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  • A Secure Visual Secret Sharing Scheme with Authentication Based on QR Code
  • Abstract With the rise of the Internet of Things (IoT), various devices in life and industry are closely linked. Because of its high payload, stable error correction capability, and convenience in reading and writing, Quick Response (QR) code has been widely researched in IoT. However, the security of privacy data in IoT is also a very important issue. At the same time, because IoT is developing towards low-power devices in order to be applied to more fields, the technology protecting the security of private needs to have the characteristics of low computational complexity. Visual Secret Sharing (VSS), with its features of…
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  • Encoder-Decoder Based Multi-Feature Fusion Model for Image Caption Generation
  • Abstract Image caption generation is an essential task in computer vision and image understanding. Contemporary image caption generation models usually use the encoder-decoder model as the underlying network structure. However, in the traditional Encoder-Decoder architectures, only the global features of the images are extracted, while the local information of the images is not well utilized. This paper proposed an Encoder-Decoder model based on fused features and a novel mechanism for correcting the generated caption text. We use VGG16 and Faster R-CNN to extract global and local features in the encoder first. Then, we train the bidirectional LSTM network with the fused…
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  •   Views:284       Downloads:299        Download PDF
  • Grain Yield Predict Based on GRA-AdaBoost-SVR Model
  • Abstract Grain yield security is a basic national policy of China, and changes in grain yield are influenced by a variety of factors, which often have a complex, non-linear relationship with each other. Therefore, this paper proposes a Grey Relational Analysis–Adaptive Boosting–Support Vector Regression (GRAAdaBoost-SVR) model, which can ensure the prediction accuracy of the model under small sample, improve the generalization ability, and enhance the prediction accuracy. SVR allows mapping to high-dimensional spaces using kernel functions, good for solving nonlinear problems. Grain yield datasets generally have small sample sizes and many features, making SVR a promising application for grain yield datasets.…
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  • Research on Key Technologies of Electronic Shelf Labels Based on LoRa
  • Abstract The demand for Electronic Shelf Labels (ESL), according to the Internet of Things (IoT) paradigm, is expected to grow considerably in the immediate future. Various wireless communication standards are currently contending to gain an edge over the competition and provide the massive connectivity that will be required by a world in which everyday objects are expected to communicate with each other. Low-Power Wide-Area Networks (LPWANs) are continuously gaining momentum among these standards, mainly thanks to their ability to provide long-range coverage to devices, exploiting license-free frequency bands. The main theme of this work is one of the most prominent LPWAN…
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  •   Views:1175       Downloads:732        Download PDF
  • RETRACTED: Recent Approaches for Text Summarization Using Machine Learning & LSTM0
  • Abstract Nowadays, data is very rapidly increasing in every domain such as social media, news, education, banking, etc. Most of the data and information is in the form of text. Most of the text contains little invaluable information and knowledge with lots of unwanted contents. To fetch this valuable information out of the huge text document, we need summarizer which is capable to extract data automatically and at the same time capable to summarize the document, particularly textual text in novel document, without losing its any vital information. The summarization could be in the form of extractive and abstractive summarization. The…
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  • OPPR: An Outsourcing Privacy-Preserving JPEG Image Retrieval Scheme with Local Histograms in Cloud Environment
  • Abstract As the wide application of imaging technology, the number of big image data which may containing private information is growing fast. Due to insufficient computing power and storage space for local server device, many people hand over these images to cloud servers for management. But actually, it is unsafe to store the images to the cloud, so encryption becomes a necessary step before uploading to reduce the risk of privacy leakage. However, it is not conducive to the efficient application of image, especially in the Content-Based Image Retrieval (CBIR) scheme. This paper proposes an outsourcing privacypreserving JPEG CBIR scheme. We…
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  • Research on Planar Double Compound Pendulum Based on RK-8 Algorithm
  • Abstract Establishing the Lagrangian equation of double complex pendulum system and obtaining the dynamic differential equation, we can analyze the motion law of double compound pendulum with application of the numerical simulation of RK-8 algorithm. When the double compound pendulum swings at a small angle, the Lagrangian equation can be simplified and the normal solution of the system can be solved. And we can walk further on the relationship between normal frequency and swing frequency of double pendulum. When the external force of normal frequency is applied to the double compound pendulum, the forced vibration of the double compound pendulum will…
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  • A New Population Initialization of Particle Swarm Optimization Method Based on PCA for Feature Selection
  • Abstract In many fields such as signal processing, machine learning, pattern recognition and data mining, it is common practice to process datasets containing huge numbers of features. In such cases, Feature Selection (FS) is often involved. Meanwhile, owing to their excellent global search ability, evolutionary computation techniques have been widely employed to the FS. So, as a powerful global search method and calculation fast than other EC algorithms, PSO can solve features selection problems well. However, when facing a large number of feature selection, the efficiency of PSO drops significantly. Therefore, plenty of works have been done to improve this situation.…
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  • Multi-Scale Blind Image Quality Predictor Based on Pyramidal Convolution
  • Abstract Traditional image quality assessment methods use the hand-crafted features to predict the image quality score, which cannot perform well in many scenes. Since deep learning promotes the development of many computer vision tasks, many IQA methods start to utilize the deep convolutional neural networks (CNN) for IQA task. In this paper, a CNN-based multi-scale blind image quality predictor is proposed to extract more effectivity multi-scale distortion features through the pyramidal convolution, which consists of two tasks: A distortion recognition task and a quality regression task. For the first task, image distortion type is obtained by the fully connected layer. For…
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  •   Views:470       Downloads:315        Download PDF
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