Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein.
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Publication date: Available online 4 January 2018 Source: European Journal of Radiology Author(s): Peiyao Zhang, Jing Wang, Qin Xu, Zhen...
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Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182, Butyric Acid from Probiotic Staphyloco...
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Does CBD Oil Lower Blood Pressure? This article was originally published at SundayScaries." Madeline Taylor POSTED ON January 13, 20...
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Medicine by Alexandros G. Sfakianakis,Αλέξανδρος Γ. Σφακιανάκης A Novel Technique for Endoscopic Repair of Large Anterior Skull Base Defect...
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2016-11-22T07-55-59Z Source: International Journal of Medical Science and Public Health Banothu Srinivas, Madhu Mohan Reddy B. Backgrou...
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2016-10-15T06-30-01Z Source: The Southeast Asian Journal of Case Report and Review Sangita Deepak Kamath, Neeraj Jain, Saurabh Pathak, Ba...
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BACKGROUND AND PURPOSE: Lesion load is a common biomarker in multiple sclerosis, yet it has historically shown modest association with cl...
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Abstract The development of focused ion beam-scanning electron microscopy (FIB-SEM) techniques has allowed high-resolution 3D imaging of n...
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Vol.48 No.2 from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/1S2Z7n2 via IFTTT
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