Results 11 to 20 of about 1,980,897 (317)
Convolutional Neural Nets in Chemical Engineering: Foundations, Computations, and Applications [PDF]
AICHE Journal, 2021 In this paper we review the mathematical foundations of convolutional neural nets (CNNs) with the goals of: i) highlighting connections with techniques from statistics, signal processing, linear algebra, differential equations, and optimization, ii ...
Shengli Jiang, Victor M Zavala
exaly +5 more sources
A taxonomy of Deep Convolutional Neural Nets for Computer Vision [PDF]
Frontiers in Robotics and AI, 2016 Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features.
Suraj eSrinivas +5 more
doaj +6 more sources
Entangled q-convolutional neural nets [PDF]
Machine Learning: Science and Technology, 2021 We introduce a machine learning model, the q-CNN model, sharing key features with convolutional neural networks and admitting a tensor network description. As examples, we apply q-CNN to the MNIST and Fashion MNIST classification tasks.
V. Anagiannis, Miranda C. N. Of Cheng
semanticscholar +4 more sources
ROADSIDE FOREST MODELING USING DASHCAM VIDEOS AND CONVOLUTIONAL NEURAL NETS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Tree failure is a primary cause of storm-related power outages throughout the United States. Roadside vegetation management is therefore critical to electric utility companies to prevent power outages during extreme weather conditions. It is difficult to
D. Joshi, C. Witharana
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Applied Sciences (Switzerland), 2021 Trust in artificial intelligence (AI) predictions is a crucial point for a widespread acceptance of new technologies, especially in sensitive areas like autonomous driving. The need for tools explaining AI for deep learning of images is thus eminent. Our
Tim Dahmen, Payman Goodarzi, Fei Chen
exaly +2 more sources
Region-Based Convolutional Neural Nets for Localization of Glomeruli in Trichrome-Stained Whole Kidney Sections. [PDF]
J Am Soc Nephrol, 2018 Background Histologic examination of fixed renal tissue is widely used to assess morphology and the progression of disease. Commonly reported metrics include glomerular number and injury.
Bukowy JD +8 more
europepmc +2 more sources
Inferring Depth Contours From Sidescan Sonar Using Convolutional Neural Nets
IET Radar, Sonar and Navigation, 2020 Sidescan sonar images are 2D representations of the seabed. The pixel location encodes distance from the sonar and along track coordinate. Thus one dimension is lacking for generating bathymetric maps from sidescan.
Yiping Xie, John Folkesson, Nils Bore
exaly +2 more sources
Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets With Multi-Stream Inputs [PDF]
IEEE Access, 2020 Understanding driver activity is vital for in-vehicle systems that aim to reduce the incidence of car accidents rooted in cognitive distraction. Automating real-time behavior recognition while ensuring actions classification with high accuracy is however
Chaoyun Zhang +4 more
doaj +2 more sources
Frontiers in Water, 2020 High-quality and high-resolution precipitation products are critically important to many hydrological applications. Advances in satellite remote sensing instruments and data retrieval algorithms continue to improve the quality of the operational ...
Alexander Y. Sun +2 more
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CE-Dedup: Cost-Effective Convolutional Neural Nets Training based on Image Deduplication [PDF]
2021 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), 2021 Attributed to the ever-increasing large image datasets, Convolutional Neural Networks (CNNs) have become popular for vision-based tasks. It is generally admirable to have larger-sized datasets for higher network training accuracies.
Xuan Li, Li-Qiong Chang, Xue Liu
semanticscholar +1 more source