Results 101 to 110 of about 599,124 (143)

Uni-Retrieval: A Multi-Style Retrieval Framework for STEM's Education [PDF]

arXiv
In AI-facilitated teaching, leveraging various query styles to interpret abstract text descriptions is crucial for ensuring high-quality teaching. However, current retrieval models primarily focus on natural text-image retrieval, making them insufficiently tailored to educational scenarios due to the ambiguities in the retrieval process. In this paper,
arxiv  

Difficulties in Image Retrieval

, 2009
The semantic gap is often regarded as a major problem in the field of image retrieval research. In this paper, I will show that there are other important topics that should be addressed for improving the image retrieval utility. Among them, the exploitation of limited information and motivating the use of images are considered to be central to ...
openaire   +3 more sources

Image retrieval based on the feature of VLAD and sparse representation

Dianxin kexue, 2016
In order to achieve the goal of fast and accurate image retrieval,an image retrieval method combining VLAD （vector of locally aggregated descriptor）feature and sparse representation was proposed.
Wen YAN, Wei JIN, Randi FU
doaj   +2 more sources

Spatial Reasoning for Image Retrieval

, 1999
Building upon the previously introduced description logic of concrete domains, we provide a system which is aimed at enhancing image retrieval with the ability to perform spatial reasoning. In this early stage of our research we focus on obtaining a formalism which is expressive enough to increase the usefulness of expensive picture descriptions ...
Aiello, M., Areces, C.E., de Rijke, M.
openaire   +4 more sources

Human-Oriented Image Retrieval System (HORSE): A Neuro-Symbolic Approach to Optimizing Retrieval of Previewed Images [PDF]

arXiv
Image retrieval remains a challenging task due to the complex interaction between human visual perception, memory, and computational processes. Current image search engines often struggle to efficiently retrieve images based on natural language descriptions, as they rely on time-consuming preprocessing, tagging, and machine learning pipelines.
arxiv  

Knowledge-aware Text-Image Retrieval for Remote Sensing Images [PDF]

arXiv
Image-based retrieval in large Earth observation archives is challenging because one needs to navigate across thousands of candidate matches only with the query image as a guide. By using text as information supporting the visual query, the retrieval system gains in usability, but at the same time faces difficulties due to the diversity of visual ...
arxiv  

Farbbasiertes Image Retrieval

, 2019
This (German) bachelor thesis discusses to what extent the feature color helps for content-based image retrieval. It analyses the use of different color spaces as well as different spatial segmentations of the image. It seems that color alone is not a very helpful feature for content-based image retrieval.
openaire   +2 more sources

Content-Based Image Retrieval for Multi-Class Volumetric Radiology Images: A Benchmark Study [PDF]

arXiv
While content-based image retrieval (CBIR) has been extensively studied in natural image retrieval, its application to medical images presents ongoing challenges, primarily due to the 3D nature of medical images. Recent studies have shown the potential use of pre-trained vision embeddings for CBIR in the context of radiology image retrieval. However, a
arxiv  

A privacy-preserving image retrieval scheme with access control based on searchable encryption in media cloud

Cybersecurity
With the popularity of the media cloud computing industry, individuals and organizations outsource image computation and storage to the media cloud server to reduce the storage burden.
Miao Tian, Yushu Zhang, Yongming Zhang, Xiangli Xiao, Wenying Wen   +4 more
doaj   +1 more source

Composed Multi-modal Retrieval: A Survey of Approaches and Applications [PDF]

arXiv
With the rapid growth of multi-modal data from social media, short video platforms, and e-commerce, content-based retrieval has become essential for efficiently searching and utilizing heterogeneous information. Over time, retrieval techniques have evolved from Unimodal Retrieval (UR) to Cross-modal Retrieval (CR) and, more recently, to Composed Multi ...
arxiv