Suchergebnisse - 3D Conventional Autoencoder~

A 3D lung lesion variational autoencoder von Li, Yiheng, Sadée, Christoph Y., Carrillo-Perez, Francisco, Selby, Heather M., Thieme, Alexander H., Gevaert, Olivier

“… In this study, we develop a 3D beta variational autoencoder (beta-VAE) to advance lung cancer imaging analysis, countering the constraints of conventional radiomics methods …”
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3D variational autoencoder for fingerprinting microstructure volume elements von White, Michael D., Atkinson, Michael D., Plowman, Adam J., Shanthraj, Pratheek

“… In this work, we present a 3D variational autoencoder (VAE) for encoding microstructure volume elements (VEs …”
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Synthetic Time-Series Data Generation for Smart Grids Using 3D Autoencoder GAN von Zhang, Guihai, Sikdar, Biplab

“… ). Beyond the conventional GAN structure, the incorporation of both the Autoencoder and 3D-convolution processes enables a more comprehensive extraction of patterns …”
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A convolutional autoencoder model with weighted multi-scale attention modules for 3D skeleton-based action recognition von Khezerlou, F., Baradarani, A., Balafar, M.A.

“… The 3D skeleton sequences of action can be recognized based on series of meaningful movements including changes in the direction and geometry features of the body pose …”
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Deep Learning Representation using Autoencoder for 3D Shape Retrieval von Zhu, Zhuotun, Wang, Xinggang, Bai, Song, Yao, Cong, Bai, Xiang

“… To address these problems, we project 3D shapes into 2D space and use autoencoder for feature learning on the 2D images …”
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A combination method of stacked autoencoder and 3D deep residual network for hyperspectral image classification von Zhao, Jinling, Hu, Lei, Dong, Yingying, Huang, Linsheng, Weng, Shizhuang, Zhang, Dongyan

“… In comparison with conventional machine learning algorithms, deep learning can effectively express the deep features of remote sensing images …”
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3D-CNN and Autoencoder-Based Gas Detection in Hyperspectral Images von Ozdemir, Okan Bilge, Koz, Alper

“… ) and autoencoder-based network, which is specially …”
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Convolutional autoencoder frameworks for projection multi-photon 3D printing von Jamil, Ishat Raihan, Johnson, Jason E., Xu, Xianfan

“… Projection multi-photon 3D printing is an emerging technique for fabricating micro-nano structures at exceptionally high speeds …”
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Contrastive Semantic-Aware Masked Autoencoder for Point Cloud Self-Supervised Learning von He, Yuan, Hu, Guyue, Yu, Shan

“… Masked Autoencoder (MAE) has shown remarkable potential in self-supervised representation learning for 3D point clouds …”
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Deep learning-based automated 3D inspection of helical gears using voxelized CAD models and 3D convolutional autoencoders von Selloum, Rabia, Ameddah, Hacene, Brioua, Mourad

“… We propose a voxel-based 3D inspection framework that integrates an XGBoost-guided perturbation model with a 3D convolutional autoencoder (3D CNN-AE …”
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Enhancing representational learning for cloud robotic vision through explainable fuzzy convolutional autoencoder framework von Udendhran, R., Yamini, G., Badrinath, N., Jegathesh Amalraj, J., Suresh, A.

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The Use of 3D Convolutional Autoencoder in Fault and Fracture Network Characterization von Xu, Feng, Li, Zhiyong, Wen, Bo, Huang, Youhui, Wang, Yaojun

“… In this paper, a fault and fracture network characterization method based on 3D convolutional autoencoder is proposed …”
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Identifying virulence factors using graph transformer autoencoder with ESMFold-predicted structures von Li, Guanghui, Bai, Peihao, Chen, Jiao, Liang, Cheng

“… Here, we propose a novel graph transformer autoencoder for VF identification (GTAE-VF), which utilizes ESMFold-predicted 3D structures and converts the VF identification problem into a graph-level prediction task …”
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Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data von Huang, Yi, Ren, Yihui, Yoo, Shinjae, Huang, Jin

“… The 3D convolutional neural network (CNN)-based approach, Bicephalous Convolutional Autoencoder (BCAE …”
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Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders von Sajid, Muhammad, Razzaq Malik, Kaleem, Ur Rehman, Ateeq, Safdar Malik, Tauqeer, Alajmi, Masoud, Haider Khan, Ali, Haider, Amir, Hussen, Seada

“… Although the Transformer architecture has established itself as the industry standard for jobs involving natural language processing, it still has few uses in …”
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DDINet: Drug-drug interaction prediction network based on multi-molecular fingerprint features and multi-head attention centered weighted autoencoder von Soni Sharmila, K, Revathi S, Thanga, Sree, Pokkuluri Kiran

“… In this paper, a novel DDI prediction network (DDINet) is proposed to enhance the predictive performance over conventional DDI methods …”
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CryoMAE: Few-Shot Cryo-EM Particle Picking with Masked Autoencoders von Xu, Chentianye, Zhan, Xueying, Xu, Min

“… To overcome these obstacles, we introduce cryoMAE, a novel approach based on few-shot learning that harnesses the capabilities of Masked Autoencoders (MAE …”
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Audio2Gestures: Generating Diverse Gestures from Speech Audio with Conditional Variational Autoencoders von Li, Jing, Kang, Di, Pei, Wenjie, Zhe, Xuefei, Zhang, Ying, He, Zhenyu, Bao, Linchao

“… Conventional CNNs/RNNs assume one-to-one mapping, and thus tend to predict the average of all possible target motions, resulting in plain/boring motions during inference …”
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3d Autoencoders For Feature Extraction In X-Ray Tomography von Tekawade, Aniket, Liu, Zhengchun, Kenesei, Peter, Bicer, Tekin, Carlo, Francesco De, Kettimuthu, Rajkumar, Foster, Ian

“… , porosity, particle size, and crack width) during continuous data acquisition. Segmentation of 2D or 3D images followed by quantitative measurement is the conventional …”
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Prototype-Guided Autoencoder for OCT-Based Fingerprint Presentation Attack Detection von Liu, Yi-Peng, Zuo, Wangyang, Liang, Ronghua, Sun, Haohao, Li, Zhanqing

“… Anti-spoofing ability is vital for fingerprint identification systems. Conventional fingerprint scanning devices can only obtain information from the fingertip …”
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