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I present a complete Sim-to-Real pipeline for quadruped locomotion using biologically grounded spiking neural networks (SNNs) on a €100 Freenove Robot Dog Kit (FNK0050) with a Raspberry Pi 4. The system employs 232 Izhikevich neurons with reward-modulated spik…
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Marc Hesse
2026-07-11T06:06:16Z
置信度 0.70
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Adaptive multiscale simulations, such as adaptive QM/MM, are indispensable for investigating complex solution dynamics but historically suffer from a fundamental dilemma: the dynamic exchange of identical solvent molecules across different model resolutions in…
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Takuma Ikeda, Hiroshi C. Watanabe, Haruyuki Nakano
2026-07-23T14:28:27Z
置信度 0.70
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Deep neural networks (DNNs) possess strong feature extraction abilities and have been widely used across various applications, serving as a core component of current artificial intelligence systems. However, the complex data communication within DNNs greatly l…
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Zhenjiao Chen, Zehao Wang, Wentao Xu
2026-06-24T07:49:55Z
置信度 0.70
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crossref
2026-04-11T21:11:18Z
置信度 0.70
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A novel convolutional neural network-based super-resolution (SR) method was proposed to accurately predict high-resolution flow fields from coarse-grid computational fluid dynamics (CFD) results. To mitigate boundary artifacts caused by transposed convolution,…
crossref
Tieying Li, Changfu You
2026-05-06T13:10:21Z
置信度 0.70
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Ganesh Immanni, Rajeev Kumar, Anurag Goel
2026-07-29T19:13:09Z
置信度 0.70
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crossref
Ji Lyu
2026-04-16T07:12:56Z
置信度 0.70
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crossref
Tao Zhang
2026-05-26T23:51:17Z
置信度 0.70
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crossref
2026-05-28T21:09:57Z
置信度 0.70
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Abstract Based on the uncertainty and control effect of electronic DC motors, a neural network algorithm, fuzzy control, and fuzzy neural network are designed. First, a small signal model controlled by a virtual direct filter motor is developed, and the stabil…
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Hongmiao Wang
2026-02-24T12:40:49Z
置信度 0.70
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Accurately solving the nuclear Schrödinger equation for molecular complexes exhibiting noncovalent interactions remains a challenge due to the exponential scaling of basis sets and the presence of strongly anharmonic, large-amplitude motions. Recently, we prop…
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Shuaishuai Zhao, Dong H. Zhang
2026-06-19T08:48:28Z
置信度 0.70
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Deteksi suara dan pengenalan kata kunci dalam sinyal audio telah menjadi bidang penelitian yang berkembang pesat karena aplikasinya yang luas, mulai dari pengawasan audio cerdas hingga sistem interaksi manusia-komputer. Penelitian ini bertujuan untuk mengemban…
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NORITA SINAGA, Imam Riadi, Herman
2026-07-11T00:00:43Z
置信度 0.70
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This paper presents a virtual boundary integral neural network (VBINN) for three-dimensional exterior acoustic problems. The method introduces a virtual boundary within the scatterer or vibrating body and represents the associated source density using a neural…
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Jiahao Li, Qiang Xi, Ilia Marchevsky, Zhuojia Fu
2026-06-29T12:37:41Z
置信度 0.70
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Abstract Origami mechanisms excel in space and material utilization, but their design variables involve the coupling of continuous and discrete variables, complicating reverse engineering—especially for polygons with dis crete side counts. Traditional numerica…
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Shijun Li
2026-03-18T01:47:20Z
置信度 0.70
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crossref
2026-08-11T21:06:19Z
置信度 0.70
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Abstract nn-based transistor models have proven to be a promising solution to accelerate device modeling. Although these models demonstrated remarkable speedup in circuit simulations, they were not rigorously tested in complex tasks within standard EDA tool fl…
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Rodion Novkin, Hussam Amrouch
2026-03-17T16:41:47Z
置信度 0.70
