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Hyunkyung Shin, Hyeonung Shin, Wonje Choi, Jaesung Park, Minjae Park, Euiyul Koh and Honguk Woo
The automatic analysis of medical data and images to help diagnosis has recently become a major area in the application of deep learning. In general, deep learning techniques can be effective when a large high-quality dataset is available for model train...
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Theodoros Psallidas, Panagiotis Koromilas, Theodoros Giannakopoulos and Evaggelos Spyrou
The exponential growth of user-generated content has increased the need for efficient video summarization schemes. However, most approaches underestimate the power of aural features, while they are designed to work mainly on commercial/professional video...
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Xi Yu, Bing Ouyang and Jose C. Principe
Deep neural networks provide remarkable performances on supervised learning tasks with extensive collections of labeled data. However, creating such large well-annotated data sets requires a considerable amount of resources, time and effort, especially f...
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Youssef Skandarani, Pierre-Marc Jodoin and Alain Lalande
Deep learning methods are the de facto solutions to a multitude of medical image analysis tasks. Cardiac MRI segmentation is one such application, which, like many others, requires a large number of annotated data so that a trained network can generalize...
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Karen Panetta, Landry Kezebou, Victor Oludare, James Intriligator and Sos Agaian
The concept of searching and localizing vehicles from live traffic videos based on descriptive textual input has yet to be explored in the scholarly literature. Endowing Intelligent Transportation Systems (ITS) with such a capability could help solve cri...
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