Results 41 to 50 of about 599,124 (143)
Deep Learning Based Image Retrieval in the JPEG Compressed Domain [PDF]
arXiv, 2021 Content-based image retrieval (CBIR) systems on pixel domain use low-level features, such as colour, texture and shape, to retrieve images. In this context, two types of image representations i.e. local and global image features have been studied in the literature.
arxiv
Autoencoding the Retrieval Relevance of Medical Images
, 2015 Content-based image retrieval (CBIR) of medical images is a crucial task that can contribute to a more reliable diagnosis if applied to big data. Recent advances in feature extraction and classification have enormously improved CBIR results for digital ...
Camlica, Zehra +2 more
core +1 more source
Standardized interoperable image retrieval
Proceedings of the 2010 ACM Symposium on Applied Computing, 2010 Digital still images are generated, distributed and stored worldwide at an ever increasing rate. Yet, the large number of available metadata description formats prevents consistent and efficient access to image repositories. Standardized solutions for unifying the access and the retrieval of image repositories are therefore strongly needed. The ISO/IEC
Döller, Mario +4 more
openaire +3 more sources
Co-word mapping of Image Retrieval based on Web of Science-Indexed Papers [PDF]
مجله علمسنجی کاسپین, 2017 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
Multi-PQTable for Approximate Nearest-Neighbor Search
Information, 2019 Image retrieval or content-based image retrieval (CBIR) can be transformed into the calculation of the distance between image feature vectors. The closer the vectors are, the higher the image similarity will be.
Xinpan Yuan +4 more
doaj +1 more source
Mr. Right: Multimodal Retrieval on Representation of ImaGe witH Text [PDF]
arXiv, 2022 Multimodal learning is a recent challenge that extends unimodal learning by generalizing its domain to diverse modalities, such as texts, images, or speech. This extension requires models to process and relate information from multiple modalities. In Information Retrieval, traditional retrieval tasks focus on the similarity between unimodal documents ...
arxiv
An approach to image retrieval for image databases [PDF]
, 1993 In this paper, a method is discussed to store and retrieve images efficiently from an image database on the basis of the data structure called E() representation. The E() representation is a spatial knowledge representation preserving the spatial information between objects embedded in symbolic images as an iconic index for the purpose of efficient ...
Gevers, T., Smeulders, A.W.M.
openaire +4 more sources
Overview of the 2005 cross-language image retrieval track (ImageCLEF) [PDF]
, 2005 The purpose of this paper is to outline efforts from the 2005 CLEF crosslanguage image retrieval campaign (ImageCLEF). The aim of this CLEF track is to explore the use of both text and content-based retrieval methods for cross-language image retrieval ...
Clough, P. +6 more
core
Exploiting Local Features from Deep Networks for Image Retrieval
, 2015 Deep convolutional neural networks have been successfully applied to image classification tasks. When these same networks have been applied to image retrieval, the assumption has been made that the last layers would give the best performance, as they do ...
Davis, Larry S. +2 more
core +1 more source
Image Retrieval Berdasarkan Fitur Warna, Bentuk, dan Tekstur
ComTech, 2014 Along with the times, information retrieval is no longer just on textual data, but also the visual data. The technique was originally used is Text-Based Image Retrieval (TBIR), but the technique still has some shortcomings such as the relevance of the ...
Rita Layona +2 more
doaj +1 more source