Suchergebnisse - vector quantized variational autoencoder~

Hierarchical Vector-Quantized Variational Autoencoder and Vector Credibility Mechanism for High-Quality Image Inpainting von Li, Cheng, Xu, Dan, Chen, Kuai

“… To restore textures at a fine-grained level, we propose an image inpainting method based on a hierarchical VQ-VAE with a vector credibility mechanism …”
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Quaternion Vector Quantized Variational Autoencoder von Luo, Hui, Liu, Xin, Sun, Jian, Zhang, Yang

“… Vector quantized variational autoencoders, as variants of variational autoencoders, effectively capture discrete representations by quantizing continuous latent spaces and are widely used in generative tasks …”
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Vector-Quantized Variational AutoEncoder for pansharpening von Talbi, Farid, Chikr Elmezouar, Miloud, Boutellaa, Elhocine, Alim, Fatiha

“… This paper describes a new, efficient, and accurate pansharpening architecture. The Vector-Quantized Variational AutoEncoder (VQ-VAE …”
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FactorVQVAE: Discrete latent factor model via Vector Quantized Variational Autoencoder von Kim, Namhyoung, Ock, Seung Eun, Song, Jae Wook

“… This study introduces FactorVQVAE, the first integration of the Vector Quantized Variational Autoencoder (VQVAE …”
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Attention-based vector quantized variational autoencoder for anomaly detection by using orthogonal subspace constraints von Yu, Qien, Dai, Shengxin, Dong, Ran, Ikuno, Soichiro

“… This paper introduces a new framework that uses a vector quantized variational autoencoder (VQVAE …”
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Frequency enhanced vector quantized variational autoencoder for structural vibration response compression von Xue, Zhilin, An, Yonghui, Ou, Jinping

“… •The frequency enhanced vector quantized variational autoencoder (FEVQVAE) is proposed for structural vibration response compression …”
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Predicting anatomical variations in radiotherapy with a vector quantized variational autoencoder generative model von Zou, Yue, Li, Zhenhao, Zhang, Menghan, Li, Ziwei, Yin, Xiaojie, Yang, Long, Hu, Weigang, Wang, Jiazhou

“… Predicting these changes may benefit adaptive radiotherapy (ART) in nasopharyngeal cancer. Purpose This study proposes a vector quantized variational autoencoder (VQ‐VAE …”
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Data augmentation for Gram-stain images based on Vector Quantized Variational AutoEncoder von V, Shwetha, Prasad, Keerthana, Mukhopadhyay, Chiranjay, Banerjee, Barnini

“… In this regard, we investigate a novel application of the Variational AutoEncoder. Specifically, the Vector Quantized Variational AutoEncoder model is trained to generate the Gram-stain images …”
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S-HR-VQVAE: Sequential Hierarchical Residual Learning Vector Quantized Variational Autoencoder for Video Prediction von Adiban, Mohammad, Stefanov, Kalin, Siniscalchi, Sabato Marco, Salvi, Giampiero

“… (i) a novel hierarchical residual learning vector quantized variational autoencoder (HR-VQVAE), and (ii) a novel autoregressive spatiotemporal predictive model …”
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SSL-VQ: vector-quantized variational autoencoders for semi-supervised prediction of therapeutic targets across diverse diseases von Namba, Satoko, Li, Chen, Yuyama Otani, Noriko, Yamanishi, Yoshihiro

“… rare diseases, intractable diseases). Results This study presents a novel machine learning approach using multimodal vector-quantized variational autoencoders (VQ-VAEs …”
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A Vector Quantized Variational Autoencoder (VQ-VAE) Autoregressive Neural F0 Model for Statistical Parametric Speech Synthesis von Wang, Xin, Takaki, Shinji, Yamagishi, Junichi, King, Simon, Tokuda, Keiichi

“… In subjective evaluations, a deep AR model (DAR) outperformed an RNN. Here, we propose a Vector Quantized Variational Autoencoder (VQ-VAE …”
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466.4-Gbit/s PCS-64QAM wireless transmission enhanced by dual-polarized SISO link and vector-quantized variational autoencoders von Liu, Xiang, Zhang, Jiao, Zhu, Min, Xin, Zhigang, Dong Tong, Wei, Wang, Yunwu, Cai, Yuancheng, Hua, Bingchang, Lei, Mingzheng, Liu, Bo, Yu, Jianjun

“… ) wireless delivery at 92.5 GHz. This is achieved by employing a likelihood-aware vector-quantized variational autoencoder (VQ-VAE …”
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Leveraging Vector-Quantized Variational Autoencoder Inner Metrics for Anomaly Detection von Gangloff, Hugo, Pham, Minh-Tan, Courtrai, Luc, Lefevre, Sebastien

“… In this context, deep generative models are widely used, in particular Variational Autoencoder (VAE) models. VAEs have been extended to Vector-Quantized VAEs …”
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Vector Quantized Variational Autoencoder-Based Compressive Sampling Method for Time Series in Structural Health Monitoring von Liang, Ge, Ji, Zhenglin, Zhong, Qunhong, Huang, Yong, Han, Kun

“… The theory of compressive sampling (CS) has revolutionized data compression technology by capitalizing on the inherent sparsity of a signal to enable signal …”
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Anomaly Detection Through Latent Space Restoration Using Vector Quantized Variational Autoencoders von Marimont, Sergio Naval, Tarroni, Giacomo

“… We propose an out-of-distribution detection method that combines density and restoration-based approaches using Vector-Quantized Variational Auto-Encoders (VQ-VAEs …”
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Connectionist temporal classification loss for vector quantized variational autoencoder in zero-shot voice conversion von Kang, Xiao, Huang, Hao, Hu, Ying, Huang, Zhihua

“… •Thorough analysis provides useful insight into representation disentangling. Vector quantized variational autoencoder (VQ-VAE …”
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SVQ-VAE: Federated-Learning-Based Semantic-Aware Communication for Vehicular Networks von Jin, Zhu, Li, Yundi, Song, Tiecheng, Jia, Wen-Kang, Song, Xiaoqin

“… The integration of semantic communication technology into intelligent vehicular networks represents a promising research direction, as it significantly reduces …”
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Crank: An Open-Source Software for Nonparallel Voice Conversion Based on Vector-Quantized Variational Autoencoder von Kobayashi, Kazuhiro, Huang, Wen-Chin, Wu, Yi-Chiao, Tobing, Patrick Lumban, Hayashi, Tomoki, Toda, Tomoki

“… For implementing the VC software, we used a vector-quantized variational autoencoder (VQVAE). To rapidly examine the effectiveness …”
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S2VQ-VAE: Semi-Supervised Vector Quantised-Variational AutoEncoder for Automatic Evaluation of Trail Making Test von Tang, Zeshen, Tang, Shiyu, Wang, Haoran, Li, Renren, Zhang, Xiaochen, Zhang, Wei, Yuan, Xiao, Zang, Yaning, Li, Yanping, Zhou, Tian, Li, Yunxia

“… We proposed a novel deep representation learning approach named Semi-Supervised Vector Quantised-Variational AutoEncoder (S2VQ-VAE …”
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Augmenting Training Data with Vector-Quantized Variational Autoencoder for Classifying RF Signals von Kompella, Srihari Kamesh, Davaslioglu, Kemal, Sagduyu, Yalin E., Kompella, Sastry

“… Radio frequency (RF) communication has been an important part of civil and military communication for decades. With the increasing complexity of wireless …”
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