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There has been considerable interest in the development of optoelectronic synaptic transistors with synaptic functions and neural computations. These neuromorphic devices exhibit high-efficiency energy consumption and fast operation by imitating biological neu…
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Jusung Chung, Kyungho Park, Gwan In Kim, Jong Bin An 等
2022-09-03T23:07:53Z
置信度 0.70
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2020-09-29T09:22:27Z
置信度 0.70
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Qing-an Ding, Chaoran Gu, Jianyu Li, Youli Yao 等
2023-11-24T15:01:10Z
置信度 0.70
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Currently, neuromorphic computing is regarded as the most efficient way to solve the von Neumann bottleneck. Transistor-based devices have been considered suitable for emulating synaptic functions in neuromorphic computing due to their synergistic control capa…
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Wen Huang, Huixing Zhang, Zhengjian Lin, Pengjie Hang 等
2024-01-09T10:48:06Z
置信度 0.70
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Abstract With the advancements in Web of Things, Artificial Intelligence, and other emerging technologies, there is an increasing demand for artificial visual systems to perceive and learn about external environments. However, traditional sensing and computing…
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Shen-Yi Li, Ji-Tuo Li, Kui Zhou, Yan Yan 等
2024-05-30T22:46:02Z
置信度 0.70
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Ali Akbar Firoozi, Ali Asghar Firoozi
2024-09-12T15:02:54Z
置信度 0.70
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Hua Yang, Lihao Yu, Yanjie Lv, Hao Xue 等
2025-05-19T17:52:05Z
置信度 0.70
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J. F. Kang, B. Gao, Z. Chen, P. Huang 等
2018-01-29T04:31:25Z
置信度 0.70
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Changhao Liu, Hang Chen, Dehao Cai, Xiang Li 等
2026-01-06T18:33:35Z
置信度 0.70
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Mark Barnell, Courtney Raymond, Matthew Wilson, Darrek Isereau 等
2020-12-22T21:07:15Z
置信度 0.70
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Recent advancements in brain imaging technology have led to a rise in the use of magnetic resonance imaging (MRI) for clinical diagnosis. Deep learning (DL) techniques have emerged as a valuable tool for automatically detecting abnormalities in brain images wi…
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Ankita Tiwari, Sampada Tavse, Mrinal Bachute, Abhishek Bhola
2024-11-29T15:16:27Z
置信度 0.70
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Xingyan Wang, Dawen Xia, Zhan Lin, Mingyue Huang 等
2025-05-19T17:52:05Z
置信度 0.70
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Yanhu Wang, Shanshan Xu, Yuling Luo, Shunsheng Zhang 等
2021-11-29T20:59:32Z
置信度 0.70
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Paula Stoll, Giacomo Indiveri, Chiara Bartolozzi, Elisa Donati
2026-01-21T21:07:17Z
置信度 0.70
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Linchao Dong, Ting Liu, Peng Liu, Hangjun Che 等
2024-03-19T18:09:52Z
置信度 0.70
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crossref
Qi Xu, Song Chen, Bei Yu, Feng Wu
2018-06-07T13:57:46Z
置信度 0.70
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crossref
2024-11-26T02:06:27Z
置信度 0.70
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Abstract Understanding how biological neural networks are shaped via local plasticity mechanisms can lead to energy-efficient and self-adaptive information processing systems, which promises to mitigate some of the
current roadblocks in edge computing …
crossref
Willian Soares Girāo, Nicoletta Risi, Caroline Geisler, Elisabetta Chicca
2026-08-10T22:49:42Z
置信度 0.70
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Neuromorphic photonic applies concepts extracted from neuroscience to develop photonic devices behaving like neural systems and achieve brain-like information processing capacity and efficiency. This new field combines the advantages of photonics and neuromorp…
crossref
Mike Haidar Shahine
