Results 71 to 80 of about 599,124 (143)
2-bit Model Compression of Deep Convolutional Neural Network on ASIC Engine for Image Retrieval [PDF]
arXiv, 2019 Image retrieval utilizes image descriptors to retrieve the most similar images to a given query image. Convolutional neural network (CNN) is becoming the dominant approach to extract image descriptors for image retrieval. For low-power hardware implementation of image retrieval, the drawback of CNN-based feature descriptor is that it requires hundreds ...
arxiv
Tag Completion for Image Retrieval [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013 Many social image search engines are based on keyword/tag matching. This is because tag-based image retrieval (TBIR) is not only efficient but also effective. The performance of TBIR is highly dependent on the availability and quality of manual tags. Recent studies have shown that manual tags are often unreliable and inconsistent.
Lei Wu, Rong Jin, Anil K. Jain
openaire +3 more sources
Co-word mapping of Image Retrieval based on Web of Science-Indexed Papers
مجله علمسنجی کاسپین, 2018 Background and aim: Given the special status and wide usage of image retrieval in various fields, the present investigation studied on the research trends and significant factors within the field of image retrieval and drawing the co-word map based on ...
Samira Daniali +2 more
doaj
Medicallmage Retrieval Method Based on Multi Feature Hierarchical Fusion
Journal of Harbin University of Science and Technology, 2017 In order to solve the problem of medical equipment image retrieval，an image retrieval method based on multi feature layer fusion is proposed. Process:This method using color moments to calculate the characteristics of color image，the LBP Operator is used
SHAH Qang, SUN Xiao-ming
doaj +1 more source
Image retrieval by hypertext links [PDF]
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '97, 1997 This paper presents a model for retrieval of images from a large World Wide Web based collection. Rather than considering complex visual recognition algorithms, the model presented is based on combining evidence of the text content and hypertext structure of the Web.
Harmandas, V. +2 more
openaire +4 more sources
Image-Text Retrieval Backdoor Attack with Diffusion-Based Image-Editing [PDF]
Jisuanji kexue yu tansuoDeep neural networks are susceptible to backdoor attacks during the training stage. When training an image-text retrieval model, if an attacker maliciously injects image-text pairs with a backdoor trigger into the training dataset, the backdoor will be ...
YANG Shun, LU Hengyang
doaj +1 more source
Deep Discrete Hashing with Self-supervised Pairwise Labels
, 2017 Hashing methods have been widely used for applications of large-scale image retrieval and classification. Non-deep hashing methods using handcrafted features have been significantly outperformed by deep hashing methods due to their better feature ...
A Andoni +12 more
core +1 more source
Neural network feature learning based on image self-encoding
International Journal of Advanced Robotic Systems, 2020 With the rapid development of information technology and the arrival of the era of big data, people’s access to information is increasingly relying on information such as images.
Yangyang Liu +3 more
doaj +1 more source
Local Feature Detectors, Descriptors, and Image Representations: A Survey [PDF]
arXiv, 2016 With the advances in both stable interest region detectors and robust and distinctive descriptors, local feature-based image or object retrieval has become a popular research topic. %All of the local feature-based image retrieval system involves two important processes: local feature extraction and image representation.
arxiv
Region-Based Image Retrieval Revisited
, 2017 Region-based image retrieval (RBIR) technique is revisited. In early attempts at RBIR in the late 90s, researchers found many ways to specify region-based queries and spatial relationships; however, the way to characterize the regions, such as by using ...
Hinami, Ryota +2 more
core +1 more source