2 research outputs found

    Improved Lip-reading Language Using Gated Recurrent Units

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    Lip-reading is one of the most challenging studies in computer vision. This is because lip-reading requires a large amount of training data, high computation time and power, and word length variation. Currently, the previous methods, such as Mel Frequency Cepstrum Coefficients (MFCC) with Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) with LSTM, still obtain low accuracy or long-time consumption because they use LSTM. In this study, we solve this problem using a novel approach with high accuracy and low time consumption. In particular, we propose to develop lip language reading by utilizing face detection, lip detection, filtering the amount of data to avoid overfitting due to data imbalance, image extraction based on CNN, voice extraction based on MFCC, and training model using LSTM and Gated Recurrent Units (GRU). Experiments on the Lip Reading Sentences dataset show that our proposed framework obtained higher accuracy when the input array dimension is deep and lower time consumption compared to the state-of-the-art

    Cloutidy: A Cloud-based Supply Chain Management System Using Semar and Blockchain System

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    Supply chain management (SCM) system is an essential requirement for companies and manufacturers to collaborate in doing business. There are many techniques to manage supply chains, such as using Excel sheets and web-based applications. However, these techniques are ineffective, insecure, and prone to human error. In this paper, we propose CLOUTIDY, a cloud-based SCM system using SEMAR (Service Market) and Blockchain system. We modify JUGO architecture to develop SEMAR as a broker between users and cloud service providers. Also, we apply the Blockchain concept to store the activity log of the SCM system in a decentralized database. CLOUTIDY system can solve several common cases: service selection, resource provisioning, authentication and access control. Also, it improves the security of data by storing each activity log of the supply chain management system in the Blockchain system
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