2020-11-06T11:04:43Z
置信度 0.70
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crossref
2026-01-21T21:08:13Z
置信度 0.70
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Energy storage and neuromorphic computation concepts based on oxygen and lithium ionic movements rely in the device preformance on the available defects and their mobilities. Through this paper we explore novel concepts on the use of strain for crystalline or …
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Jennifer L.M. Rupp
2022-02-09T01:07:35Z
置信度 0.70
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Abstract Neuromorphic computing is a budding avenue though it has been known since the 80’s. The extensive research and development in the field of artificial intelligence particularly in the last decade is tremendous. The growth of artificial intelligence is …
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R Vishwa, R Karthikeyan, R Rohith, A Sabaresh
2020-09-12T01:17:00Z
置信度 0.70
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Distinct technologies have been formulated at different times to improve technology, and unique technologies are continuously emerging. Neurocomputing has significantly expanded technologies, revealed moderately acceptable results, and provided ultimate collab…
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Soumitra Saha, Umesh Kumar Lilhore, Sarita Simaiya
2024-11-29T15:16:27Z
置信度 0.70
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Md Mahadi Rajib, Dhritiman Bhattacharya, Kai Liu, Jayasimha Atulasimha
2024-10-04T19:10:32Z
置信度 0.70
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Ashish Gautam, Robert Patton, Thomas Potok, Ramakrishnan Kannan 等
2025-06-27T13:58:23Z
置信度 0.70
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Deep neural networks have demonstrated impressive results in various cognitive tasks such as object detection and image classification. This paper describes a neuromorphic computing system that is designed from the ground up for energy-efficient evaluation of …
crossref
Taeyang Hong, Yongshin Kang, Jaeyong Chung
2020-10-30T21:34:47Z
置信度 0.70
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Neuromorphic computing, drawing inspiration from the brain, stands out for its high energy efficiency in executing complex tasks. Memristive device-based neuromorphic computing has demonstrated ultrahigh efficiency. While there are numerous review papers in th…
crossref
Yike Xiao, Cheng Gao, Juncheng Jin, Weiling Sun 等
2024-10-31T09:00:55Z
置信度 0.70
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Atomic Switch Networks comprising silver iodide (AgI) junctions, a material previously unexplored as functional memristive elements within highly interconnected nanowire networks, were employed as a neuromorphic substrate for physical Reservoir Computing This …
crossref
Sam Lilak, Walt Woods, Kelsey Scharnhorst, Christopher Dunham 等
2021-05-26T06:24:40Z
置信度 0.70
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crossref
Ali Akbar Firoozi, Ali Asghar Firoozi
2024-09-12T15:02:54Z
置信度 0.70
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This study investigates how dynamical systems may be learned and modeled with a neuromorphic network, which is itself a dynamical system. The neuromorphic network used in this study is based on a complex electrical circuit comprised of memristive elements that…
crossref
Yinhao Xu, Georg A. Gottwald, Zdenka Kuncic
2025-10-23T13:19:53Z
置信度 0.70
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Sidi Yaya Arnaud Yarga, Sean U. N. Wood
2025-07-23T21:05:53Z
置信度 0.70
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Abstract Spiking neural networks (SNNs) are a type of artificial neural networks in which communication between neurons is only made of events, also called spikes. This property allows neural networks to make asynchronous and sparse computations and therefore …
crossref
Florent De Geeter, Damien Ernst, Guillaume Drion
2024-05-03T22:27:50Z
置信度 0.70
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Sarah Sharif, Hossein Karimkhani, Yaser M. Banad
2024-03-11T19:01:37Z
置信度 0.70
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crossref
