Search Results - Loss-conditional autoencoder~

Semantic-oriented learning-based image compression by Only-Train-Once quantized autoencoders by 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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Autoencoder-Based PPG Compression for Resource-Constrained Device by Santiwongkarn, Suvichak, Kornworakarn, Natakorn, Suksompong, Prapun, Choksatchawathi, Tanut, Kaewlee, Thitikorn, Wilaiprasitporn, Theerawit

“… at 0.026 and peak MAE at 0.020. This is possible through the loss-conditional training approach on specific task learning…”
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FastMVAE2: On Improving and Accelerating the Fast Variational Autoencoder-Based Source Separation Algorithm for Determined Mixtures by Li Li, Hirokazu Kameoka, Shoji Makino

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Loss of Control Detection for Commercial Transports Using Conditional Variational Autoencoders by Campbell, Newton H, Grauer, Jared, Gregory, Irene

“… The detector has a belief state defined by the latent variable stochastic modeling of a conditional variational autoencoder (CVAE…”
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Analyzing Multimodal Probability Measures with Autoencoders by Lelièvre, Tony, Pigeon, Thomas, Stoltz, Gabriel, Zhang, Wei

“… Our focus here is on neural network approaches based on autoencoders. We study some relevant mathematical properties of the loss function considered for training…”
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PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation by Chatterjee, Soumick, Gaidzik, Franziska, Sciarra, Alessandro, Mattern, Hendrik, Janiga, Gábor, Speck, Oliver, Nürnberger, Andreas, Pathiraja, Sahani

“… This approach makes use of an improved loss function based on statistical distances in a conditional variational autoencoder structure (Probabilistic UNet…”
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Cross-age Face Synthesis Based on Conditional Adversarial Autoencoder by CHENG Zhikang, SUN Rui, SUN Qijing, ZHANG Xudong

“…, and so on.To solve the problems of organ distortion and poor local feature preservation in cross-age face image synthesis, a cross-age face image synthesis method based on a Conditional Adversarial AutoEncoder (CAAE…”
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ICVAE: Interpretable Conditional Variational Autoencoder for De Novo Molecular Design by Fan, Xiaqiong, Fang, Senlin, Li, Zhengyan, Ji, Hongchao, Yue, Minghan, Li, Jiamin, Ren, Xiaozhen

“… To address this issue, we propose the Interpretable Conditional Variational Autoencoder (ICVAE), which introduces a modified loss function that correlates the latent value with molecular properties…”
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Nonlinear Facial Attribute Editing Method based on Autoencoder in StyleGAN Latent Space by Kuang, Qixian, He, Xiping, Yang, Chutian, Xie, Xiaoqin

“… In the training process, reconstruction loss and conditional loss are introduced to constrain the autoencoder network, so that it can reconstruct the editing results that keep…”
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Loss of Control Detection for Commercial Transport Aircraft Using Conditional Variational Autoencoders by American Institute of Aeronautics and Astronautics

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Generative Neural Network Channel Modeling for Millimeter-Wave UAV Communication by Xia, William, Rangan, Sundeep, Mezzavilla, Marco, Lozano, Angel, Geraci, Giovanni, Semkin, Vasilii, Loianno, Giuseppe

“…), and subsequently feeds this state into a conditional variational autoencoder (VAE) that generates the path losses, delays, and angles of arrival and departure for all the propagation paths…”
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Diverse Motion In-Betweening From Sparse Keyframes With Dual Posture Stitching by Ren, Tianxiang, Yu, Jubo, Guo, Shihui, Ma, Ying, Ouyang, Yutao, Zeng, Zijiao, Zhang, Yazhan, Qin, Yipeng

“…In-betweening is a technique for generating transitions given start and target character states. The majority of existing works require multiple (often…”
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Face Aging With Boundary Equilibrium Conditional Autoencoder by Chen, Longxiang, Hu, Xiaolong, Zhang, Zuping

“… With the reconstruction loss of an autoencoder, conditional adversarial autoencoder (CAAE) is free from mode collapse…”
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Lifting Posture Prediction With Generative Models for Improving Occupational Safety by Li, Li, Prabhu, Saiesh, Xie, Ziyang, Wang, Hanwen, Lu, Lu, Xu, Xu

“… The conditional variational autoencoder and the regular FNN achieved comparable top performance in lifting posture…”
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Conditional Variational Autoencoder for Learned Image Reconstruction by Zhang, Chen, Barbano, Riccardo, Jin, Bangti

“… Once the network is trained using the conditional variational autoencoder loss, it provides a computationally efficient sampler for the approximate…”
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Cellular data extraction from multiplexed brain imaging data using self-supervised Dual-loss Adaptive Masked Autoencoder by Ly, Son T., Lin, Bai, Vo, Hung Q., Maric, Dragan, Roysam, Badrinath, Nguyen, Hien V.

“… This paper presents a novel self-supervised Dual-Loss Adaptive Masked Autoencoder (DAMA) for learning rich features from multiplexed immunofluorescence brain images…”
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Anomaly Detection with Conditional Variational Autoencoders by Pol, Adrian Alan, Berger, Victor, Germain, Cecile, Cerminara, Gianluca, Pierini, Maurizio

“… In this work, we exploit the deep conditional variational autoencoder (CVAE) and we define an original loss function together with a metric that targets hierarchically structured data AD…”
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Normalized Conditional Variational Auto-Encoder with adaptive Focal loss for imbalanced fault diagnosis of Bearing-Rotor system by Zhao, Xiaoli, Yao, Jianyong, Deng, Wenxiang, Jia, Minping, Liu, Zheng

“…•A new adaptive focus loss (AFL) function is designed.•A hybrid generative and cost-sensitive integrated deep neural network, named Normalized conditional variational Autoencoder with Adaptive Focal Loss (NCVAE-AFL…”
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Transforming Healthcare Diagnostics With Tensorized Attention and Continual Learning on Multi-Modal Data by Iqbal, Saeed, Zhong, Xiaopin, Khan, Muhammad Attique, Shabaz, Mohammad, Wu, Zongze, AlHammadi, Dina Abdulaziz, Liu, Weixiang, Algamdi, Shabbab Ali, Li, Yang

“…Analyzing multi-modal medical data in the setting of uncertain healthcare situations continues to be a major topic in medical image analysis and healthcare big…”
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A Conditional Variational Autoencoder Algorithm for Reconstructing Defect Data of Magnetic Flux Leakage by Lu, Senxiang, Wu, Jing, Zhang, Jianan

“… Therefore, it is important to reconstruct the missing data. This paper analyzes four types of MFL data loss, and presents a conditional variational autoencoder algorithm to reconstruct defect data of MFL for these types of loss…”
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