A review on content based image retrieval by different Techniques

Saini, Antima; Bharti, Rajendra Kumar

doi:10.21742/ijnse.2017.1.1.01

Cited by 2 publications

(2 citation statements)

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“…Early image retrieval technologies are mainly divided into two categories ( Antima & Rajendra, 2017 ): text-based image retrieval (TBIR) and content-based image retrieval (CBIR). TBIR uses text annotation to describe keywords of image information.…”

Section: Introductionmentioning

confidence: 99%

Exploration of Chinese cultural communication mode based on the Internet of Things and mobile multimedia technology

Xie

Yin

2023

PeerJ Computer Science

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Image retrieval technology has emerged as a popular research area of China’s development of cultural digital image dissemination and creative creation with the growth of the Internet and the digital information age. This study uses the shadow image in Shaanxi culture as the research object, suggests a shadow image retrieval model based on CBAM-ResNet50, and implements it in the IoT system to achieve more effective deep-level cultural information retrieval. First, ResNet50 is paired with an attention mechanism to enhance the network’s capacity to extract sophisticated semantic characteristics. The second step is configuring the IoT system’s picture acquisition, processing, and output modules. The image processing module incorporates the CBAM-ResNet50 network to provide intelligent and effective shadow play picture retrieval. The experiment results show that shadow plays on GPU can retrieve images at a millisecond level. Both the first image and the first six photographs may be accurately retrieved, with a retrieval accuracy of 92.5 percent for the first image. This effectively communicates Chinese culture and makes it possible to retrieve detailed shadow-play images.

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Section: Introductionmentioning

confidence: 99%

Exploration of Chinese cultural communication mode based on the Internet of Things and mobile multimedia technology

Xie

Yin

2023

PeerJ Computer Science

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“…It is very fast and efficient technique. Many commercial and academic systems used CH for image retrieval such as QBIC, NETRA, RETIN, KIWI, and Image Minor [3]. Email still fill in as imperative application to store data and information for their day by day activities [4].…”

Section: Introductionmentioning

confidence: 99%

An Online Content Based Email Attachments Retrieval System

Jameel

Mohammed

George

2017

KJAR

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E-mail is one of the most popular programs used by most people today. As a result of the continuous daily use, thousands of messages are accumulated in the electronic box of most individuals, which make it difficult for them after a period of time to retrieve the attachments of these messages. Most Email providers constantly improved their search technology, but till now there is something could not be done; i.e., searching inside attachments. Some email providers like Gmail has added searching words inside attachments for some file types (.pdf files, .doc documents, .ppt presentations) but for image files this feature not supported till now. However, E-mail providers and even modern researches have not focused on retrieving the image attachments in the Email box. The paper was aimed to introduce a novel idea of using Content based Image Retrieval (CBIR) in E-mail application to retrieve images from email attachments based on entire contents. The work main phases are: feature extraction based on color features and connect to Email server to read Emails, the second phase is retrieving similar image attachments. The tests carried on mail inbox contain 100 messages with 500 image attachments and gave good precision and recall rates When the threshold value is less than or equal to 0.4.

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A review on content based image retrieval by different Techniques

Abstract: In present time image data is growing up day by day in a large

Cited by 2 publications

References 4 publications

Exploration of Chinese cultural communication mode based on the Internet of Things and mobile multimedia technology

Exploration of Chinese cultural communication mode based on the Internet of Things and mobile multimedia technology

An Online Content Based Email Attachments Retrieval System

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