2025-11-28T21:10:51Z
置信度 0.70
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Abstract Designing algorithms for versatile AI hardware that can learn on the edge using both labeled and unlabeled data is challenging. Deep end-to-end training methods incorporating phases of self-supervised and supervised learning are accurate and adaptable…
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Dongshu Liu, Jérémie Laydevant, Adrien Pontlevy, Damien Querlioz 等
2024-10-29T22:54:28Z
置信度 0.70
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crossref
2025-11-28T21:10:51Z
置信度 0.70
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crossref
Kewei Zhou, Ziming Wang, Zhihao Chen, Xin Wang
2025-05-19T17:52:05Z
置信度 0.70
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crossref
Ali Siddique, Mang I. Vai, Sio Hang Pun
2023-07-08T15:02:18Z
置信度 0.70
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crossref
Ali Akbar Firoozi, Ali Asghar Firoozi
2024-07-26T13:01:53Z
置信度 0.70
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crossref
Lei Deng, Huajin Tang, Kaushik Roy
2024-10-03T04:39:11Z
置信度 0.70
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Abstract Reinforcement learning (RL) faces substantial challenges when applied to real-life problems, primarily stemming from the scarcity of available data due to limited interactions with the environment. This limitation is exacerbated by the fact that RL of…
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Cristiano Capone, Paolo Muratore
2024-06-27T22:26:09Z
置信度 0.70
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crossref
Bokyung Kim, Parshva Mehta, Yiran Chen
2026-01-12T18:21:00Z
置信度 0.70
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crossref
Debanjan Bhowmik
2024-07-15T14:02:06Z
置信度 0.70
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crossref
Wenju Wang, Gang Chen, Haoran Zhou, Elena Goi
2024-01-21T06:48:32Z
置信度 0.70
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crossref
Brian Millikan, Lauren Reinerman-Jones, Daniel Barber
2025-11-17T18:39:19Z
置信度 0.70
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The increasing amount of data in the era of artificial intelligence imposes higher demands on the computational power of neural networks, and in order to fulfill this demand, there is a pressing need to overcome the limitations imposed by the von Neumann archi…
crossref
Luwei Fan
2025-01-10T04:48:26Z
置信度 0.70
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crossref
Yidi Deng, Lan Zhou, Jinjun Wu, Zhu Zhang 等
2025-05-19T17:52:05Z
置信度 0.70
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crossref
Wenxiao Wang, Yang Li, Jiewei Chen
2024-08-09T17:18:24Z
置信度 0.70
-
crossref
James B. Aimone, Ojas Parekh, Cynthia A. Phillips, Ali Pinar 等
2019-09-12T14:21:08Z
置信度 0.70
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crossref
Hyeryung Jang, Osvaldo Simeone
2019-04-17T16:01:56Z
置信度 0.70
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crossref
Laura Capatina, Alexandra Cernian, Mihnea Alexandru Moisescu
2023-08-17T17:20:48Z
置信度 0.70
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crossref
2026-07-06T19:15:47Z
置信度 0.70
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crossref
Shahzada Ahmad, Dani S. Assi, Mahdi Gassara, Samrana Kazim 等
2025-12-17T09:40:46Z
置信度 0.70
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crossref
Debanjan Bhowmik
2024-07-15T14:02:06Z
置信度 0.70
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crossref
Jeffrey L. Krichmar, Hiroaki Wagatsuma
2012-02-06T06:03:07Z
置信度 0.70
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crossref
Paschalis Gkoupidenis
2023-02-01T09:31:42Z
置信度 0.70
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crossref
Disha Maheshwari, Aaron Young, Prasanna Date, Shruti Kulkarni 等
2024-01-15T20:56:12Z
置信度 0.70
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crossref
Felix Staudigl, Rainer Leupers
2026-01-22T14:21:54Z
置信度 0.70
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crossref
Priya Vij, Ashu Nayak
2026-08-31T19:14:00Z
置信度 0.70
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crossref
Wen Zhou, James Tan, Johannes Feldmann, Harish Bhaskaran
