Kannan, Salini Prabhakaran, Bhagirath Parshuram Prajapati
2023-10-11T06:03:30Z
置信度 0.70
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crossref
Sneha Singh, Deep Gupta, R.S. Anand, Vinod Kumar
2015-03-25T13:22:36Z
置信度 0.70
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crossref
Li-Ye Niu, Ying Wei, Wen-Bo Liu, Jun-Yu Long 等
2023-03-08T08:03:32Z
置信度 0.70
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crossref
Junxiu Liu, Xingyue Huang, Yongchuang Huang, Yuling Luo 等
2019-09-08T23:02:47Z
置信度 0.70
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crossref
Shilong Zhu, Jun Wang, Weiguo Huang, Shuang Li 等
2026-07-01T19:36:05Z
置信度 0.70
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crossref
J. Bose, S. B. Furber, J. L. Shapiro
2006-03-10T03:45:04Z
置信度 0.70
-
A hardware-based spiking neural network (SNN) has attracted many researcher’s attention due to its energy-efficiency. When implementing the hardware-based SNN, offline training is most commonly used by which trained weights by a software-based artificial neura…
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Sungmin Hwang, Hyungjin Kim, Byung-Gook Park
2021-02-25T21:16:53Z
置信度 0.70
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crossref
Praveena Kakarla, C. Vimala, S. Hemachandra
2023-10-27T10:01:48Z
置信度 0.70
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crossref
Pengfei Sun, Jibin Wu, Paul Devos, Dick Botteldooren
2025-01-16T17:57:40Z
置信度 0.70
-
Spiking neural networks (SNNs) have recently demonstrated significant progress across various computational tasks, due to their potential for energy efficiency. Neural radiance fields (NeRFs) excel at rendering high-quality 3D scenes but require substantial en…
crossref
Xingting Yao, Qinghao Hu, Fei Zhou, Tielong Liu 等
2025-07-23T12:46:16Z
置信度 0.70
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crossref
Viet-Ngu Cong Huynh, Keon Myung Lee
2020-11-25T16:46:55Z
置信度 0.70
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Zohreh Doborjeh, Balkaran Singh, Alexander Sumich, Maryam Doborjeh 等
2025-11-14T18:46:15Z
置信度 0.70
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crossref
Matteo Saponati, Chiara De Luca, Giacomo Indiveri, Benjamin Grewe
2025-07-08T13:36:20Z
置信度 0.70
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crossref
Changjiang Han, Li-Juan Liu, Hamid Reza Karimi
2025-02-25T16:18:33Z
置信度 0.70
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crossref
Gexiang Zhang, Sergey Verlan, Tingfang Wu, Francis George C. Cabarle 等
2024-12-13T12:14:30Z
置信度 0.70
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Abstract Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This development has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The demand…
crossref
Karla Burelo, Georgia Ramantani, Giacomo Indiveri, Johannes Sarnthein
2022-02-02T06:06:03Z
置信度 0.70
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crossref
2025-01-31T19:14:15Z
置信度 0.70
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crossref
Jing Peng, Shanshan Jia, Jiyuan Zhang, Yongxing Wang 等
2025-07-16T05:11:43Z
置信度 0.70
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Prediction of Crop yield focuses primarily on agriculture research which will have a significant effect on making decisions such as import-export, pricing and distribution of specific crops. Predicting accurately with well-timed forecasts is important, but it …
crossref
G. Karuna, K. Pravallika, K. Anuradha, V. Srilakshmi
2021-10-07T08:52:32Z
置信度 0.70
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crossref
Seamus Cawley, Fearghal Morgan, Brian McGinley, Sandeep Pande 等
2011-04-01T20:28:26Z
置信度 0.70
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crossref
