Výsledky vyhledávání - sparse conventional autoencoder (((same OR sage) OR cae))

A Novel Convolutional Autoencoder-Based Clutter Removal Method for Buried Threat Detection in Ground-Penetrating Radar Autor Temlioglu, Eyyup, Erer, Isin

“… A new clutter removal method based on convolutional autoencoders (CAEs) is introduced. The raw GPR image is encoded via successive convolution and pooling layers and then decoded to provide the clutter-free GPR image…”
Získat plný text

Enhanced fault detection in digital VLSI circuits using convolutional autoencoders Autor Savalam, Chandrasekhar, Medisetti, Sanjay, Korapati, Prasanti

“… A Convolutional Autoencoder (CAE) is employed to extract spatial and structural features from circuit test patterns, effectively reducing dimensionality while preserving fault-related information…”
Získat plný text

Deep Learning Augmented Data Assimilation: Reconstructing Missing Information with Convolutional Autoencoders Autor Wang, Yueya, Shi, Xiaoming, Lei, Lili, Fung, Jimmy Chi-Hung

“… By training a convolutional autoencoder (CAE) with a long simulation at a coarse “forecast” resolution (T63), we obtained a deep learning approximation…”
Získat plný text

Deep hyperspectral clustering using attention-enhanced 3D-2D convolutional autoencoder for mineral mapping Autor Peyghambari, Sima, Zhang, Yun

“… However, the most commonly used 3D-convolutional autoencoder (3D-CAE) models have several disadvantages, including intensive computational costs and the potential to lose spatial information…”
Získat plný text

Masked autoencoder for highly compressed single-pixel imaging Autor Liu, Haiyan, Chang, Xuyang, Yan, Jun, Guo, Pengyu, Xu, Dong, Bian, Liheng

“… In this way, we can effectively decrease 75% modulation patterns experimentally. To reconstruct the entire image, we designed a highly sparse input and extrapolation network consisting of two modules…”
Zjistit podrobnosti o přístupu

Sensor-Driven Surrogate Modeling and Control of Nonlinear Dynamical Systems Using FAE-CAE-LSTM and Deep Reinforcement Learning Autor Kherad, Mahdi, Moayyedi, Mohammad Kazem, Fotouhi-Ghazvini, Faranak, Vahabi, Maryam, Fotouhi, Hossein

“… This paper presents a sensor-driven, non-intrusive reduced-order modeling (NIROM) framework called FAE-CAE-LSTM, which combines convolutional and fully connected autoencoders with a long short-term memory (LSTM) network…”
Získat plný text

Deep learning for pixel-level image fusion: Recent advances and future prospects Autor Liu, Yu, Chen, Xun, Wang, Zengfu, Wang, Z. Jane, Ward, Rabab K., Wang, Xuesong

“…•The difficulties that exist in conventional image fusion research are analyzed.•The advantages of deep learning (DL…”
Získat plný text

Image fusion based on shift invariant shearlet transform and stacked sparse autoencoder Autor Wang, Peng-Fei, Luo, Xiao-Qing, Li, Xin-Yi, Zhang, Zhan-Cheng

“…Stacked sparse autoencoder is an efficient unsupervised feature extraction method, which has excellent ability in representation of complex data…”
Získat plný text

Application of the robust autoencoder to reduce reverberation and facilitate underwater target tracking Autor Xiang, Wenjie, Song, Zhongchang, Gao, Zhanyuan, Yang, Wuyi, Zhang, Boyu, Yang, Hongjun, Tu, Jianqiu, Li, Baoyu, Zhang, Hairui, Zhang, Yu

“… To improve the accuracy of target detection under reverberation conditions, a novel sparse track-before-detect algorithm integrating a robust autoencoder and a particle filter (PF-RAE-TBD…”
Získat plný text

Seismic noise attenuation by signal reconstruction: an unsupervised machine learning approach Autor Gao, Yang, Zhao, Pingqi, Li, Guofa, Li, Hao

“…ABSTRACT Random noise attenuation is an essential step in seismic data processing for improving seismic data quality and signal‐to‐noise ratio. We adopt an…”
Získat plný text

ProteinVAE: Variational AutoEncoder for Translational Protein Design Autor Lyu, Suyue, Shahin Sowlati-Hashjin, Garton, Michael

“… This means that they are often not suitable for generating proteins with the most potential for high clinical impact, due to the additional challenges of sparse data and large size many…”
Získat plný text

Advancing deep learning-based dimension reduction for complex three-dimensional saturation data in large-scale geological carbon storage Autor Wang, Hongsheng, Hosseini, Seyyed A.

“… However, conventional DR methods, such as principal component analysis (PCA) and convolutional autoencoders (CAE…”
Získat plný text

Leveraging explainable artificial intelligence for early detection and mitigation of cyber threat in large-scale network environments Autor Nalinipriya, G., Rama Sree, S., Radhika, K., Laxmi Lydia, E., Karim, Faten Khalid, Ishak, Mohamad Khairi, Mostafa, Samih M.

“… Recently, cybercriminals have become more complex with their approaches, though the underlying motives for conducting cyber threats remain largely the same…”
Získat plný text

A new Sparse Auto-encoder based Framework using Grey Wolf Optimizer for Data Classification Problem Autor Karim, Ahmad Mozaffer

“… Different training approaches are applied to train sparse autoencoders. Previous studies and preliminary experiments reveal that those approaches may present remarkable…”
Získat plný text

On the Performance of Deep Learning-based Data-aided Active User Detection for GF-SCMA System Autor Han, Minsig, Abebet, Ameha T., Kang, Chung G.

“…) in the receiver has demonstrated a significant performance improvement for grant-free sparse code multiple access (GF-SCMA) system…”
Získat plný text

On the Performance of Deep Learning-based Data-aided Active User Detection for GF-SCMA System Autor Han, Minsig, Ameha Tsegaye Abebe, Kang, Chung G

“…) in the receiver has demonstrated a significant performance improvement for grant-free sparse code multiple access (GF-SCMA) system…”
Získat plný text

A dense multi-path decoder for tissue segmentation in histopathology images Autor Vu, Quoc Dang, Kwak, Jin Tae

“…•We propose a dense multi-path decoder for tissue segmentation in histopathology images.•Convolutional neural networks are built upon the up-to-date encoders…”
Získat plný text