Suchergebnisse - "Convolutional Neural Network"

EEGNet: a compact convolutional neural network for EEG-based brain-computer interfaces von Lawhern, Vernon J, Solon, Amelia J, Waytowich, Nicholas R, Gordon, Stephen M, Hung, Chou P, Lance, Brent J

“… Convolutional neural networks (CNNs), which have been used in computer vision and speech recognition to perform automatic feature extraction and classification, have successfully been applied to EEG-based BCIs …”
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EEG-Based Spatio-Temporal Convolutional Neural Network for Driver Fatigue Evaluation von Gao, Zhongke, Wang, Xinmin, Yang, Yuxuan, Mu, Chaoxu, Cai, Qing, Dang, Weidong, Zuo, Siyang

“… In this paper, based on the spatial-temporal structure of multichannel electroencephalogram (EEG) signals, we develop a novel EEG-based spatial-temporal convolutional neural network …”
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MR‐based synthetic CT generation using a deep convolutional neural network method von Han, Xiao

“… We propose in this work a novel deep convolutional neural network (DCNN) method for sCT generation and evaluate its performance on a set of brain tumor patient images …”
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A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer’s disease von Liu, Manhua, Li, Fan, Yan, Hao, Wang, Kundong, Ma, Yixin, Shen, Li, Xu, Mingqing

“… Alzheimer’s disease (AD) is a progressive and irreversible brain degenerative disorder. Mild cognitive impairment (MCI) is a clinical precursor of AD. Although …”
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Three‐dimensional feature maps and convolutional neural network‐based emotion recognition von Zheng, Xiangwei, Yu, Xiaomei, Yin, Yongqiang, Li, Tiantian, Yan, Xiaoyan

“… temporal and spatial feature fusion and classification method with improved convolutional neural networks (CNNs …”
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EEG-Based Cross-Subject Driver Drowsiness Recognition With an Interpretable Convolutional Neural Network von Cui, Jian, Lan, Zirui, Sourina, Olga, Muller-Wittig, Wolfgang

“… In this article, we develop a novel convolutional neural network combined with an interpretation technique that allows sample-wise analysis of important features for classification …”
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Adaptive transfer learning-based multiscale feature fused deep convolutional neural network for EEG MI multiclassification in brain–computer interface von Roy, Arunabha M.

“… However, due to inter-subject variability, inherent complex properties, and low signal-to-noise ratio (SNR …”
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Adaptive transfer learning for EEG motor imagery classification with deep Convolutional Neural Network von Zhang, Kaishuo, Robinson, Neethu, Lee, Seong-Whan, Guan, Cuntai

“… Addressing this, in this paper, we propose 5 schemes for adaptation of a deep convolutional neural network (CNN …”
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Diagnosis of Alzheimer’s Disease via Multi-Modality 3D Convolutional Neural Network von Huang, Yechong, Xu, Jiahang, Zhou, Yuncheng, Tong, Tong, Zhuang, Xiahai

“… In this paper, we propose a convolutional neural network (CNN) to integrate all the multi-modality information included in both T1-MR and FDG-PET images of the hippocampal area, for the diagnosis of AD …”
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Convolutional neural network to identify symptomatic Alzheimer’s disease using multimodal retinal imaging von Wisely, C. Ellis, Wang, Dong, Henao, Ricardo, Grewal, Dilraj S., Thompson, Atalie C., Robbins, Cason B., Yoon, Stephen P., Soundararajan, Srinath, Polascik, Bryce W., Burke, James R., Liu, Andy, Carin, Lawrence, Fekrat, Sharon

“… Background/AimsTo develop a convolutional neural network (CNN) to detect symptomatic Alzheimer’s disease (AD …”
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Convolutional neural network based Alzheimer’s disease classification from magnetic resonance brain images von Jain, Rachna, Jain, Nikita, Aggarwal, Akshay, Hemanth, D. Jude

“… Nowadays, deep learning or particularly convolutional neural network (CNN) is getting more attention due to its state-of-the-art performances in variety of computer vision tasks such as visual object classification, detection and segmentation …”
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Investigating the Use of Pretrained Convolutional Neural Network on Cross-Subject and Cross-Dataset EEG Emotion Recognition von Cimtay, Yucel, Ekmekcioglu, Erhan

“… The aim of this study is to increase the subject-independent recognition accuracy by exploiting pretrained state-of-the-art Convolutional Neural Network …”
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Deep learning based diagnosis of Parkinson’s disease using convolutional neural network von Sivaranjini, S., Sujatha, C. M.

“… The Convolutional Neural Network architecture AlexNet is used to refine the diagnosis of Parkinson’s disease. The MR images are trained …”
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Detection of Hypertrophic Cardiomyopathy Using a Convolutional Neural Network-Enabled Electrocardiogram von Ko, Wei-Yin, Siontis, Konstantinos C, Attia, Zachi I, Carter, Rickey E, Kapa, Suraj, Ommen, Steve R, Demuth, Steven J, Ackerman, Michael J, Gersh, Bernard J, Arruda-Olson, Adelaide M, Geske, Jeffrey B, Asirvatham, Samuel J, Lopez-Jimenez, Francisco, Nishimura, Rick A, Friedman, Paul A, Noseworthy, Peter A

“… ). A convolutional neural network (CNN) was trained and validated using digital 12-lead ECG from 2,448 …”
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AML, ALL, and CML classification and diagnosis based on bone marrow cell morphology combined with convolutional neural network: A STARD compliant diagnosis research von Huang, Furong, Guang, Peiwen, Li, Fucui, Liu, Xuewen, Zhang, Weimin, Huang, Wendong

“… This study proposes using bone marrow cell microscopy images and employs convolutional neural network (CNN …”
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A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification von Zhao, Xinqiao, Zhang, Hongmiao, Zhu, Guilin, You, Fengxiang, Kuang, Shaolong, Sun, Lining

“… convolutional neural network (3D CNN) and the corresponding classification strategy. The 3D representation is generated by transforming EEG signals into a sequence of 2D array which preserves spatial distribution of sampling electrodes …”
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Computer‐aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI von Song, Yang, Zhang, Yu‐Dong, Yan, Xu, Liu, Hui, Zhou, Minxiong, Hu, Bingwen, Yang, Guang

“… ‐aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp‐MRI). Purpose To develop an automatic approach based on deep convolutional neural network (DCNN …”
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A compact and interpretable convolutional neural network for cross-subject driver drowsiness detection from single-channel EEG von Cui, Jian, Lan, Zirui, Liu, Yisi, Li, Ruilin, Li, Fan, Sourina, Olga, Müller-Wittig, Wolfgang

“… •The model can discover biologically explainable features from a diversity of EEG data of different subjects …”
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Automatic ECG Diagnosis Using Convolutional Neural Network von Avanzato, Roberta, Beritelli, Francesco

“… The proposed new neural architecture based on the recent popularity of convolutional neural networks (CNN …”
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A Multi-Stream Convolutional Neural Network for Classification of Progressive MCI in Alzheimer's Disease Using Structural MRI Images von Ashtari-Majlan, Mona, Seifi, Abbas, Dehshibi, Mohammad Mahdi

“… ), is critical since some patients with progressive MCI will develop the disease. We propose a multi-stream deep convolutional neural network fed with patch-based imaging data to classify stable MCI and progressive MCI …”
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