Results 31 to 40 of about 86,091 (310)
A Simple Neural Network Approach to Mineral Potential Mapping Using Open Gravity Data [PDF]
E3S Web of ConferencesAs a fundamental approach in machine learning, neural networks have evolved through phases of emergence, relative dormancy, and subsequent flourishing since their inception.
Ji Jiaxin
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P-CNN: Pose-Based CNN Features for Action Recognition [PDF]
2015 IEEE International Conference on Computer Vision (ICCV), 2015 ICCV, December 2015, Santiago ...
Chéron, Guilhem +2 more
openaire +3 more sources
Driving Scene Understanding using Spiking Neural Networks [PDF]
, 2021 One of the applications of AI lies in developing intelligent systems for safe on-road driving, other than building and perfecting self-driving vehicles, and many others.
Gaurav, Ramashish
core
Evaluating 'Graphical Perception' with CNNs
, 2018 Convolutional neural networks can successfully perform many computer vision tasks on images. For visualization, how do CNNs perform when applied to graphical perception tasks?
James Tompkin +2 more
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Evaluation of the benchmark datasets for testing the efficacy of deep convolutional neural networks
Visual Informatics, 2021 In the past decade, deep neural networks, and specifically convolutional neural networks (CNNs), have been becoming a primary tool in the field of biomedical image analysis, and are used intensively in other fields such as object or face recognition ...
Sanchari Dhar, Lior Shamir
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Automatic Cough Detection from Audio Signals Using Deep Learning and Hybrid CNN–SVM Models [PDF]
EPJ Web of ConferencesCoughing is a natural physiological reflex that helps maintain respiratory health by clearing the airways of irritants, fluids, and pathogens. It also serves as a key clinical indicator for various respiratory conditions, including asthma, infections ...
Barkani Fatima +2 more
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Parameter Distribution Balanced CNNs.
, 2021 Convolutional neural network (CNN) is the primary technique that has greatly promoted the development of computer vision technologies. However, there is little research on how to allocate parameters in different convolution layers when designing CNNs. We
Wei, S +4 more
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REAL TIME EMBBEDED RGB-D SLAM USING CNNS FOR DEPTH ESTIMATION AND FEATURE EXTRACTION [PDF]
, 2023 "A robust and efficient Simultaneous Localization and Mapping (SLAM) system is essential for intelligent mobile robots to work in unknown environments.
Marcos Renato Rocha Hernández
core
Dynamic Hyperspectral Pansharpening CNNs
, 2023 International audienceHyperspectral (HS) pansharpening seeks to integrate low spatial resolution HS (LRHS) images with connected panchromatic (PAN) images to produce high spatial resolution HS (HRHS) images. Traditional pansharpening convolutional neural
Li, Jun +5 more
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Adaptive Deep Learning for Soft Real-Time Image Classification
Technologies, 2021 CNNs (Convolutional Neural Networks) are becoming increasingly important for real-time applications, such as image classification in traffic control, visual surveillance, and smart manufacturing.
Fangming Chai, Kyoung-Don Kang
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