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IEEE15h
Integrated Monitoring of Stress and Damage Using CNN Deep Learning of Electromechanical Impedance Responses of CSA Sensor - IEEE Xplore
A multitask 2D CNN model is designed for integrated monitoring stress and damage in concrete specimens utilizing the raw impedance signatures of capsule-like smart aggregated (CSA). The fundamental ...
Microsoft, OpenAI and Anthropic are investing millions to train teachers how to use AI
A group of leading tech companies is teaming up with two teachers’ unions to train 400,000 kindergarten through 12th grade teachers in artificial intelligence over the next five years.
IEEE1d
Musical Instrument Classification Using Deep Learning CNN Models
Musical instrument recognition is the act of counting on machine learning or the application of signal processing to isolate and classify various musical instruments in an audio track. Such capability ...
Devdiscourse2d
Oceans and AI: Scientists use deep learning to combat climate crisis
Oceans are facing a multitude of climate-induced stresses including acidification, sea-level rise, warming waters, and ice ...
IEEE2d
An automated early ischemic stroke detection system using CNN deep learning algorithm - IEEE Xplore
Over the past few years, stroke has been among the top ten causes of death in Taiwan. Stroke symptoms belong to an emergency condition, the sooner the patient is treated, the more chance the patient ...
IEEE3d
Deep CNN-Based Super-Resolution Using External and Internal Examples - IEEE Xplore
The external example-driven single image super-resolution (SISR) method that uses a deep convolutional neural network (CNN) has exhibited superior performance as compared to previously developed SISR ...
IEEE4d
Multi-Agent Deep Reinforcement Learning for Computation Offloading and Interference Coordination in Small Cell Networks - IEEE Xplore
Integrating mobile edge computing (MEC) with small cell networks has been conceived as a promising solution to provide pervasive computing services. However, the interactions among small cells due to ...
IEEE5d
A Deep Learning Convolutional Neural Network for Antenna Near-Field Prediction and Surrogate Modeling - IEEE Xplore
This study investigates the use of deep learning techniques for building a generalized surrogate model that can accurately and very efficiently predict antenna performance parameters. Notably, we ...
IEEE5d
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning - IEEE Xplore
Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning ...
IEEE5d
Deep Reinforcement Learning on Autonomous Driving Policy With Auxiliary Critic Network - IEEE Xplore
Deep reinforcement learning (DRL) is a machine learning method based on rewards, which can be extended to solve some complex and realistic decision-making problems. Autonomous driving needs to deal ...
IEEE5d
Learning From Noisy Labels With Deep Neural Networks: A Survey
Deep learning has achieved remarkable success in numerous domains with help from large amounts of big data. However, the quality of data labels is a concern because of the lack of high-quality labels ...
IEEE5d
Classification based DOA estimation using ANN and CNN Models
The Deep Learning Frameworks like ANN and CNN are employed in the area of DOA Estimation has been a recent trend. In this paper we propose Artificial Neural Network(ANN) and Convolutional Neural ...