|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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,...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|