Suchergebnisse - "Convolutional Autoencoder"

Three-Dimensional Convolutional Autoencoder Extracts Features of Structural Brain Images With a “Diagnostic Label-Free” Approach: Application to Schizophrenia Datasets von Yamaguchi, Hiroyuki, Hashimoto, Yuki, Sugihara, Genichi, Miyata, Jun, Murai, Toshiya, Takahashi, Hidehiko, Honda, Manabu, Hishimoto, Akitoyo, Yamashita, Yuichi

“… The purpose of this study was to investigate the efficacy of a 3D convolutional autoencoder (3D-CAE …”
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CAE-MAS: Convolutional Autoencoder Interference Cancellation for Multiperson Activity Sensing With FMCW Microwave Radar von Raeis, Hossein, Kazemi, Mohammad, Shirmohammadi, Shervin

“… Frequency-modulated continuous-wave (FMCW) radars can be used for target tracking, but their collected data are usually accompanied by a significant amount of interference, especially in indoor environments hosting multiple human subjects …”
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Graph-informed convolutional autoencoder to classify brain responses during sleep von Zakeri, Sahar, Makouei, Somayeh, Danishvar, Sebelan

“… To this aim, we pre-processed EEG recordings from 33 healthy subjects. Then, functional connectivity features and recurrence quantification analysis were extracted from sub-bands …”
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A Deep Convolutional Autoencoder for Automatic Motion Artifact Removal in Electrodermal Activity von Hossain, Md-Billal, Posada-Quintero, Hugo F., Chon, Ki H.

“… ) removal technique from electrodermal activity (EDA) signal. Methods: we proposed a deep convolutional autoencoder (DCAE …”
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CAE-MAS: Convolutional Autoencoder Interference Cancellation for Multi-Person Activity Sensing with FMCW Microwave Radar von Raeis, Hossein, Kazemi, Mohammad, Shirmohammadi, Shervin

“… Frequency Modulated Continuous Wave (FMCW) radars can be used for target tracking, but their collected data is usually accompanied by a significant amount of interference, especially in indoor environments hosting multiple human subjects …”
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EEG channel selection-based binary particle swarm optimization with recurrent convolutional autoencoder for emotion recognition von Kouka, Najwa, Fourati, Rahma, Fdhila, Raja, Siarry, Patrick, Alimi, Adel M.

“… Extensive validation on three public effective benchmarks, i.e. DASPS, DEAP, and SEED which are different in channel number used stimuli, and participant ratings, was carried out with subject independent scheme …”
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Detection and localization of myocardial infarction based on a convolutional autoencoder von Sugimoto, Kaiji, Kon, Yudai, Lee, Saerom, Okada, Yoshifumi

“… Twelve-lead electrocardiograms (ECG) are widely used for the diagnosis of myocardial infarction (MI). For MI detection and localization, 12 ECG signals should …”
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Unsupervised defect detection for solar photovoltaic cells based on convolutional autoencoder von Zhang, Yufei, Zhang, Xu, Tu, Dawei

“… Aiming at PV cell EL images, an unsupervised defect detection method was proposed. Specifically, an unsupervised convolutional autoencoder (CAE …”
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Novel Soft Smart Shoes for Motion Intent Learning of Lower Limbs Using LSTM With a Convolutional Autoencoder von Yang, Jiantao, Yin, Yuehong

“… This study presents novel soft smart shoes designed for motion intent learning at unspecified walking speeds using long short-term memory with a convolutional autoencoder …”
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Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder von Zhao, Yu, Dong, Qinglin, Chen, Hanbo, Iraji, Armin, Li, Yujie, Makkie, Milad, Kou, Zhifeng, Liu, Tianming

“… •A new deep 3D convolutional autoencoder to model brain network maps.•Derived fine-granularity functional brain network atlases …”
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Segmentation of Brain Tumors from MRI Images Using Convolutional Autoencoder von Badža, Milica M., Barjaktarović, Marko Č.

“… The use of machine learning algorithms and modern technologies for automatic segmentation of brain tissue increases in everyday clinical diagnostics. One of …”
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DOA Estimation Based on Convolutional Autoencoder in the Presence of Array Imperfections von Chang, Dah-Chung, Liu, Yan-Ting

“… Array imperfections may exist in an antenna system subject to non-ideal design and practical limitations …”
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An Integrated Method Using a Convolutional Autoencoder, Thresholding Techniques, and a Residual Network for Anomaly Detection on Heritage Roof Surfaces von Zhang, Yongcheng, Kong, Liulin, Antwi-Afari, Maxwell Fordjour, Zhang, Qingzhi

“… The paper proposes an integrated method that employs a convolutional autoencoder, thresholding techniques, and a residual network to automatically detect anomalies on heritage roof surfaces …”
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Non-Invasive Continuous Real-Time Blood Glucose Estimation Using PPG Features-based Convolutional Autoencoder with TinyML Implementation von Ali, Noor Faris, Aldhaheri, Alyazia, Wodajo, Bethel, Alshamsi, Meera, Alshamsi, Shaikha, Atef, Mohamed

“… In this paper, we developed a convolutional autoencoder for non-invasive continuous monitoring of blood glucose levels (BGL …”
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A Convolutional Autoencoder Approach To Learn Volumetric Shape Representations For Brain Structures von Yu, Evan M., Sabuncu, Mert R.

“… Thanks to the adopted autoencoder framework, inter-subject differences are automatically enhanced in the learned representation, while intra-subject variances are minimized …”
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Comparative Analysis of Potato Leaf Disease Detection Using Convolutional AEVGG19 Model Based on Deep Learning von Kalaiyarasi, M., Saravanan, S., Bejaxhin, A. Bovas Herbert

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Compression of EMG Signals Using Deep Convolutional Autoencoders von Dinashi, Kimia, Ameri, Ali, Akhaee, Mohammad Ali, Englehart, Kevin, Scheme, Erik

“… As a solution, this work proposes a new method for EMG data compression using deep convolutional autoencoders (CAE …”
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Weighted salp swarm algorithm with deep learning-powered cyber-threat detection for robust network security von Althobaiti, Maha M., Escorcia-Gutierrez, José

“… The fast development of the internet of things has been associated with the complex worldwide problem of protecting interconnected devices and networks. The …”
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Breast Cancer Detection using Convolutional Autoencoder with Hybrid Deep Learning Model von S. Ranjana, A. Meenakshi

“… The most deadly cancer among women in world is Breast cancer (BC). The early identification of malignancy helps in the disease diagnosis and it can help …”
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Convolutional Autoencoder based Stress Detection using Soft Voting von Choi, Eun Bin, Kim, Soo Hyung

“… of classification models can vary greatly depending on the subject …”
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