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检索条件"主题词=autoencoder"
4251 条 记 录,以下是4151-4160 订阅
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SEMANTIC ANNOTATION OF SATELLITE IMAGES VIA JOINT MULTI-FEATURE LEARNING WITH DIVERSITY CONSTRAINT  36
SEMANTIC ANNOTATION OF SATELLITE IMAGES VIA JOINT MULTI-FEAT...
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36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
作者: Yao, Xiwen Han, Junwei Cheng, Gong Zhou, Peicheng Guo, Lei Northwestern Polytech Univ Sch Automat Xian 710072 Peoples R China
Automatic semantic annotation of high-resolution optical satellite images is a task to assign one or several predefined semantic concepts to an image according to its content. The fundamental challenge arises from the... 详细信息
来源: 评论
Large-Scale Prediction of Drug-Target Interactions from Deep Representations
Large-Scale Prediction of Drug-Target Interactions from Deep...
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International Joint Conference on Neural Networks (IJCNN)
作者: Hu, Peng-Wei Chan, Keith C. C. You, Zhu-Hong Hong Kong Polytech Univ Dept Comp Kowloon Hong Kong Peoples R China
Identifying drug-target interactions (DTIs) is a major challenge in drug development. Traditionally, similarity-based methods use drug and target similarity matrices to infer the potential drug-target interactions. Bu... 详细信息
来源: 评论
Page Segmentation for Historical Handwritten Document Images Using Conditional Random Fields  15
Page Segmentation for Historical Handwritten Document Images...
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15th International Conference on Frontiers in Handwriting Recognition (ICFHR)
作者: Chen, Kai Seuret, Mathias Liwicki, Marcus Hennebert, Jean Liu, Cheng-Lin Ingold, Rolf Univ Fribourg DIVA Fribourg Switzerland Univ Appl Sci HES SO FR Fribourg Switzerland Chinese Acad Sci Inst Automat NLPR Beijing Peoples R China
In this paper, we present a Conditional Random Field (CRF) model to deal with the problem of segmenting handwritten historical document images into different regions. We consider page segmentation as a pixel-labeling ... 详细信息
来源: 评论
Identifying Nontechnical Power Loss via Spatial and Temporal Deep Learning  15
Identifying Nontechnical Power Loss via Spatial and Temporal...
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15th IEEE International Conference on Machine Learning and Applications (ICMLA)
作者: Bhat, Rajendra Rana Trevizan, Rodrigo Daniel Sengupta, Rahul Li, Xiaolin Bretas, Arturo Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA
Fraud detection in electricity consumption is a major challenge for power distribution companies. While many pattern recognition techniques have been applied to identify electricity theft, they often require extensive... 详细信息
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Dimensionality Reduction Method's Comparison Based On Statistical Dependencies  7
Dimensionality Reduction Method's Comparison Based On Statis...
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7th International Conference on Ambient Systems, Networks and Technologies (ANT) / 6th International Conference on Sustainable Energy Information Technology (SEIT)
作者: Vantuch, Tomas Snasel, Vaclav Zelinka, Ivan VSB Tech Univ Ostrava Dept Comp Sci 17 Listopadu 15 Ostrava 70833 Czech Republic
The field of machine learning deals with a huge amount of various algorithms, which are able to transform the observed data into many forms and dimensionality reduction (DR) is one of such transformations. There are m... 详细信息
来源: 评论
INFORMATION THEORETIC-LEARNING AUTO-ENCODER
INFORMATION THEORETIC-LEARNING AUTO-ENCODER
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International Joint Conference on Neural Networks (IJCNN)
作者: Santana, Eder Emigh, Matthew Principe, Jose C. Univ Florida Gainesville FL 32611 USA
We propose Information Theoretic-Learning (ITL) divergence measures for variational regularization of neural networks. We also explore ITL-regularized autoencoders as an alternative to variational autoencoding bayes, ... 详细信息
来源: 评论
Censoring Sensitive Data From Images  18
Censoring Sensitive Data From Images
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18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)
作者: Postavaru, Stefan Plesea, Ionut-Mihaita Univ Bucharest Bitdefender Bucharest Romania
In the recent years, the vast volume of digital images available enabled a large range of learning methods to be applicable, while making human input obsolete for many tasks. In this paper, we are addressing the probl... 详细信息
来源: 评论
Real-time Reconstruction of EEG Signals from Compressive Measurements via Deep Learning
Real-time Reconstruction of EEG Signals from Compressive Mea...
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International Joint Conference on Neural Networks (IJCNN)
作者: Majumdar, Angshul Ward, Rabab IIIT Delhi New Delhi India Univ British Columbia Vancouver BC Canada
To elongate the battery life of sensors worn in wireless body area networks, recent studies have advocated compressing the acquired biological signals before transmitting them. The signals are compressed using compres... 详细信息
来源: 评论
Human Interaction Recognition through Deep Learning Network  50
Human Interaction Recognition through Deep Learning Network
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IEEE International Carnahan Conference on Security Technology (ICCST)
作者: Berlin, S. Jeba John, Mala Anna Univ Dept Elect Engn Madras Inst Technol Madras Tamil Nadu India
This paper provides an efficient framework for recognizing human interactions based on deep learning based architecture. The Harris corner points and the histogram form the feature vector of the spatiotemporal volume.... 详细信息
来源: 评论
BARCODES FOR MEDICAL IMAGE RETRIEVAL USING AUTOENCODED RADON TRANSFORM  23
BARCODES FOR MEDICAL IMAGE RETRIEVAL USING AUTOENCODED RADON...
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23rd International Conference on Pattern Recognition (ICPR)
作者: Tizhoosh, Hamid R. Mitcheltree, Christopher Zhu, Shujin Dutta, Shamak Univ Waterloo KIMIA Lab Waterloo ON Canada Univ Waterloo Elect & Comp Engn Waterloo ON Canada Nanjing Univ Sci & Technol Sch Elect & Opt Engn Nanjing Jiangsu Peoples R China Univ Waterloo Syst Design Engn Waterloo ON Canada
Using content-based binary codes to tag digital images has emerged as a promising retrieval technology. Recently, Radon barcodes (RBCs) have been introduced as a new binary descriptor for image search. RBCs are genera... 详细信息
来源: 评论