This paper joins the image-matching module into the hybrid recommendation system and constructs its workflow, which fuses image features and hybrid recommendation algorithms to improve diversity of advice result. SIFT...
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This paper joins the image-matching module into the hybrid recommendation system and constructs its workflow, which fuses image features and hybrid recommendation algorithms to improve diversity of advice result. SIFT feature extracted was used as the standard of image matching, improved lsh algorithm based on p-stable distribution to implement image matching and searching module for high dimensional and huge image set, then redesigned the workflow of existing commodity recommendation system combined with the proposed image matching module. This paper proposed an improved lsh algorithm based on p-stable distribution to finish image searching and matching. The experiment proved that the algorithm has a certain degree of optimization to improve recall rate and error rate at the same time, through the matching time and the length of hash table shows that the algorithm optimizes the memory utilization and search efficiency. The extracted SIFT feature of images is the only foundation we used when comparing different images at present. In the following research, we can try to use a variety of image features as the basis for matching to improve the reliability of the matching results.
Ultra-short-term photovoltaic power prediction is one of the important measures to reduce the adverse effects of the safe and stable operation of traditional power systems. First, the periodicity of the PV power is ta...
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Ultra-short-term photovoltaic power prediction is one of the important measures to reduce the adverse effects of the safe and stable operation of traditional power systems. First, the periodicity of the PV power is taken into account to extract periodic components. For the remaining components, under different weather types, the local sensitive hashing algorithmalgorithm is used to achieve rapid classification of photovoltaic power segments, and the European distance is introduced as a measure of the prediction to predict. Using the data of the photovoltaic power station for verification, the results show that the method has a higher prediction accuracy.
As the development of cloud computing technology, cloud storage service has been widely used these years. People upload most of their data files to the cloud for saving local storage space and making data sharing avai...
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ISBN:
(纸本)9783030050634;9783030050627
As the development of cloud computing technology, cloud storage service has been widely used these years. People upload most of their data files to the cloud for saving local storage space and making data sharing available everywhere. Except for storage service, data similarity retrieval is another basic service that cloud provides, especially for image data. As demand for near-duplicate image detection increases, it has been an attracted research topic in cloud image data similarity retrieval in resent years. However, due to some image data (like medical images and face recognition images) contains important privacy information, it is preferred to support privacy protection in cloud image data similarity retrieval. In this paper, focusing on image data stored in the cloud, we propose a privacy preserving near-duplicate image data detection scheme based on the lsh algorithm. In particular, users would use their own image data to generate image-feature lsh metadata vector using lsh algorithm and would store both the ciphertexts of image data and image-feature lsh metadata vector in cloud. When the inquirer queries the near-duplicate image data, he would generate the imagefeature query token lsh metadata vector using lsh algorithm and send it to cloud. With the query token, cloud will execute the privacy-preserving near-duplicate image data detection and return the encrypted result to inquirer. Then the inquirer would decrypt the ciphertext and get the final result. Our security and performance analysis shows that the proposed scheme achieves the goals of privacy preserving and lightweight.
To study the problem of real-time and accuracy of the image retrieval algorithm of embedded system with scale, rotation and illumination. Improved SURF algorithm, which is applied to the binary image feature extractio...
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ISBN:
(纸本)9781538612309
To study the problem of real-time and accuracy of the image retrieval algorithm of embedded system with scale, rotation and illumination. Improved SURF algorithm, which is applied to the binary image feature extraction, improve the real-time performance of the image, the use of lsh algorithm to establish the index of the image feature database, to avoid duplicate feature extraction, the use of lsh algorithm to approximate the search image features, and the similarity into line sort, select the best matching image. When the image has scale, rotation, illumination, this algorithm has a higher retrieval accuracy than the SURF algorithm and ORB algorithm, and has a better robustness than the SURF algorithm. The experiments show that the algorithm has scale, rotation and illumination conditions of the embedded system of image retrieval, has good real-time performance and achieved good application effect.
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