Browsing by Subject "CNN"
Now showing items 1-9 of 9
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(2021-12-07)Deep learning algorithms are highly energy and memory-intensive as their performance increases with an increasing amount of data. Moore’s law coming to an end and the ever-increasing demand for high computational power by ...
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(2022-12-09)Video monitoring is essential for a variety of coastal research. While monitoring can provide a wealth of information about coastal processes, extracting relevant information from in-situ beach photography remains challenging. ...
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(2022-07-26)Magnetic resonance imaging (MRI) is a noninvasive imaging modality that produces high-quality images. One of the biggest challenges in MRI is the lengthy scan procedure which could lead to motion artifact and patient ...
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(2018-11-06)Convolution neural networks have become one of the dominating deep learning models, especially for computation vision tasks such as image classification and segmentation. Dense convolution filters are inefficient, due to ...
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(2019-07-09)Facial expressions plan a very important role in interpersonal relations as they convey nonverbal cues. Automatic recognition of facial expressions forms a crucial component in human-machine interfaces. The main motivation ...
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(2019-10-30)High Efficiency Video Coding (HEVC) is also know as H.265 was first official introduced in 2013, it is one of the video coding standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. ...
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(2022-04-19)There are several methods in the exploration of Convolutional Neural Network’s (CNN’s) inner workings. However, in general, finding the inverse of the function performed by CNN as a whole is an ill-posed problem. We propose ...
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(2023-07-11)In this project, we seek to provide a computer vision model that can detect and classify traffic signs and lights for autonomous vehicles. Such a model enables proper information transmission to the controller so that ...
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(2020-12-02)Convolutional Neural Networks have become the standard mechanism for machine vision problems due to their high accuracy and ability to keep improving with new data. Although precise, these algorithms are mathematically ...