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Turbidites have been widely studied as indicators of the occurrences and magnitudes of paleo-tsunamis and paleo-earthquakes. Inversion to estimate flow conditions from turbidites offers valuable insights into the magnitudes of paleo-seismic and tsunami events.…
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Seiya Fujishima, Hajime Naruse
2026-01-03T15:35:27Z
置信度 0.70
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Vishnudatta Indraganti, Anirban Dasgupta, Manish Bhatt
2026-08-17T19:13:17Z
置信度 0.70
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This paper analyzes domestic and international sources confirming the potential of neural network technologies for solving user experience optimization problems in mobile applications. A comprehensive approach is proposed, including selecting the optimal combi…
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Danil Nikolajevich Zinovjev, Mariya Anatoljevna Bogomolova
2026-08-28T09:27:06Z
置信度 0.70
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Masashi Arita, Atsushi Tsurumaki-Fukuchi, Yasuo Takahashi
2018-04-05T06:33:36Z
置信度 0.70
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crossref
Xinyu Wu, Vishal Saxena, Kehan Zhu
2015-10-01T21:48:02Z
置信度 0.70
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Convolutional Neural Network forms the base of all computer vision applications. Uses like self-driving cars, object recognition, face recognition, etc. Simple neural networks struggle with images because they are slow at training and processing and have a lar…
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Shrutika Adole, Prof. K. P. Barabde
2026-01-20T11:28:06Z
置信度 0.70
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Farida Gamal, Ayman El-Badawy
2026-03-10T19:50:57Z
置信度 0.70
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crossref
Joshua Xia, Adam Birchfield
2026-05-15T19:51:24Z
置信度 0.70
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Abhay Kumar Dubey, Sukwinder Singh
2026-05-21T19:40:52Z
置信度 0.70
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Akram Karimi Zarandi, Ali Fahim
2026-05-15T03:06:29Z
置信度 0.70
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Song Kaiwen
2026-05-20T19:48:58Z
置信度 0.70
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Xiaoran Wang, Yun Zhang
2026-06-30T20:25:22Z
置信度 0.70
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The development of interdisciplinary academic leaders is crucial for universities aiming to enhance collaboration, innovation, and knowledge integration across disciplines. Research introduces a deep learning-based framework, Wingsuit Flying Search-driven Dyna…
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Qiuyue Ling
2026-08-28T22:26:46Z
置信度 0.70
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Sonam Gour
2025-10-17T10:23:27Z
置信度 0.70
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crossref
Wang Hanyue
2026-08-17T06:53:28Z
置信度 0.70
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crossref
2026-05-12T09:34:06Z
置信度 0.70
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crossref
2026-01-19T02:04:26Z
置信度 0.70
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crossref
Kenneth McDonald, Edward Daughtery, Zhihua Qu, Trevor McCants 等
2026-05-22T19:33:47Z
置信度 0.70
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Simon Michael Papalexiou, Antonios Mamalakis
2025-11-28T07:43:22Z
置信度 0.70
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crossref
Wesley Forbes, Min Long
2026-02-20T16:30:03Z
置信度 0.70
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Wellington D. Almeida, Ajalmar R. Rocha Neto
2026-06-01T19:33:50Z
置信度 0.70
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This publication explores the possibility of implementing a colour classifier for various types of Bulgarian honey. For this purpose, spectroradiometric measurement is used based on a measuring device from JETI Technische Instrumente GmbH – Specbos1201 providi…
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Ventsislav Simonov
2026-05-25T07:47:37Z
置信度 0.70
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Lei Wu, Hongyuan Zhang
2026-05-30T07:33:17Z
置信度 0.70
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crossref
2026-06-22T03:19:49Z
置信度 0.70
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Feng Zhou, Shenglan Chen
2026-04-24T19:44:36Z
置信度 0.70
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This paper explores the possibility of improving the efficiency of fifth-generation communication networks through the use of intelligent forecasting methods. The aim of the study is to apply a nonlinear autoregressive neural network (NARNN) for the analysis a…
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Behruz Saidov
2026-04-15T05:21:09Z
置信度 0.70
