Výsledky vyhledávání - "Quantized Autoencoder"

Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset Autor Sharmila, B S, Nagapadma, Rohini

“… This study proposes quantized autoencoder (QAE) model for intrusion detection systems to detect anomalies…”
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Tackling the Nonlinearity Problem in Inverse Modeling: Mixture Density Network-Backed Quantized AutoEncoder Autor Talha Kilic, Muhammed Nur, Mao, Yuwei, Gupta, Vishu, Choudhary, Alok, Liao, Wei-keng, Agrawal, Ankit

“…Generative models have been widely used in the field of computer vision due to their ability to produce unseen data points. Its application has proven to be…”
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Avoiding Domain Drift and Constant Predictions with Diffusion Enhanced Vector-Quantized Autoencoders for Temperature Predictions Autor Lampl, Nina, de Freitas, Joao Machado, Fuchs, Alexander, Brezina, Benedikt, Klitzsch, Michael, Pernkopf, Franz

“… Using a vector-quantized autoencoder can mitigate the problem as it can map predictions back to the source domain, but it leads to almost constant predictions…”
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A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow Autor Momenifar, Mohammadreza, Diao, Enmao, Tarokh, Vahid, Bragg, Andrew D.

“…Analyzing large-scale data from simulations of turbulent flows is memory intensive, requiring significant resources. This major challenge highlights the need…”
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A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow Autor Momenifar, Mohammadreza, Diao, Enmao, Tarokh, Vahid, Bragg, Andrew D

“…Analyzing large-scale data from simulations of turbulent flows is memory intensive, requiring significant resources. This major challenge highlights the need…”
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Real-Time Monitoring and Anomaly Detection in Hospital IoT Networks Using Machine Learning Autor Ranjith Kumar, G, Govekar, Navnath Sopan, Karthik, A, Nijhawan, Ginni, Alawadi, Ahmed Hussien, V, Asha

“…The study covers the vital aspect of strong abnormality detection systems on IoT hospital networks that do not have enough resources available. The study…”
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Multi-rate deep semantic image compression with quantized modulated autoencoder Autor Sebai, Dorsaf

“…Recently, deep learning has demonstrated impressive performance in image compression. Methods, that achieve and even outperform conventional codecs…”
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Variable Rate Allocation for Vector-Quantized Autoencoders Autor Baldassarre, Federico, El-Nouby, Alaaeldin, Jegou, Herve

“…Vector-quantized autoencoders have recently gained interest in image compression, generation and self-supervised learning…”
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Semantic-oriented learning-based image compression by Only-Train-Once quantized autoencoders Autor Sebai, D., Shah, A. Ulah

“…Accessibility to big training datasets together with current advances in computing power has emerged interest in the leverage of deep learning to address image…”
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Enhancing into the Codec: Noise Robust Speech Coding with Vector-Quantized Autoencoders Autor Casebeer, Jonah, Vale, Vinjai, Isik, Umut, Valin, Jean-Marc, Giri, Ritwik, Krishnaswamy, Arvindh

“…Audio codecs based on discretized neural autoencoders have recently been developed and shown to provide significantly higher compression levels for comparable…”
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Hierarchical Quantized Autoencoders: Using Hierarchical Models for Data Compression Across Multiple Domains Autor Rodriguez, Armani Lorenzo

“…In the era of vast data processing and transmission, sending data over a channel for downstream operations is a very common occurrence. The bandwidth of this…”
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Group Residual Vector Quantized Autoencoders for SAR Raw Data Compression Autor Pilikos, Georgios, Azcueta, Mario, Floury, Nicolas

“…Synthetic Aperture Radar (SAR) systems are being improved continuously with increased swath sizes, better spatial resolution, multi-frequency and multi-channel…”
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Learning Product Codebooks Using Vector-Quantized Autoencoders for Image Retrieval Autor Wu, Hanwei, Flierl, Markus

“…Vector-Quantized Variational Autoencoders (VQ-VAE)[1] provide an unsupervised model for learning discrete representations by combining vector quantization and…”
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Hierarchical Quantized Autoencoders Autor Williams, Will, Ringer, Sam, Ash, Tom, Hughes, John, MacLeod, David, Dougherty, Jamie

“…Despite progress in training neural networks for lossy image compression, current approaches fail to maintain both perceptual quality and abstract features at…”
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Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment Autor Liu, Hao, Wilson, Yan, Abbeel, Pieter

“… In order to resolve this limitation, we propose a simple yet effective approach called Language-Quantized AutoEncoder (LQAE…”
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Harnessing the Power of Pre-Trained Models for Efficient Semantic Communication of Text and Images Autor Kutay, Emrecan, Yener, Aylin

“…This paper investigates point-to-point multimodal digital semantic communications in a task-oriented setup, where messages are classified at the receiver. We…”
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Theory and Experiments on Vector Quantized Autoencoders Autor Aurko Roy, Vaswani, Ashish, Neelakantan, Arvind, Parmar, Niki

“… and their performance has mostly failed to match their continuous counterparts. Recent work on vector quantized autoencoders (VQ-VAE…”
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Variational Information Bottleneck on Vector Quantized Autoencoders Autor Wu, Hanwei, Flierl, Markus

“…In this paper, we provide an information-theoretic interpretation of the Vector Quantized-Variational Autoencoder (VQ-VAE). We show that the loss function of…”
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EfficientFi: Toward Large-Scale Lightweight WiFi Sensing via CSI Compression Autor Yang, Jianfei, Chen, Xinyan, Zou, Han, Wang, Dazhuo, Xu, Qianwen, Xie, Lihua

“…WiFi technology has been applied to various places due to the increasing requirement of high-speed Internet access. Recently, besides network services, WiFi…”
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Enhancing into the codec: Noise Robust Speech Coding with Vector-Quantized Autoencoders Autor Casebeer, Jonah, Vale, Vinjai, Isik, Umut, Valin, Jean-Marc, Giri, Ritwik, Krishnaswamy, Arvindh

“…Audio codecs based on discretized neural autoencoders have recently been developed and shown to provide significantly higher compression levels for comparable…”
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