Results 11 to 20 of about 6,908 (119)
Deep Medical Image Reconstruction with Autoencoders using Deep Boltzmann Machine Training [PDF]
INTRODUCTION: Deep learning-based Image compression achieves a promising result in recent years as compared with the traditional transform coding methodology.
Saravanan. S, Sujitha Juliet
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Abnormal Network Traffic Detection Method Combining Mahalanobis Distance and Autoencoder [PDF]
The existing abnormal traffic detection methods are limited in the accuracy due to the large scale of network traffic data and its imbalanced distribution.To address the problem, a method combining Mahalanobis distance and autoencoder is proposed to ...
LI Beibei, PENG Li, DAI Feifei
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Representation Learning: Recommendation With Knowledge Graph via Triple-Autoencoder
The last decades have witnessed a vast amount of interest and research in feature representation learning from multiple disciplines, such as biology and bioinformatics.
Yishuai Geng +3 more
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Dual Autoencoder Network with Separable Convolutional Layers for Denoising and Deblurring Images
A dual autoencoder employing separable convolutional layers for image denoising and deblurring is represented. Combining two autoencoders is presented to gain higher accuracy and simultaneously reduce the complexity of neural network parameters by using ...
Elena Solovyeva, Ali Abdullah
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RN-Autoencoder: Reduced Noise Autoencoder for classifying imbalanced cancer genomic data
Background In the current genomic era, gene expression datasets have become one of the main tools utilized in cancer classification. Both curse of dimensionality and class imbalance problems are inherent characteristics of these datasets.
Ahmed Arafa +3 more
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Autoencoder untuk Sistem Prediksi Berat Lahir Bayi
Salah satu ukuran terpenting saat awal persalinan adalah keakuratan prediksi berat lahir. Dengan menggunakan metode prediksi yang tepat, perkiraan ekstrim berat lahir bayi dapat dideteksi lebih atau kurang sehingga beberapa tindakan pencegahan dapat ...
Fitra Septia Nugraha +1 more
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Recent progress in Generative Artificial Intelligence (AI) relies on efficient data representations, often featuring encoder-decoder architectures. We formalize the mathematical problem of finding the optimal encoder-decoder pair and characterize its solution, which we name the "benign autoencoder" (BAE). We prove that BAE projects data onto a manifold
Semyon Malamud +4 more
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On the Regularization of Autoencoders
While much work has been devoted to understanding the implicit (and explicit) regularization of deep nonlinear networks in the supervised setting, this paper focuses on unsupervised learning, i.e., autoencoders are trained with the objective of reproducing the output from the input. We extend recent results [Jin et al.
Harald Steck, Dario García-García
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Autoencoding Variational Autoencoder
Neurips ...
A. Taylan Cemgil +4 more
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Anomaly Detection for Agricultural Vehicles Using Autoencoders
The safe in-field operation of autonomous agricultural vehicles requires detecting all objects that pose a risk of collision. Current vision-based algorithms for object detection and classification are unable to detect unknown classes of objects. In this
Esma Mujkic +4 more
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