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Massimiliano Ferrara
2026-06-02T16:28:33Z
置信度 0.70
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crossref
Shaziya Islam, Ansar Isak Sheikh, Jayapal Lande, Mayank Srivastava 等
2026-04-23T19:57:35Z
置信度 0.70
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crossref
2018-12-14T02:49:52Z
置信度 0.70
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Yongbo Zhou, Sicheng Pan, Peilong Yu, Han Wei
2026-08-04T01:58:50Z
置信度 0.70
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This study introduces a multi-similarity neural network framework for paraphrase detection, an important task in natural language processing that identifies whether two sentences convey the same meaning using different expressions. The proposed method combines…
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Emad Nabil
2026-08-11T16:12:11Z
置信度 0.70
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Jiyuan Li, Jianwu Dang, Na Jiang, Jingyu Yang
2026-06-16T09:18:32Z
置信度 0.70
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crossref
Jyoti Saini, Jyoti Rani, Nitasha Tayal
2026-05-01T19:51:19Z
置信度 0.70
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crossref
Kiruthikan Sithamparanathan, Jeff Dix
2026-05-28T22:26:58Z
置信度 0.70
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crossref
Qingguang Li, Guangluan Xu
2025-11-24T07:35:20Z
置信度 0.70
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crossref
Eden Luzon, Guy Amit, Roy Weiss, Torsten Krauß 等
2026-05-13T16:20:44Z
置信度 0.70
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crossref
Jing Jia
2026-06-02T12:09:11Z
置信度 0.70
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crossref
Dip Roy, Rajiv Misra, Sanjay Kumar Singh
2026-03-27T03:52:45Z
置信度 0.70
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crossref
S.W. Al-Sayegh
2008-07-18T11:27:21Z
置信度 0.70
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crossref
Mahsa Banadkooki, Martin Bogdan
2026-03-27T11:13:44Z
置信度 0.70
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crossref
Zahraa Haidar Sharba, Hawraa Abbas Almurieb
2026-07-24T19:05:55Z
置信度 0.70
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crossref
Sasan Soltani, Farshid Khojasteh, Majid Alavi, Majid Haghverdi
2026-08-28T12:53:30Z
置信度 0.70
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Riya Bansal, Nikhil Kumar Rajput, Megha Khanna
2026-05-09T23:09:45Z
置信度 0.70
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crossref
Hasmik Osipyan, Bosede Iyiade Edwards, Adrian David Cheok
2022-02-17T12:22:57Z
置信度 0.70
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crossref
Henok Moges, Deshendran Moodley
2026-03-13T07:25:13Z
置信度 0.70
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crossref
Leimin Wang, Chuan-Ke Zhang
2022-05-27T16:57:57Z
置信度 0.70
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Penelitian ini bertujuan untuk membangun sistem klasifikasi tingkat kematangan buah pisang tanduk menggunakan metode Convolutional Neural Network (CNN) berbasis Transfer Learning dengan arsitektur MobileNetV2 dan EfficientNetB0. Dataset yang digunakan terdiri …
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Dela_rizqi Fitriani, Dela Rizqi Fitriani
2026-07-11T00:03:24Z
置信度 0.70
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Sparse neural networks are essential for deploying deep learning models on resource-limited and latency-sensitive platforms, where efficiency must be improved without compromising predictive performance. While the Graph-Constrained Neural Multi-Objective Evoluti…
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Collen Channer, Syed Sajjad Hussain Rizvi, Peter Ndajah, Otis Osbourne
2026-07-06T10:50:42Z
置信度 0.70
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Abstract Colorectal polyps are precancerous lesions with a high risk of developing into cancer if left untreated. Colonoscopy is the gold standard for detecting and removing these polyps, but it has high miss rates, especially for small and flat polyps. Deep l…
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Khaled ELKarazle, Valliappan Raman, Caslon Chua, Patrick Then
2026-03-17T03:28:27Z
置信度 0.70
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crossref
Varun Sahni
2026-07-22T19:15:10Z
置信度 0.70
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Abstract We investigate how training regimes and sample size affect the performance of neural networks in financial forecasting. Using volatility forecasts for more than 10,000 stocks, we find that, within the specifications studied, performance gains from sam…
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Chen Liu, Minh-Ngoc Tran, Chao Wang, Richard Gerlach 等
2026-07-23T11:51:15Z
置信度 0.70
