Search Results - Multi-scale conventional autoencoder

Design of multi-scale receptive field convolutional neural network for surface inspection of hot rolled steels by He, Di, Xu, Ke, Wang, Dadong

“… A group of AutoEncoders are trained to reduce the dimension of the extracted multi-scale features which improve the generalization ability under insufficient training samples…”
Get full text

Optimal Spectrum Sensing Framework for Cognitive Radio Networks Using Attention‐Based Autoencoder With Multi‐Scale Capsule Network by Rao, R. Koteswara, Sahaai, Madona B.

“… In addition, the conventional models cause high computational complexity in the SS. In this work, an adaptive SS system for CR networks is developed to identify unused bands of frequencies in order to get outside of these constraints…”
Get full text

A convolutional autoencoder model with weighted multi-scale attention modules for 3D skeleton-based action recognition by Khezerlou, F., Baradarani, A., Balafar, M.A.

“…The 3D skeleton sequences of action can be recognized based on series of meaningful movements including changes in the direction and geometry features of the…”
Get full text

Multi-scale variational autoencoder for imputation of missing values in untargeted metabolomics using whole-genome sequencing data by Zhao, Chen, Su, Kuan-Jui, Wu, Chong, Cao, Xuewei, Sha, Qiuying, Li, Wu, Luo, Zhe, Qing, Tian, Qiu, Chuan, Zhao, Lan Juan, Liu, Anqi, Jiang, Lindong, Zhang, Xiao, Shen, Hui, Zhou, Weihua, Deng, Hong-Wen

“… Our approach utilizes a multi-scale variational autoencoder to jointly model the burden score, polygenetic risk score (PGS…”
Get full text

Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders by Wang, Yao, Lei, Xiujuan, Chen, Yuli, Guo, Ling, Wu, Fang-Xiang

“… In this study, we propose a circRNA-drug association prediction method based on multi-scale convolutional neural networks (MSCNN…”
Get full text

Multi-scale asynchronous correlation and 2D convolutional autoencoder for adolescent health risk prediction with limited fMRI data by Gao, Di, Yang, Guanghao, Shen, Jiarun, Wu, Fang, Ji, Chao

“…) with multi-sequence learning and multi-scale asynchronous correlation information extraction techniques…”
Get full text

IoT-based prediction model for aquaponic fish pond water quality using multiscale feature fusion with convolutional autoencoder and GRU networks by Sundararajan, Suma Christal Mary, Shankar, Yamini Bhavani, Selvam, Sinthia Panneer, Manogaran, Nalini, Seerangan, Koteeswaran, Natesan, Deepa, Selvarajan, Shitharth

“…The Internet of Things (IoT)-based smart solutions have been developed to predict water quality and they are becoming an increasingly important means of…”
Get full text

Slim multi-scale convolutional autoencoder-based reduced-order models for interpretable features of a complex dynamical system by Teutsch, Philipp, Pfeffer, Philipp, Sharifi Ghazijahani, Mohammad, Cierpka, Christian, Schumacher, Jörg, Mäder, Patrick

“… Within the context of reduced-order models, convolutional autoencoders (CAEs) pose a universally applicable alternative to conventional approaches…”
Get full text

Video Prediction Using Multi-Scale Deep Neural Networks by N. Shayanfar, V. Derhami, M. Rezaeian

“… This architecture is in the broad family of autoencoders. It is comprised of an encoder and decoder…”
Get full text

A Variational Multi-Scale Error Compensation Network for Single-Pixel Imaging by Lin, Jian, Yan, Qiurong, Zou, Quan, Sun, Shida, Wei, Zhen, Du, Hua

“… In this paper, we propose a Variational Multi-Scale Error Compensation Network (VMSE) based on variational autoencoders…”
Get full text

Multi-Scale Reinforcement Learning of Dynamic Energy Controller for Connected Electrified Vehicles by Zhang, Hao, Lei, Nuo, Li, Shengbo Eben, Zhang, Junzhi, Wang, Zhi

“…The synergy of reinforcement learning (RL)-based energy management and vehicle-to-everything communication has been proved effective in boosting the fuel…”
Get full text

Saliency supervised masked autoencoder pretrained salient location mining network for remote sensing image salient object detection by Fu, Yuxiang, Fang, Wei, Sheng, Victor S.

“… However, we observed that the conventional use of masked autoencoder for pretraining encoders through masked image reconstruction yields subpar results in the context of RSI-SOD…”
Get full text

Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders by Sajid, Muhammad, Razzaq Malik, Kaleem, Ur Rehman, Ateeq, Safdar Malik, Tauqeer, Alajmi, Masoud, Haider Khan, Ali, Haider, Amir, Hussen, Seada

“…Although the Transformer architecture has established itself as the industry standard for jobs involving natural language processing, it still has few uses in…”
Get full text

Performance enhancement in hydroponic and soil compound prediction by deep learning techniques by Abidi, Mustufa Haider, Chintakindi, Sanjay, Rehman, Ateekh Ur, Mohammed, Muneer Khan

“…The soil quality plays a crucial role in providing essential nutrients for crop growth and ensuring a bountiful yield. Identifying the soil composition, which…”
Get full text

Multi-scale Residual Segmentation Network for Histopathological Image by Bozdağ, Zehra, Talu, Muhammed Fatih

“… Unlike conventional autoencoder approaches, it consists…”
Get full text

Autoencoder-based Unsupervised Intrusion Detection using Multi-Scale Convolutional Recurrent Networks by Singh, Amardeep, Jang-Jaccard, Julian

“…The massive growth of network traffic data leads to a large volume of datasets. Labeling these datasets for identifying intrusion attacks is very laborious and…”
Get full text

Trans-cVAE-GAN: Transformer-Based cVAE-GAN for High-Fidelity EEG Signal Generation by Yao, Yiduo, Wang, Xiao, Hao, Xudong, Sun, Hongyu, Dong, Ruixin, Li, Yansheng

“…Electroencephalography signal generation remains a challenging task due to its non-stationarity, multi-scale oscillations, and strong spatiotemporal coupling…”
Get full text

Dual-Path Autoencoder-DenseNet Architecture for Robust Object Classification via Background-Free Reconstruction and Multi-Task Feature Fusion by Rosli, Hashim, Ali, Rozniza, Hitam, Muhamad Suzuri, Deris, Ashanira Mat

“… The model utilizes a dual-path design, incorporating a DenseNet121 backbone to extract multi-scale features for both image reconstruction and classification tasks…”
Get full text

Multi-Task Graph Attention Net for Electricity Consumption Prediction and Anomaly Detection by Bai, Na, Zhang, Jian, Wu, Zhaoli

“… (processed via multi-scale attention networks) and volatile…”
Get full text

Improving Supervised Microaneurysm Segmentation using Autoencoder-Regularized Neural Network by Kasantikul, Rangwan, Kusakunniran, Worapan

“… The proposed method is developed using two levels of the segmentation. First, the coarse-level segmentation stage locates the candidate areas using the multi-scale correlation filter and region growing…”
Get full text