Rui-Jie Zhu, Ziqing Wang, Leilani Gilpin, Jason Eshraghian
2025-11-03T11:20:56Z
置信度 0.70
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crossref
Haowen Fang, Amar Shrestha, Qinru Qiu
2020-09-30T00:40:33Z
置信度 0.70
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Graph theory investigates relationships among entities through mathematical structures composed of vertices (nodes) and edges (connections) [1]. A hypergraph generalizes the classical graph by introducing hyperedges, which can join any number of vertices rathe…
crossref
Takaaki Fujita
2025-06-11T11:54:04Z
置信度 0.70
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crossref
Zafeirios Fountas, Murray Shanahan
2015-10-01T21:48:02Z
置信度 0.70
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crossref
David Chik, Roman Borisyuk, Yakov Kazanovich
2009-02-22T02:58:09Z
置信度 0.70
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crossref
Manh V. Nguyen, Liang Zhao, Bobin Deng, Shaoen Wu
2025-09-30T17:36:40Z
置信度 0.70
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crossref
2025-01-31T19:14:36Z
置信度 0.70
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Spiking neural P systems with weights are a new class of distributed and parallel computing models inspired by spiking neurons. In such models, a neuron fires when its potential equals a given value (called a threshold). In this work, spiking neural P systems …
crossref
Xiangxiang Zeng, Xingyi Zhang, Tao Song, Linqiang Pan
2014-04-08T00:15:53Z
置信度 0.70
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crossref
Mingming Sun, Jianhua Qu
2017-07-13T20:47:48Z
置信度 0.70
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crossref
Dongcheng Zhao, Yang Li, Yi Zeng, Jihang Wang 等
2022-08-01T01:45:53Z
置信度 0.70
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crossref
Hiroki Shinagawa, Gouhei Tanaka
2025-03-31T22:30:11Z
置信度 0.70
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crossref
Leonard Knapp, Sven Nitzsche, Matthias Börsig, Alexandru Vasilache 等
2025-11-14T18:47:04Z
置信度 0.70
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Η παρούσα διδακτορική διατριβή μελετά την ανάπτυξη φωτονικών νευρομορφικών επεξεργαστών (ΝΕ) που απευθύνονται στις εξής τρεις κρίσιμες προκλήσεις των Big Data και του Internet of Things: την υψηλή ταχύτητα επεξεργασίας, την χαμηλή κατανάλωση ισχύος και την ελα…
crossref
Μενέλαος Σκοντράνης
2025-01-24T08:32:27Z
置信度 0.70
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crossref
Trung-Khanh Le, Do-Cuong Nguyen, Trong-Tu Bui, Duc-Hung Le
2025-03-07T18:33:20Z
置信度 0.70
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crossref
Zhanglu Yan, Jun Zhou, Weng-Fai Wong
2020-08-28T13:26:06Z
置信度 0.70
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crossref
R. Arivalahan, T. Vinoth
2024-01-12T06:20:16Z
置信度 0.70
-
Spiking neural networks (SNNs) have garnered significant attention for their low power consumption when deployed on neuromorphic hardware that operates in orders of magnitude lower power than general-purpose hardware. Direct training methods for SNNs come with…
crossref
Srinivas Anumasa, Bhaskar Mukhoty, Velibor Bojkovic, Giulia De Masi 等
2024-03-25T10:44:02Z
置信度 0.70
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crossref
Yanjing Li
2023-06-16T08:23:44Z
置信度 0.70
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crossref
Paolo Lunghi, Stefano Silvestrini, Dominik Dold, Gabriele Meoni 等
2025-10-17T02:49:23Z
置信度 0.70
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crossref
2025-01-31T19:14:16Z
置信度 0.70
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crossref
Shengjie Zheng, Wenyi Li, Lang Qian, Chenggang He 等
2022-09-06T00:02:53Z
置信度 0.70
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crossref