2024-01-18T15:12:19Z
置信度 0.70
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crossref
Weihong Shen, Qiming Zhang
2024-01-18T15:12:33Z
置信度 0.70
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crossref
2026-02-03T21:08:48Z
置信度 0.70
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As the pace of complementary metal oxide semiconductor (CMOS) scaling slows down and Moore's law approaches its limit, optoelectronics has emerged as a promising solution for next‐generation computing hardware. Optoelectronic systems are appealing due to their…
crossref
Jinxian Li, Runyu Hu, Fengyu Wang, Jiabin Shen 等
2025-06-23T09:38:26Z
置信度 0.70
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crossref
2024-02-05T14:10:16Z
置信度 0.70
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crossref
K. Ramkumar, V. Prabhakar, V. Agrawal, L. Hinh 等
2020-06-30T21:20:26Z
置信度 0.70
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The exponentially improving performance of digital computers has recently slowed due to power consumption issues resulting from the von Neumann bottleneck. In contrast, neuromorphic computing circumvents these limitations by spatially co-locating logic and mem…
crossref
Mark C Hersam
2025-11-24T08:16:10Z
置信度 0.70
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crossref
A. Olivares Cruz, E.S. Espinoza, L.E. Ramos Velasco, O.A. García Alcántara 等
2025-11-10T23:42:36Z
置信度 0.70
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crossref
B.F. Yang, D. Wang, J. Wang, Z.Y. Zhou 等
2023-09-01T17:23:28Z
置信度 0.70
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crossref
Jian Xiao, Yiyin Hu, Rongli Shao
2024-03-19T18:09:52Z
置信度 0.70
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Abstract The pursuit of energy-efficient and adaptive artificial intelligence (AI) has positioned neuromorphic computing as a promising alternative to conventional computing. However, achieving learning on these platforms requires techniques that prioritize lo…
crossref
Jesús García Fernández, Nasir Ahmad, Marcel van Gerven
2026-06-17T22:50:26Z
置信度 0.70
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Abstract In this work, low-power RRAM (Resistive random-access memory) devices were characterized by a SiO 2 layer serving as an oxygen scavenging barrier, which suppresses conductive filament overgrowth and reduces operation current and power consumption. Add…
crossref
Minki Kim, Sungjoon Kim, Sungmin Hwang
2025-09-02T22:48:43Z
置信度 0.70
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Abstract The emerging field of neuromorphic computing for edge control applications poses the need to quantitatively estimate and limit the number of spiking neurons, to reduce network complexity and optimize the number of neurons per core and hence, the chip …
crossref
Shreyan Banerjee, Luna Gava, Aasifa Rounak, Vikram Pakrashi
2025-10-06T22:50:06Z
置信度 0.70
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crossref
Ricky J. Sethi, Amit K. Roy-Chowdhury, Saad Ali Robotics
2010-02-02T15:27:37Z
置信度 0.70
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Abstract Aspect term extraction (ATE) identifies aspect terms in review sentences, a key subtask of sentiment analysis. It is a sequence labeling task that aims to identify aspect expressions within opinionated text. While most existing approaches predominantl…
crossref
Abhishek Kumar Mishra, Arya Somasundaram, Anup Das, Nagarajan Kandasamy
2026-04-28T22:52:18Z
置信度 0.70
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crossref
Anatole Moureaux, Anthony Lopes, Lindiomar Borges de Avila, Flavio Abreu Araujo
2026-05-28T17:55:45Z
置信度 0.70
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crossref
Murat Isik, Newton Howard, Sols Miziev, Wiktoria Pawlak
2024-09-09T17:35:05Z
置信度 0.70
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crossref
Swagath Venkataramani, Ashish Ranjan, Kaushik Roy, Anand Raghunathan
2014-08-01T20:13:39Z
置信度 0.70
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As a promising alternative to conventional computing paradigms, the neuromorphic computing has been demonstrated by using various artificial synaptic devices. Due to the excellent capability for the conductance modulation, the ferroelectric thin film transisto…
