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Neuromorphic computing for content-based image retrieval. [PDF]
PLoS ONE, 2022 Neuromorphic computing mimics the neural activity of the brain through emulating spiking neural networks. In numerous machine learning tasks, neuromorphic chips are expected to provide superior solutions in terms of cost and power efficiency.
Te-Yuan Liu +3 more
doaj +5 more sources
Content-Based Histopathological Image Retrieval [PDF]
SensorsFeature descriptors in histopathological images are an important challenge for the implementation of Content-Based Image Retrieval (CBIR) systems, an essential tool to support pathologists.
Camilo Nuñez-Fernández +2 more
doaj +3 more sources
Saliency-Based Image Retrieval as a Refinement to Content-Based Image Retrieval [PDF]
ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2021 Searching for an image in a database is important in different applications; hence, many algorithms have been proposed to identify the contents of the image.
Mohammad A. N. Al-Azawi
doaj +5 more sources
CONTENT-BASED IMAGE RETRIEVAL: SURVEY [PDF]
Journal of Engineering and Sustainable Development, 2019 Extensive use of digital photographic devices has resulted in large volumes of digital images being acquired and stored in databases. Whether it is for scientific research, medical or social networking, there is a growing demand for effective retrieval ...
Hanan Ahmed Al-Jubouri
doaj +4 more sources
Interactive Content Based Image Retrieval using Multiuser Feedback
JOIV: International Journal on Informatics Visualization, 2017 Retrieving images from large databases becomes a difficult task. Content based image retrieval (CBIR) deals with retrieval of images based on their similarities in content (features) between the query image and the target image.
M. Premkumar, R. Sowmya
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Image Retrieval Berdasarkan Fitur Warna, Bentuk, dan Tekstur [PDF]
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 +3 more sources
Automated benchmarking in content-based image retrieval
IEEE International Conference on Multimedia and Expo, 2001. ICME 2001., 2001 Benchmarking has always been a crucial problem in content-based image retrieval (CBIR). A key issue is the lack of a common access method to retrieval systems, such as SQL for relational databases. The Multimedia Retrieval Mark-up Language (MRML) solves this problem by standardizing access to CBIR systems (CBIRSs).
Henning Müller +4 more
openalex +5 more sources
Medical Image Retrieval: Past and Present [PDF]
Healthcare Informatics Research, 2012 With the widespread dissemination of picture archiving and communication systems (PACSs) in hospitals, the amount of imaging data is rapidly increasing. Effective image retrieval systems are required to manage these complex and large image databases. The
Kyung Hoon Hwang +2 more
doaj +4 more sources
An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model. [PDF]
PLoS One, 2018 For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository.
Jabeen S +5 more
europepmc +2 more sources
Content-Based Image Retrieval for Semiconductor Process Characterization [PDF]
EURASIP Journal on Advances in Signal Processing, 2002 Image data management in the semiconductor manufacturing environment is becoming more problematic as the size of silicon wafers continues to increase, while the dimension of critical features continues to shrink.
Kenneth W. Tobin +5 more
doaj +2 more sources