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Showing 1 to 8 of 8 for “"image tagging"”.
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Semantically-enhanced image tagging system
In multimedia databases, data are images, audio, video, texts, etc. Research interests in these types of databases have increased in the last decade or so, especially with the advent of the Internet and Semantic Web. Fundamental research issues vary from unified data modelling, retrieval of data …
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Rethinking Serverless for Machine Learning Inference
… language detection, tweet classification, image tagging, and free-tier-chat-bots do not require real-time inference. All these characteristics make serverless platforms a good fit for deployment, and in this work, we identify the bottlenecks involved in hosting these inference jobs on …
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Recognition of dates handwritten on cheques
… is described. This system is composed of date image segmentation, handwritten digit recognition, and cursive word recognition. The proposed method does not impose any restriction or require any a priori information on the date written, and is able to handle both English and French cheques. With …
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Using Generative Adversarial Networks to Classify Structural Damage Caused by Earthquakes
<p>The amount of structural damage image data produced in the aftermath of an earthquake can be staggering. It is challenging for a few human volunteers to efficiently filter and tag these images with meaningful damage information. There are several solution to automate post-earthquake …
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Motivations to Upload and Tag Images vs. Tagging Practice: An Investigation of the Web 2.0 Site Flickr
Digital images are being created and uploaded online in large numbers and this can be attributed to three main interconnected factors: a change in attitudes towards photography and its role in society; technological advancements in the camera industry; and changes in web technology. Many of these …
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Leveraging the Information Redundancy In Wireless and Mobile Environments
… a mobile phone based auto-tagging system that can automatically sense and tag the people/activity/context in a picture, The main challenge pertains to discriminating phone users that are in the picture, from those that are not. We proposed method by exploiting the redundancy …
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Learning and inference with Wasserstein metrics
… We demonstrate this property on a real-data image tagging problem, outperforming a baseline that doesn't use the metric. In the second part, we consider the probabilistic inference problem for diffusion processes. Such processes model a variety of stochastic phenomena and appear often in …
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Acceleration of Jaccard's Index Algorithm for Training to Tag Damage on Post-earthquake Images
… Networks (NN) to automatically label damages on images of above ground infrastructure (buildings made of concrete) taken after an earthquake. The goal of the supervised NN is to classify raw input data according to the patterns learned from an input training set. This input training data set is …