Suchergebnisse - Cascade stacked autoencoder neural network

Cascade stacked autoencoder neural network for intrusion detection in CAN-FD vehicular network von Devi, V. Anjana, Reddy, P.V. Bhaskar, Ponnada, Sreenu, Kumar, K. Suresh

“… In this work, an Intrusion Detection System (IDS) for Controller Area Network with Flexible Data Rate (CAN-FD …”
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Multi-label classification using a cascade of stacked autoencoder and extreme learning machines von Law, Anwesha, Ghosh, Ashish

“… •Three phase cascade of neural networks for multi-label classification.•Network model includes stacked autoencoders and extreme learning machines …”
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CDAE: A Cascade of Denoising Autoencoders for Noise Reduction in the Clustering of Single-Particle Cryo-EM Images von Lei, Houchao, Yang, Yang

“… In this study, we design an effective cryo-EM image denoising model, CDAE, i.e., a cascade of denoising autoencoders …”
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Prediction of miRNA–Disease Associations by Cascade Forest Model Based on Stacked Autoencoder von Hu, Xiang, Yin, Zhixiang, Zeng, Zhiliang, Peng, Yu

“… Then, the stacked autoencoder is applied for obtaining the underlying feature representation. Finally, the modified cascade forest model is employed to complete …”
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Stacked encoded cascade error feedback deep extreme learning machine network for manufacturing order completion time von Khan, Waqar Ahmed, Masoud, Mahmoud, Eltoukhy, Abdelrahman E. E., Ullah, Mehran

“… To predict the OCT, firstly, the stacked autoencoder is used to generate input connection weights for the network by learning a deep representation of the real …”
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Sparse stacked autoencoder network for complex system monitoring with industrial applications von Deng, Ziwei, Li, Yuxuan, Zhu, Hongqiu, Huang, Keke, Tang, Zhaohui, Wang, Zhen

“… •A fault classification and isolation method based on SAE is proposed for complex system.•Deep learning model formed by AE with sparse and regular constraints …”
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Infomax-based deep autoencoder network for recognition of multi-element geochemical anomalies linked to mineralization von Esmaeiloghli, Saeid, Tabatabaei, Seyed Hassan, Carranza, Emmanuel John M.

“… In recent years, deep autoencoder networks (DANs) have shown enormous potential to achieve state-of-the-art performance for recognizing multi-element geochemical anomalies related to mineralization …”
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Cascade neural network-based joint sampling and reconstruction for image compressed sensing von Zeng, Chunyan, Ye, Jiaxiang, Wang, Zhifeng, Zhao, Nan, Wu, Minghu

“… In this paper, we propose a unified framework, which jointly considers the sampling and reconstruction process for image compressive sensing based on well-designed cascade neural networks …”
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CSO-CNN: circulatory system optimization-based cascade region CNN for fault estimation and driver behavior detection von Priyadharshini, G., Ukrit, M. Ferni

“… Taking these into consideration his paper proposes a novel cascade region convolutional neural network-based circulatory system optimization algorithm (CRCNN++ based CSO …”
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A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data von Xu, Jing, Wu, Peng, Chen, Yuehui, Meng, Qingfang, Dawood, Hussain, Dawood, Hassan

“… Stacked autoencoder (SAE) is used to learn high-level representations in each omics data, then the complex representations are learned by integrating …”
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Target Detection in Clutter/Interference Regions Based on Deep Feature Fusion for HFSWR von Wu, Maokai, Zhang, Ling, Niu, Jiong, Wu, Q. M. Jonathan

“… The algorithm has two stages: preprocessing and target detection. In the preprocessing stage, faster region-based convolutional neural networks Faster R-CNN are designed …”
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Breast cancer cell nuclei classification in histopathology images using deep neural networks von Feng, Yangqin, Zhang, Lei, Yi, Zhang

“… To address this challenge, this paper aims to present a novel deep neural network which performs representation learning and cell nuclei recognition in an end-to-end manner …”
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An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals von Zheng, Zhanpeng, Yin, Zhong, Zhang, Jianhua

“… This study proposes an inter-subject CW classifier, extreme learning machine (ELM)-based deep stacked denoising autoencoder ensemble (ED-SDAE …”
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JSRNN: Joint Sampling and Reconstruction Neural Networks for High Quality Image Compressed Sensing von Zeng, Chunyan, Ye, Jiaxiang, Wang, Zhifeng, Zhao, Nan, Wu, Minghu

“… In the reconstruction sub-network, a cascade network combining stacked denoising autoencoder …”
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Parallel Multistage Wide Neural Network von Xi, Jiangbo, Ersoy, Okan K., Fang, Jianwu, Wu, Tianjun, Wei, Xin, Zhao, Chaoying

“… (RBF) networks, and knowledge transfer (FDRK). In this article, a parallel multistage wide neural network (PMWNN) is presented …”
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Australia's long-term electricity demand forecasting using deep neural networks von Hamedmoghadam, Homayoun, Joorabloo, Nima, Jalili, Mahdi

“… A stacked autoencoder is used in combination with multilayer perceptrons or cascade-forward multilayer perceptrons to predict the nation-wide electricity consumption rates for 1-24 months ahead of time …”
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