Results 31 to 40 of about 5,580,472 (385)
Large image datasets: A pyrrhic win for computer vision? [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2020 In this paper we investigate problematic practices and consequences of large scale vision datasets (LSVDs). We examine broad issues such as the question of consent and justice as well as specific concerns such as the inclusion of verifiably pornographic ...
Vinay Uday Prabhu, Abeba Birhane
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Learning to Resize Images for Computer Vision Tasks [PDF]
IEEE International Conference on Computer Vision, 2021 For all the ways convolutional neural nets have revolutionized computer vision in recent years, one important aspect has received surprisingly little attention: the effect of image size on the accuracy of tasks being trained for.
Hossein Talebi, P. Milanfar
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A Convolutional Neural Network for Nonrigid Structure from Motion
International Journal of Digital Multimedia Broadcasting, 2022 In this study, we propose a reconstruction and optimization neural network (RONN), a novel neural network for nonrigid structure from motion, which is completed by an unsupervised convolution neural network.
Yaming Wang +3 more
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The Visual Computer, 2021 The research progress in multimodal learning has grown rapidly over the last decade in several areas, especially in computer vision. The growing potential of multimodal data streams and deep learning algorithms has contributed to the increasing ...
Khaled Bayoudh +3 more
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Automatic evaluation of practices in Moodle for Self Learning in Engineering
Journal of Technology and Science Education, 2015 The first years in engineering degree courses are usually made of large groups with a low teacher-student ratio. Overcrowding in classrooms hinders continuous assessment much needed to promote independent learning.
Carles Sanchez +5 more
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Tensor Methods in Computer Vision and Deep Learning [PDF]
Proceedings of the IEEE, 2021 Tensors, or multidimensional arrays, are data structures that can naturally represent visual data of multiple dimensions. Inherently able to efficiently capture structured, latent semantic spaces and high-order interactions, tensors have a long history ...
Yannis Panagakis +6 more
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Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey [PDF]
IEEE Access, 2018 Deep learning is at the heart of the current rise of artificial intelligence. In the field of computer vision, it has become the workhorse for applications ranging from self-driving cars to surveillance and security.
Naveed Akhtar, A. Mian
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Manuscript Investigation in the Sinai II Project
Digital Presentation and Preservation of Cultural and Scientific Heritage, 2014 This work is concerned with the analysis of historical manuscripts. The manuscripts investigated are partially in a bad condition, due to their age, bad storage conditions etc.
Fabian Hollaus +4 more
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Deep Learning for Computer Vision: A Brief Review
Computational Intelligence and Neuroscience, 2018 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.
A. Voulodimos +3 more
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Recent Advances of Continual Learning in Computer Vision: An Overview [PDF]
IET Computer Vision, 2021 In contrast to batch learning where all training data is available at once, continual learning represents a family of methods that accumulate knowledge and learn continuously with data available in sequential order.
Haoxuan Qu +4 more
semanticscholar +1 more source