Výsledky vyhledávání - novel stack deep conventional autoencoder

Precise single step and multistep short-term photovoltaic parameters forecasting based on reduced deep convolutional stack autoencoder and minimum variance multikernel random vector functional network Autor Sahani, Mrutyunjaya, Choudhury, Sasmita, Siddique, Marif Daula, Parida, Tanmoy, Dash, Pradipta Kishore, Panda, Sanjib Kumar

“… To address this, we have developed a novel hybrid model: a reduced deep convolutional stack autoencoder with a minimum variance multikernel random vector functional link network (RDCSAE-MVMRVFLN…”
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DeepSign: Deep learning for automatic malware signature generation and classification Autor David, Omid E., Netanyahu, Nathan S.

“… The method uses a deep belief network (DBN), implemented with a deep stack of denoising autoencoders, generating an invariant compact representation of the malware behavior…”
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Post-stack seismic impedance inversion based on sparse-coded Mamba seismic model Autor Lin, Yijian, Peng, Suping, Cui, Xiaoqin, Lu, Yongxu

“…Post-stack seismic impedance inversion plays a vital role in reservoir characterization and seismic attribute analysis, enabling the interpretation of lithological properties and the prediction…”
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Deep Learning Frameworks with Applications in Medical Signal and Image Classification Autor Jia, Guangyu

“… The main contributions of this research include: 1) proposing novel deep learning architectures which can improve the classification performance, generalisation ability…”
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DeepSign: Deep Learning for Automatic Malware Signature Generation and Classification Autor Eli, David, Netanyahu, Nathan S

“… The method uses a deep belief network (DBN), implemented with a deep stack of denoising autoencoders, generating an invariant compact representation of the malware behavior…”
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