Results 31 to 40 of about 5,349,509 (291)
CNN Variants for Computer Vision: History, Architecture, Application, Challenges and Future Scope
Electronics, 2021 Computer vision is becoming an increasingly trendy word in the area of image processing. With the emergence of computer vision applications, there is a significant demand to recognize objects automatically.
Dulari Bhatt +7 more
semanticscholar +1 more source
The Programming Historian, 2022 This is the first of a two-part lesson introducing deep learning based computer vision methods for humanities research. Using a dataset of historical newspaper advertisements and the fastai Python library, the lesson walks through the pipeline of ...
Daniel van Strien +4 more
doaj +1 more source
Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades [PDF]
, 2015 Creating datasets for Neuromorphic Vision is a challenging task. A lack of available recordings from Neuromorphic Vision sensors means that data must typically be recorded specifically for dataset creation rather than collecting and labelling existing ...
Ajinkya eJayawant +4 more
core +3 more sources
Fruits and vegetables quality evaluation using computer vision: A review
Journal of King Saud University: Computer and Information Sciences, 2021 In agriculture science, automation increases the quality, economic growth and productivity of the country. The export market and quality evaluation are affected by assorting of fruits and vegetables.
Anuja Bhargava, A. Bansal
semanticscholar +1 more source
Deep reinforcement learning in computer vision: a comprehensive survey [PDF]
Artificial Intelligence Review, 2021 Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works have demonstrated the remarkable successes of deep reinforcement learning in various domains ...
Ngan T. H. Le +4 more
semanticscholar +1 more source
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
semanticscholar +1 more source
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
semanticscholar +1 more source
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
doaj +1 more source
International Journal for Research in Applied Science and Engineering Technology, 2023 Abstract: Computer vision is a field of artificial intelligence that focuses on enabling computers to understand and interpret visual information from images or videos. It involves developing algorithms and techniques to extract meaningful insights, patterns, and knowledge from visual data, mimicking human visual perception capabilities.
openaire +1 more source
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
semanticscholar +1 more source