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Adil Redaoui, Amina Belalia and Kamel Belloulata
Deep network-based hashing has gained significant popularity in recent years, particularly in the field of image retrieval. However, most existing methods only focus on extracting semantic information from the final layer, disregarding valuable structura...
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Kai Ma, Bowen Wang, Yunqin Li and Jiaxin Zhang
Propagating architectural heritage is of great significance to the inheritance and protection of local culture. Recommendations based on user preferences can greatly benefit the promotion of local architectural heritage so as to better protect and inheri...
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Zijian Chao and Yongming Li
Nowadays, people?s lives are filled with a huge amount of picture information, and image retrieval tasks are widely needed. Deep hashing methods are extensively used to manage such demands due to their retrieval rate and memory consumption. The problem w...
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Wenjing Yang, Liejun Wang, Shuli Cheng, Yongming Li and Anyu Du
Recently, deep learning to hash has extensively been applied to image retrieval, due to its low storage cost and fast query speed. However, there is a defect of insufficiency and imbalance when existing hashing methods utilize the convolutional neural ne...
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Xin Chen and Ying Li
Conventionally, the similarity between two images is measured by the easy-calculating Euclidean distance between their corresponding image feature representations for image retrieval. However, this kind of direct similarity measurement ignores the local ...
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Hongwei Zhao, Lin Yuan and Haoyu Zhao
Recently, with the rapid growth of the number of datasets with remote sensing images, it is urgent to propose an effective image retrieval method to manage and use such image data. In this paper, we propose a deep metric learning strategy based on Simila...
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Lili Fan, Hongwei Zhao, Haoyu Zhao, Pingping Liu and Huangshui Hu
Image retrieval applying deep convolutional features has achieved the most advanced performance in most standard benchmark tests. In image retrieval, deep metric learning (DML) plays a key role and aims to capture semantic similarity information carried ...
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Shahbaz Sikandar, Rabbia Mahum and AbdulMalik Alsalman
The multimedia content generated by devices and image processing techniques requires high computation costs to retrieve images similar to the user?s query from the database. An annotation-based traditional system of image retrieval is not coherent becaus...
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Wenjin Hu, Yukun Chen, Lifang Wu, Ge Shi and Meng Jian
Hamming space retrieval is a hot area of research in deep hashing because it is effective for large-scale image retrieval. Existing hashing algorithms have not fully used the absolute boundary to discriminate the data inside and outside the Hamming ball,...
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Antonio Maria Rinaldi, Cristiano Russo and Cristian Tommasino
In recent years the information user needs have been changed due to the heterogeneity of web contents which increasingly involve in multimedia contents. Although modern search engines provide visual queries, it is not easy to find systems that allow sear...
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DaYou Jiang and Jongweon Kim
This paper presents a new content-based image retrieval (CBIR) method based on image feature fusion. The deep features are extracted from object-centric and place-centric deep networks. The discrete cosine transform (DCT) solves the strong correlation of...
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Yating Gu, Yantian Wang and Yansheng Li
As a fundamental and important task in remote sensing, remote sensing image scene understanding (RSISU) has attracted tremendous research interest in recent years. RSISU includes the following sub-tasks: remote sensing image scene classification, remote ...
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Jianan Bai, Danyang Qin, Ping Zheng and Lin Ma
In visual indoor positioning systems, the method of constructing a visual map by point-by-point sampling is widely used due to its characteristics of clear static images and simple coordinate calculation. However, too small a sampling interval will cause...
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Ashish Bagwari, Anurag Sinha, N. K. Singh, Namit Garg and Jyotshana Kanti
Business-based decision support systems have been proposed for a few decades in the e-commerce and textile industries. However, these Decision Support Systems (DSS) have not been so productive in terms of business decision delivery. In our proposed model...
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Yuhai Yu, Hongfei Lin, Jiana Meng, Xiaocong Wei, Hai Guo and Zhehuan Zhao
Medical images are valuable for clinical diagnosis and decision making. Image modality is an important primary step, as it is capable of aiding clinicians to access required medical image in retrieval systems. Traditional methods of modality classificati...
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Jong Woo Kim, Marc Messerschmidt and William S. Graves
We present a deep learning-based generative model for the enhancement of partially coherent diffractive images. In lensless coherent diffractive imaging, a highly coherent X-ray illumination is required to image an object at high resolution. Non-ideal ex...
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Jong Woo Kim, Marc Messerschmidt and William S. Graves
We present a supervised deep neural network model for phase retrieval of coherent X-ray imaging and evaluate the performance. A supervised deep-learning-based approach requires a large amount of pre-training datasets. In most proposed models, the various...
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Hongwei Zhao, Jiaxin Wu, Danyang Zhang and Pingping Liu
For full description of images? semantic information, image retrieval tasks are increasingly using deep convolution features trained by neural networks. However, to form a compact feature representation, the obtained convolutional features must be furthe...
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Tian Xie, Weiping Ding, Jinbao Zhang, Xusen Wan and Jiehua Wang
The discipline of automatic image captioning represents an integration of two pivotal branches of artificial intelligence, namely computer vision (CV) and natural language processing (NLP). The principal functionality of this technology lies in transmuti...
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Tianqi Qiu, Xiaojin Liang, Qingyun Du, Fu Ren, Pengjie Lu and Chao Wu
Emergency remote sensing mapping can provide support for decision making in disaster assessment or disaster relief, and therefore plays an important role in disaster response. Traditional emergency remote sensing mapping methods use decryption algorithms...
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