Paul Kirkland, Gaetano Di Caterina, John Soraghan, Yiannis Andreopoulos 等
2019-09-08T19:02:47Z
置信度 0.70
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europepmc
Xianghong Lin, Mingshuai Yu, Xiangwen Wang
2026
置信度 0.80
-
crossref
Hideki TANAKA, Takashi MORIE, Kazuyuki AIHARA
2009-07-08T05:57:28Z
置信度 0.70
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crossref
Alexandru Vasilache, Sven Nitzsche, Christian Kneidl, Mikael Tekneyan 等
2026-01-21T21:07:17Z
置信度 0.70
-
crossref
Qi Jin, Jiang Xie
2025-11-19T09:17:34Z
置信度 0.70
-
crossref
Kaushalya Kumarasinghe, Mahonri Owen, Denise Taylor, Nikola Kasabov 等
2018-09-21T18:28:03Z
置信度 0.70
-
crossref
Abdulrazak Yahya Saleh, Siti Mariyam Shamsuddin, Haza Nuzly Abdull Hamed
2017-01-02T07:30:12Z
置信度 0.70
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crossref
Enrico Ferrea, Pierre Morel, Alexander Gail
2022-07-05T15:58:33Z
置信度 0.70
-
crossref
Seunghwan Song, Bosung Jeon, Munhyeon Kim, Jae-Joon Kim
2023-04-06T17:37:29Z
置信度 0.70
-
crossref
Xunqin Lai, Federico Corradi, Siva Satyendra Sahoo
2025-08-20T18:28:20Z
置信度 0.70
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crossref
Xuelei Chen, Sotirios Spanogianopoulos
2025-12-22T18:39:45Z
置信度 0.70
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crossref
Andrew Rowley, Oliver Rhodes, Petrut Bogdan, Christian Brenninkmeijer 等
2021-07-05T10:13:16Z
置信度 0.70
-
We demonstrate that recently introduced ultra-compact neurons (UCN) with a minimal number of components can be interconnected to implement a functional spiking neural network. For concreteness we focus on the Jeffress model, which is a classic neuro-computatio…
crossref
Pablo Stoliar, Olivier Schneegans, Marcelo J. Rozenberg
2021-02-25T08:47:57Z
置信度 0.70
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crossref
Zhen Cao, Ziyi Zhang, Qi Sun, Biao Hou 等
2025-01-13T19:41:59Z
置信度 0.70
-
crossref
Aleksandr Sboev, Alexey Serenko, Roman Rybka, Danila Vlasov 等
2018-12-11T07:40:19Z
置信度 0.70
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crossref
Jeonggyu Yang, Taigon Song
2021-02-02T15:51:49Z
置信度 0.70
-
We introduce a supervised learning algorithm for photonic spiking neural network (SNN) based on back propagation. For the supervised learning algorithm, the information is encoded into spike trains with different strength, and the SNN is trained according to d…
crossref
Yahui Zhang, Shuiying Xiang, Yanan Han, Xingxing Guo 等
2023-04-20T11:00:16Z
置信度 0.70
-
Abstract Control theory provides a natural language to describe multi-areal interactions and flexible cognitive tasks such as covert attention or brain-machine interface (BMI) experiments, which require finding adequate inputs to a local circuit in order to st…
preprints
Tiago Costa, Juan R. Castiñeiras de Saa, Alfonso Renart
2024
置信度 0.74
-
crossref
Zhi-Song Liu, Petri Clusius, Michael Boy
2025-01-02T17:17:04Z
置信度 0.70
-
crossref
Mohammad Tayefe Ramezanlou
2026-07-22T19:42:12Z
置信度 0.70
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crossref
Wenjie Wei, Malu Zhang, Jieyuan (Eric) Zhang, Ammar Belatreche 等
2026-08-06T14:44:29Z
置信度 0.70
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crossref
Shigeru Shinomoto
2010-05-01T05:00:33Z
置信度 0.70
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crossref
K.Subathra, Prathima G, K.Sundareswari, G.Shailaja 等
2026-03-09T19:55:25Z
置信度 0.70
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crossref
Nadia Ahmed, Shaghayegh Gomar, Arash Ahmadi
2025-11-25T18:26:55Z
置信度 0.70
-
crossref
Roberto A. Vazquez, Bernard Girau, Jean-Charles Quinton
2011-10-06T13:24:17Z
置信度 0.70
-
crossref
Jieyuan (Eric) Zhang, Xiaolong Zhou, Shuai Wang, Wenjie Wei 等
2026-08-06T14:44:29Z
置信度 0.70