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Enhancing movie script creation through retrieval-augmented LLMs and stable diffusion scene modeling. [PDF]
Sci RepLulla A +4 more
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Preprocessing for content-based image retrieval. [PDF]
, 2009 The research focuses on image retrieval problems where the query is formed as an image of a specific object of interest. The broad aim is to investigate pre-processing for retrieval of images of objects when an example image containing the object is given. The object may be against a variety of backgrounds.
Rodhetbhai, Wasara
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Localized content based image retrieval
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval, 2005We define localized content-based image retrieval as a CBIR task where the user is only interested in a portion of the image, and the rest of the image is irrelevant. In this paper we present a localized CBIR system, Accio, that uses labeled images in conjunction with a multiple-instance learning algorithm to first identify the desired object and ...
Rouhollah Rahmani +4 more
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Content-Based Image Retrieval in Astronomy
Information Retrieval, 2000Summary: Content-based image retrieval in astronomy needs methods that can deal with an image content made of noisy and diffuse structures. This motivates investigations on how information should be summarized and indexed for this specific kind of images.
André Csillaghy +2 more
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Faceted Content-Based Image Retrieval
2008 19th International Conference on Database and Expert Systems Applications, 2008In typical content-based image retrieval systems it is not possible to navigate the image space by simultaneously applying multiple similarity criteria. The model we propose addresses this problem by representing the search for the images similar to a given image as the exploration of a lattice of (non-disjoint) image clusters, induced by a natural ...
Amato G, Meghini C
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Content based image and video retrieval
SPIE Proceedings, 2010The growing capacity of computers, the abundance of digital cameras and the increased connectivity of the world all point to large digital multimedia archives. They include images and videos from the World Wide Web, museum objects, flowers, trademarks, and views from everyday life.
Shubhangi H. Patil +4 more
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SPIE Proceedings, 2010
Large collection of information is being created in many areas of modern life on daily basis. This information exists in many forms from plain text to high resolution multimedia. Today computers are many times faster than human in text based searching using keywords and indexing but the story is totally different in case of multimedia.
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Large collection of information is being created in many areas of modern life on daily basis. This information exists in many forms from plain text to high resolution multimedia. Today computers are many times faster than human in text based searching using keywords and indexing but the story is totally different in case of multimedia.
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Prefetching for content-based image retrieval
Proceedings. IEEE International Conference on Multimedia and Expo, 2003Currently, research on content-based image retrieval (CBIR) is focused on the improvement of retrieval performance using relevance feedback techniques. However, for the remote user, retrieval latency is also a critical metric of satisfaction. In this paper, we show how to integrate the prefetching mechanism into the CBIR system in order to reduce ...
Janghyun Yoon, Nikil Jayant
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Content Based Image Retrieval with Hadoop
2016Hadoop has become a widely used open source framework for large scale data processing. MapReduce is the core component of Hadoop. It is this programming paradigm that allows for massive scalability across hundreds or thousands of servers in a Hadoop cluster. It allows processing of extremely large video files or image files on data nodes.
Heba Gaber +3 more
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Content Based Image Retrieval for Unsegmented Images
2003We present a new method for image retrieval by shape similarity able to deal with real images with not uniform background and possible touching/occluding objects. First of all we perform a sketch-driven segmentation of the scene by means of a Deformation Tolerant version of the Generalized Hough Transform (DTGHT). Using the DTGHT we select in the image
Marco Anelli +2 more
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