Suchergebnisse - Reduced deep convolutional stack autoencoder

Epileptic Seizure Recognition Using Reduced Deep Convolutional Stack Autoencoder and Improved Kernel RVFLN From EEG Signals von Sahani, Mrutyunjaya, Rout, Susanta Kumar, Dash, Pradipta Kishor

“… In this paper, reduced deep convolutional stack autoencoder (RDCSAE) and improved kernel random vector functional link network (IKRVFLN …”
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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 von 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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RDCSAE-RKRVFLN: A unified deep learning framework for robust and accurate DOA estimation von Raiguru, Priyadarshini, Swain, Bhanja Kishor, Rout, Susanta Kumar, Sahani, Mrutyunjaya, Mishra, Rabindra Kishore

“… This paper introduces an innovative unified deep learning (DL) model, “reduced deep convolutional stack autoencoder (RDCSAE …”
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Deep Convolutional Stack Autoencoder of Process Adaptive VMD Data With Robust Multikernel RVFLN for Power Quality Events Recognition von Sahani, Mrutyunjaya, Dash, Pradipta Kishore

“… ). A novel reduced deep convolutional neural network (RDCNN) embedded with stack autoencoder, that is, RDCSAE structure is introduced to extract the most discriminative …”
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Coupling of a lightweight model of reduced convolutional autoencoder with linear SVM classifier to detect brain tumours on FPGA von Chatterjee, Soumita, Pandit, Soumya, Das, Arpita

“… Following this preprocessing step, a dual-stack Reduced Convolutional Autoencoder (RCA) unit is coupled with a linear Support Vector Machine (SVM) classifier …”
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Unsupervised Deep Learning for Landslide Detection from Multispectral Sentinel-2 Imagery von Shahabi, Hejar, Rahimzad, Maryam, Tavakkoli Piralilou, Sepideh, Ghorbanzadeh, Omid, Homayouni, Saied, Blaschke, Thomas, Lim, Samsung, Ghamisi, Pedram

“… This paper proposes a new approach based on an unsupervised deep learning (DL) model for landslide detection …”
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Impact of Patch-Size on Classification Accuracy of Latent Fingerprint Image in Stacked Convolutional Auto-encoder based Segmentation and Detection von Chhabra, Megha, Shukla, Manoj Kumar, Ravulakollu, Kiran Kumar

“… ) using a stack of convolutional auto-encoders. The idea is to early detect the structure of interest from the image using a color-based mask …”
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Light Field Intrinsics with a Deep Encoder-Decoder Network von Alperovich, Anna, Johannsen, Ole, Strecke, Michael, Goldluecke, Bastian

“… We present a fully convolutional autoencoder for light fields, which jointly encodes stacks of horizontal and vertical epipolar plane images through a deep network of residual layers …”
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