Results 31 to 40 of about 1,457 (180)
IPDH: An Improved Pairwise-Based Deep Hashing Method for Large-Scale Image Retrieval
IEEE Access, 2020 Hashing technique has been extensively utilized in approximate nearest neighbor (ANN) search for large-scale image retrieval by virtue of its storage simplicity and computational efficiency. Recently, many researches show that hashing methods based.
Wei Yao +6 more
doaj +1 more source
Self-Collaborative Unsupervised Hashing for Large-Scale Image Retrieval
IEEE Access, 2022 Learning based hashing approaches have achieved considerable success in large-scale image retrieval due to the query effectiveness and efficiency. However, most studies highly rely on supervised knowledge like data labels, thus might fail in unsupervised
Hongmin Zhao, Zhigang Luo
doaj +1 more source
IEEE Access, 2023 Supervised cross-modal retrieval has significant advantages in retrieval efficiency and storage cost. In the field of hashing retrieval, existing supervised methods are divided into single-label and multi-label methods.
Mingyong Li, Jiabao Fan, Ziyong Lin
doaj +1 more source
An Efficient Supervised Deep Hashing Method for Image Retrieval
Entropy, 2022 In recent years, searching and retrieving relevant images from large databases has become an emerging challenge for the researcher. Hashing methods that mapped raw data into a short binary code have attracted increasing attention from the researcher ...
Abid Hussain +5 more
doaj +1 more source
Remote Sensing Image Retrieval Based on Deep Multi-Similarity Hashing Method [PDF]
Jisuanji gongcheng, 2023 Hashing methods are widely used in remote sensing image retrieval owing to their low storage and high efficiency.Unsupervised hashing methods for remote sensing image retrieval tasks are often associated with unreliable pseudo-labeling, the same training
HE Yue, CHEN Guangsheng, JING Weipeng, XU Zekun
doaj +1 more source
Sensors, 2021 Recently, with the popularization of camera tools such as mobile phones and the rise of various short video platforms, a lot of videos are being uploaded to the Internet at all times, for which a video retrieval system with fast retrieval speed and high ...
Hanqing Chen +6 more
doaj +1 more source
Fusion-Supervised Deep Cross-Modal Hashing [PDF]
2019 IEEE International Conference on Multimedia and Expo (ICME), 2019 Deep hashing has recently received attention in cross-modal retrieval for its impressive advantages. However, existing hashing methods for cross-modal retrieval cannot fully capture the heterogeneous multi-modal correlation and exploit the semantic information.
Wang, Li +4 more
openaire +2 more sources
Discrete Robust Supervised Hashing for Cross-Modal Retrieval
IEEE Access, 2019 Cross-modal hashing has been studied extensively in the past decades for its significant advantage in computation and storage cost. For heterogeneous data points, the cross-modal hashing aims at learning a sharing Hamming space in where one query from ...
Tao Yao +4 more
doaj +1 more source
Kernelised supervised context hashing
IET Image Processing, 2016 Most existing supervised hashing methods learn the affinity‐preserving binary codes to represent the high‐dimensional data. However, each hashing code is assumed as independent and irrelevant with other codes. In practice, the authors find that there exists context association among hashing bits.
Yun‐Qiang Li +4 more
openaire +1 more source
Supervised Multi-scale Locality Sensitive Hashing [PDF]
Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, 2015 LSH is a popular framework to generate compact representations of multimedia data, which can be used for content based search. However, the performance of LSH is limited by its unsupervised nature and the underlying feature scale. In this work, we propose to improve LSH by incorporating two elements - supervised hash bit selection and multi-scale ...
Weng, Li +5 more
openaire +2 more sources