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Keyword: ConvolutionVerification of the Usefulness of Personal Authentication with Aerial Input Numerals Using Leap Motion
With the progress of IoT, everything is going to be connected to the network. It will bring us a lot of benefits however some security risks will be occurred by connecting network. To avoid such problems, it is indispensable to strengthen security more than now. We focus on personal authentication as one of the security.…
Read MoreSmart Meter Data Analysis for Electricity Theft Detection using Neural Networks
The major problem in electric utility is Electrical Theft, which is harmful to electric power suppliers and causes economic loss. Detecting and controlling electrical theft is a challenging task that involves several aspects like economic, social, regional, managerial, political, infrastructural, literacy rate, etc. Numerous methods were proposed formerly for detecting electricity theft. However, the previous…
Read MoreA Relation Extraction System for Indian Languages
Relation Extraction is an important subtask of Information Extraction that involves extracting significant facts from natural language text. Extracting structured information from the plaintext is the ultimate goal of IE systems. The Indian language content on the internet is increasing day to day. Extracting relevant information from this huge unstructured data is a challenging task…
Read MoreCNN-based Automatic Coating Inspection System
The application of protective coatings is the primary method of protecting marine and offshore structures from corrosion. Coating breakdown and corrosion (CBC) assessment is a major aspect of coating failure management. Evaluation methods can result in unnecessary maintenance costs and a higher risk of failure. To achieve a comprehensive collection of data for CBC assessment,…
Read MoreRetrieving Dialogue History in Deep Neural Networks for Spoken Language Understanding
In this paper, we propose a revised version of the semantic decoder for multi-label classification task in the spoken language understanding (SLU) pilot task of the Dialog State Tracking Challenge 5 (DSTC5). Our model concatenates two deep neural networks – a Convolutional Neural Network (CNN) and a Recurrent Neural Networks (RNN) – for detecting semantic…
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