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Biomedical event extraction (BEE) is a significant task which plays an important role for some downstream biomedical applications. The recent works have applied joint methods using Graph Convolutional Network (GCN) based on the dependency tree to capture non-l…
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Fangyong Tan, Jing Zhang, Ruifeng Zhao
2026-06-29T11:25:30Z
置信度 0.70
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crossref
Xiang-Sheng Wang, Chisheng Wang
2026-05-19T22:02:24Z
置信度 0.70
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crossref
Guillem Boquet, Edwar Macias, Antoni Morell, Javier Serrano 等
2020-12-18T21:54:18Z
置信度 0.70
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Abstract Memristors, emerging non-volatile memory devices, have shown promising potential in neuromorphic hardware designs, especially in spiking neural network (SNN) hardware implementation. Memristor-based SNNs have been successfully applied in a wide range …
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Jinqi Huang, Alexantrou Serb, Spyros Stathopoulos, Themis Prodromakis
2023-01-13T22:28:01Z
置信度 0.70
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crossref
Ľubica Beňušková, Slavomír Eštok
2015-08-18T16:05:01Z
置信度 0.70
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crossref
Jan Zielasko, Rolf Drechsler
2026-06-04T19:53:10Z
置信度 0.70
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crossref
Manh V. Nguyen, Liang Zhao, Shaoen Wu
2026-07-03T19:49:45Z
置信度 0.70
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crossref
Florita Siritean, Loretta Ichim, Dan Popescu
2026-03-10T19:50:57Z
置信度 0.70
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crossref
Evgenia Slivko, Kay Bierzynski, Lorenzo Servadei, Robert Wille
2026-05-05T20:01:05Z
置信度 0.70
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crossref
Xiang-Sheng Wang, Chisheng Wang
2026-05-19T22:02:38Z
置信度 0.70
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crossref
2020-12-22T23:12:00Z
置信度 0.70
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crossref
Lilan Chen, Yufeng Zhou
2026-08-14T19:30:51Z
置信度 0.70
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crossref
Ya-Qi Lin, Ming-Feng Ge, Teng-Fei Ding, Ziqi Zhu 等
2019-10-17T23:19:42Z
置信度 0.70
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crossref
D. V. Budko
2026-03-30T18:56:56Z
置信度 0.70
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crossref
Mamadou Kanouté, Florence Forbes
2026-07-20T01:35:31Z
置信度 0.70
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crossref
Zhendong Chen, Lejian Liao, Siu Cheung Hui, Heyan Huang
2025-08-08T02:16:09Z
置信度 0.70
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crossref
Vasily D. Voroshchenko, Michael A. Gorkavyy
2026-08-18T19:03:54Z
置信度 0.70
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crossref
Shiping Wen, Zhigang Zeng
2011-10-29T08:52:39Z
置信度 0.70
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crossref
2022-08-30T03:45:01Z
置信度 0.70
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crossref
2022-12-01T06:22:51Z
置信度 0.70
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crossref
Hiramatsu
2003-01-13T18:46:33Z
置信度 0.70
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crossref
Awatef Khoury, Avi Mendelson, Ori Shacham-Barr
2026-05-07T19:51:19Z
置信度 0.70
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crossref
Shiyuan Zhang, Shan Lu, Qing Li
2026-04-24T15:43:45Z
置信度 0.70
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Abstract Electrocardiogram (ECG) signal classification plays significant role in early diagnosis, continuous monitoring cardiovascular diseases. The existing deep learning methods often rely on single-domain feature extraction methods, restricting capability o…
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Harshini Polavarapu, Rajesh Mitukula
2026-06-22T22:53:15Z
置信度 0.70
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Igor Livshin
2019-04-12T15:05:25Z
置信度 0.70
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Pavan Mohan Neelamraju, Raghukanth STG
2026-03-22T15:56:46Z
置信度 0.70
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crossref
Jhansi Lakshmi Vigrahala, Abinash Pujahari
2026-03-25T00:18:19Z
置信度 0.70
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crossref
Dhanyavathi A, Veena M B
2026-06-26T17:36:33Z
置信度 0.70
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crossref
2022-12-01T18:12:48Z
置信度 0.70
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crossref
Yuxin Jiang, Song Zhu
2024-07-06T16:01:52Z
置信度 0.70
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crossref
A Hartstein
2015-08-18T20:03:58Z
置信度 0.70
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crossref
Jia Jia, Xia Huang, Yuxia Li, Zhen Wang
2018-01-05T17:56:39Z
置信度 0.70
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crossref
2018-03-24T08:06:28Z
置信度 0.70