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检索条件"主题词=Autoencoder"
4298 条 记 录,以下是3841-3850 订阅
Character Prediction in TV Series via a Semantic Projection Network  25th
Character Prediction in TV Series via a Semantic Projection ...
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25th International Conference on MultiMedia Modeling (MMM)
作者: Sun, Ke Lei, Zhuo Zhu, Jiasong Hou, Xianxu Liu, Bozhi Qiu, Guoping Shenzhen Univ Shenzhen Key Lab Spatial Informat Smarting Sensin Shenzhen Peoples R China Univ Nottingham Ningbo Sch Comp Sci Ningbo Peoples R China Shenzhen Univ Coll Informat Engn Guangdong Key Lab Intelligent Informat Proc Shenzhen Peoples R China Univ Nottingham Sch Comp Sci Nottingham England
The goal of this paper is to automatically recognize characters in popular TV series. In contrast to conventional approaches which rely on weak supervision afforded by transcripts, subtitles or character facial data, ... 详细信息
来源: 评论
Effective Feature Learning with Unsupervised Learning for Improving the Predictive Models in Massive Open Online Courses  19
Effective Feature Learning with Unsupervised Learning for Im...
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9th International Conference on Learning Analytics and Knowledge (LAK)
作者: Ding, Mucong Yang, Kai Yeung, Dit-Yan Pong, Ting-Chuen Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Peoples R China
The effectiveness of learning in massive open online courses (MOOCs) can be significantly enhanced by introducing personalized intervention schemes which rely on building predictive models of student learning behavior... 详细信息
来源: 评论
Model-Free Training of End-to-End Communication Systems
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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2019年 第11期37卷 2503-2516页
作者: Aoudia, Faycal Ait Hoydis, Jakob Paris Saclay Nokia Bell Labs F-91620 Nozay France
The idea of end-to-end learning of communication systems through neural network (NN)-based autoencoders has the shortcoming that it requires a differentiable channel model. We present in this paper a novel learning al... 详细信息
来源: 评论
A Generalized Data Representation and Training-Performance Analysis for Deep Learning Based Communication Systems  90
A Generalized Data Representation and Training-Performance A...
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90th IEEE Vehicular Technology Conference (IEEE VTC-Fall)
作者: Chen, Xiao Cheng, Julian Zhang, Zaichen Wu, Liang Dang, Jian Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Univ British Columbia Sch Engn Kelowna BC V1V 1V7 Canada
Deep learning (DL) based autoencoder is a potential architecture to implement end-to-end communication systems. In this paper, we first give a brief introduction to the autoencoder-represented communication system. Th... 详细信息
来源: 评论
Spatial-Temporal Scientific Data Clustering via Deep Convolutional Neural Network
Spatial-Temporal Scientific Data Clustering via Deep Convolu...
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IEEE International Conference on Big Data (Big Data)
作者: Sun, Jianxin Wu, Chunxia Ge, Yufeng Li, Yusong Yu, Hongfeng Univ Nebraska Lincoln Dept Comp Sci & Engn Lincoln NE 68588 USA Univ Nebraska Lincoln Dept Biol Syst Engn Lincoln NE USA Univ Nebraska Lincoln Dept Civil & Environm Engn Lincoln NE USA
We explore the usage of deep convolutional neural network for clustering the time steps of a spatial-temporal scientific dataset. Our approach first takes the scientific datasel as training data and trains a deep conv... 详细信息
来源: 评论
DISTORTED REPRESENTATION SPACE CHARACTERIZATION THROUGH BACKPROPAGATED GRADIENTS  26
DISTORTED REPRESENTATION SPACE CHARACTERIZATION THROUGH BACK...
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26th IEEE International Conference on Image Processing (ICIP)
作者: Kwon, Gukyeong Prabhushankar, Mohit Temel, Dogancan AlRegib, Ghassan Georgia Inst Technol Sch Elect & Comp Engn Ctr Signal & Informat Proc Atlanta GA 30332 USA
In this paper, we utilize weight gradients from backpropagation to characterize the representation space learned by deep learning algorithms. We demonstrate the utility of such gradients in applications including perc... 详细信息
来源: 评论
A New Approach to Batch Effect Removal Based on Distribution Matching in Latent Space
A New Approach to Batch Effect Removal Based on Distribution...
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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
作者: Li, Huaqing Dogan, Haluk Cui, Juan Univ Nebraska Syst Biol & Biomed Informat Lab Comp Sci & Engn Lincoln NE 68588 USA
Advanced measurement techniques such as genomics are capable of acquiring high-throughput data in high dimensions, enabling new scientific discoveries, and offering unique insights in biomedical research. However, bio... 详细信息
来源: 评论
EIT-CDAE: A 2-D Electrical Impedance Tomography Image Reconstruction Method Based on Auto Encoder Technique
EIT-CDAE: A 2-D Electrical Impedance Tomography Image Recons...
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IEEE Biomedical Circuits and Systems Conference (BioCAS)
作者: Gao, Yue Lu, Yewangqing Li, Hui Liu, Boxiao Li, Yongfu Chen, Mingyi Wang, Guoxing Lian, Yong Shanghai Jiao Tong Univ Dept Micronano Elect Shanghai Peoples R China Shanghai Jiao Tong Univ MoE Key Lab Artificial Intelligence Shanghai Peoples R China
Electrical Impedance Tomography is considered to be an alternative substitution to CT and MRI technologies as it is a non-invasive, safe medical imaging technology, and free of ionizing or heating radiation. Similar t... 详细信息
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Deep learning enables accurate alignment of single cell RNA-seq data
Deep learning enables accurate alignment of single cell RNA-...
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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
作者: Zhong, Yuanke Li, Jing Liu, Jie Zheng, Yan Shang, Xuequn Hu, Jialu Northwestern Polytech Univ Sch Comp Sci Xian Peoples R China Northwestern Polytech Univ Mingde Coll Xian Peoples R China
As more and more single-cell RNA-seq (scRNA-seq) datasets become available, carrying out compare between them is key. However, this task is challengeable due to differences caused by different experiment. We proposed ... 详细信息
来源: 评论
A Case Study on Using Deep Learning for Network Intrusion Detection
A Case Study on Using Deep Learning for Network Intrusion De...
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IEEE Military Communications Conference (MILCOM)
作者: Fernandez, Gabriel C. Xu, Shouhuai Univ Texas San Antonio Dept Comp Sci San Antonio TX 78249 USA
Deep Learning has been very successful in many application domains. However, its usefulness in the context of network intrusion detection has not been systematically investigated. In this paper, we report a case study... 详细信息
来源: 评论