Výsledky vyhledávání - "vector quantized variational autoencoder"

Quaternion Vector Quantized Variational Autoencoder Autor 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 Autor 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 Autor 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 Autor 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 Autor 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 Autor 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 Autor 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 Autor 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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A Vector Quantized Variational Autoencoder (VQ-VAE) Autoregressive Neural F0 Model for Statistical Parametric Speech Synthesis Autor 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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Leveraging Vector-Quantized Variational Autoencoder Inner Metrics for Anomaly Detection Autor Gangloff, Hugo, Pham, Minh-Tan, Courtrai, Luc, Lefevre, Sebastien

“…Anomaly Detection (AD) is an important research topic, with very diverse applications such as industrial defect detection, medical diagnosis, fraud detection,…”
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Vector Quantized Variational Autoencoder-Based Compressive Sampling Method for Time Series in Structural Health Monitoring Autor 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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Crank: An Open-Source Software for Nonparallel Voice Conversion Based on Vector-Quantized Variational Autoencoder Autor 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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Connectionist temporal classification loss for vector quantized variational autoencoder in zero-shot voice conversion Autor 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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Hierarchical Vector-Quantized Variational Autoencoder and Vector Credibility Mechanism for High-Quality Image Inpainting Autor Li, Cheng, Xu, Dan, Chen, Kuai

“…Image inpainting infers the missing areas of a corrupted image according to the information of the undamaged part. Many existing image inpainting methods can…”
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Augmenting Training Data with Vector-Quantized Variational Autoencoder for Classifying RF Signals Autor 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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Robust Semantic Communications with Masked VQ-VAE Enabled Codebook Autor Hu, Qiyu, Zhang, Guangyi, Qin, Zhijin, Cai, Yunlong, Yu, Guanding, Li, Geoffrey Ye

“…Although semantic communications have exhibited satisfactory performance on a large number of tasks, the impact of semantic noise and the robustness of the…”
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A Vector Quantized Variational Autoencoder (VQ-VAE) Autoregressive Neural $F_0$ Model for Statistical Parametric Speech Synthesis Autor Wang, Xin, Takaki, Shinji, Yamagishi, Junichi, King, Simon, Tokuda, Keiichi

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The Multilayer Perceptron Vector Quantized Variational AutoEncoder for Spectral Envelope Quantization Autor Srikotr, Tanasan, Mano, Kazunori

“… In this paper, we propose The Multilayer Perceptron Vector Quantized Variational Autoencoder (MLP-VQ-VAE) to manage the flexibility of controlling the number of z-latent vectors to quantize and embedding space size efficiently…”
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A Vector Quantized Variational Autoencoder (VQ-VAE) Autoregressive Neural [Formula Omitted] Model for Statistical Parametric Speech Synthesis Autor 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) neural [Formula Omitted…”
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Unsupervised brain imaging 3D anomaly detection and segmentation with transformers Autor Pinaya, Walter H.L., Tudosiu, Petru-Daniel, Gray, Robert, Rees, Geraint, Nachev, Parashkev, Ourselin, Sebastien, Cardoso, M. Jorge

“…•We develop transformers for unsupervised brain imaging anomaly detection.•Our approach combines a VQ-VAE with an ensemble of autoregressive…”
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