crossref
Yao Dong, Guangtan Miao, Wenlan Xiao, Chunyan You 等
2025-04-23T12:51:37Z
置信度 0.70
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This study, Neuromorphic Adaptation and Cognitive Parallelism, is a core output of the VerbaTerra Project, which seeks to unify neuroscience, linguistics, anthropology, and artificial intelligence under the principle of resonant coherence — the alignment of fe…
crossref
Harshit Gupta
2025-11-20T11:26:46Z
置信度 0.70
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crossref
Farah Baracat, Giacomo Indiveri, Elisa Donati
2026-01-14T20:38:47Z
置信度 0.70
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crossref
Ziwei Li, Jianyang Shi, Nan Chi
2024-01-21T06:48:33Z
置信度 0.70
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crossref
Jinwoo Hwang, Junho Sung, Eunho Lee, Wonbong Choi
2025-03-17T13:36:16Z
置信度 0.70
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crossref
Enrique Barba Roque, Luis Cruz
2025-09-30T17:37:14Z
置信度 0.70
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crossref
ChangMin Ye, Doo Seok Jeong
2025-06-27T17:42:19Z
置信度 0.70
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crossref
Jesus Armando Garcia Franco, Juan Luis del Valle Padilla, Susana Ortega Cisneros
2014-01-10T20:07:14Z
置信度 0.70
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crossref
Rongyang Xu, Shabnam Taheriniya, Akhil Varri, Frank Brückerhoff-Plückelmann 等
2024-09-02T17:34:14Z
置信度 0.70
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crossref
Y. Katayama, T. Yamane, D. Nakano, R. Nakane 等
2016-02-03T12:35:14Z
置信度 0.70
-
crossref
Hongyu Chen, Lihua Tan, Xin Wang, Chen Zhao
2025-05-19T17:52:05Z
置信度 0.70
-
Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of attention lately due to its promise of reducing the computational energy, latency, as well as learning complexity in artificial neural networks. Taking inspiration from neuros…
crossref
Nitin Rathi, Indranil Chakraborty, Adarsh Kosta, Abhronil Sengupta 等
2022-11-17T10:05:37Z
置信度 0.70
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crossref
Seungjun Yim, Hyung Bin Park, Jaehoon Kim
2026-01-07T00:17:28Z
置信度 0.70
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crossref
Jung-Kyu Lee, Yongjin Park, Euncho Seo, Woohyun Park 等
2025-03-25T17:46:23Z
置信度 0.70
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crossref
Philipp Dauer, Milena Czierlinski, Sebastian Billaudelle, Andreas Grübl 等
2023-06-29T17:21:05Z
置信度 0.70
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crossref
Abhronil Sengupta, Priyadarshini Panda, Anand Raghunathan, Kaushik Roy
2016-03-17T16:29:07Z
置信度 0.70
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crossref
Bruno U. Pedroni, Stephen R. Deiss, Nishant Mysore, Gert Cauwenberghs
2021-02-12T21:34:26Z
置信度 0.70
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Abstract The human visual system encodes optical information perceived by photoreceptors in the retina into neural spikes and then processes them by the visual cortex, with high efficiency and low energy consumption. Inspired by this information processing mod…
crossref
Juan Wen, Zhen-Ye Zhu, Xin Guo
2023-03-01T22:29:33Z
置信度 0.70
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crossref
Jing Han, Guici Chen, Guodong Zhang
2021-11-29T20:59:32Z
置信度 0.70
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Abstract Percolating networks of nanoparticles (PNNs) are self-assembled nanoscale systems that possess brain-like characteristics that are useful for information processing, particularly within a reservoir computing (RC) framework. Previous work has successfu…
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Zachary E Heywood, Joshua B Mallinson, Philip J Bones, Simon A Brown
2024-08-23T22:51:48Z
置信度 0.70
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crossref
Balachandran Swaminathan, Jack Sampson
2026-01-21T21:07:17Z
置信度 0.70
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crossref
Amos Sironi
2022-11-02T08:32:12Z
置信度 0.70
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crossref
Dingzhou Cui, Zhiyuan Zhao, Fugu Tian, Wenbo Chen 等
2025-05-30T11:20:27Z
置信度 0.70