Results 31 to 40 of about 10,164 (194)
Deep Binary Representation for Efficient Image Retrieval
Advances in Multimedia, 2017 With the fast growing number of images uploaded every day, efficient content-based image retrieval becomes important. Hashing method, which means representing images in binary codes and using Hamming distance to judge similarity, is widely accepted for ...
Xuchao Lu +4 more
doaj +1 more source
Transformer-Based Discriminative and Strong Representation Deep Hashing for Cross-Modal Retrieval
IEEE Access, 2023 Cross-modal hashing retrieval has attracted extensive attention due to its low storage requirements as well as high retrieval efficiency. In particular, how to more fully exploit the correlation of different modality data and generate a more ...
Suqing Zhou +6 more
doaj +1 more source
Deep Supervised Hashing by Fusing Multiscale Deep Features
, 2023 Deep networks-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 structural information that contains important semantic details crucial for effective hash learning.
REDAOUI ADIL +2 more
openaire +1 more source
MIHash: Online Hashing with Mutual Information [PDF]
, 2017 Learning-based hashing methods are widely used for nearest neighbor retrieval, and recently, online hashing methods have demonstrated good performance-complexity trade-offs by learning hash functions from streaming data. In this paper, we first address a
Bargal, Sarah Adel +3 more
core +1 more source
IET Generation, Transmission & Distribution, 2021 With the development of smart grids, appliance‐level data information plays a vital role in smart power consumption. Nowadays, appliance signatures detected by non‐intrusive load monitoring (NILM) can be used for anomaly detection, demand response, and ...
Yinghua Han +3 more
doaj +1 more source
RelaHash: Deep Hashing With Relative Position
IEEE Access, 2023 Deep hashing has been widely used as a solution to encoding binary hash code for approximating nearest neighbor problem. It has been showing superior performance in terms of its ability to index high-level features by learning compact binary code.
Pham Vu Thai Minh +4 more
doaj +1 more source
Deep Supervised Discrete Hashing
, 2017 With the rapid growth of image and video data on the web, hashing has been extensively studied for image or video search in recent years. Benefit from recent advances in deep learning, deep hashing methods have achieved promising results for image retrieval.
Li, Qi +3 more
openaire +2 more sources
Dual Attention Triplet Hashing Network for Image Retrieval
Frontiers in Neurorobotics, 2021 In recent years, learning-based hashing techniques have proven to be efficient for large-scale image retrieval. However, since most of the hash codes learned by deep hashing methods contain repetitive and correlated information, there are some ...
Zhukai Jiang, Zhichao Lian, Jinping Wang
doaj +1 more source
Unsupervised Deep Hashing for Large-scale Visual Search [PDF]
, 2016 Learning based hashing plays a pivotal role in large-scale visual search. However, most existing hashing algorithms tend to learn shallow models that do not seek representative binary codes.
Feng, Xiaoyi +3 more
core +2 more sources
Deep Feature Pyramid Hashing for Efficient Image Retrieval
Information, 2022 Thanks to the success of deep learning, deep hashing has recently evolved as a leading method for large-scale image retrieval. Most existing hashing methods use the last layer to extract semantic information from the input image.
Adil Redaoui, Kamel Belloulata
doaj +1 more source