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IEEE6h
Dynamic Semantic Compression for CNN Inference in Multi-Access Edge Computing: A Graph Reinforcement Learning-Based Autoencoder - IEEE Xplore
This paper studies the computational offloading of CNN inference in dynamic multi-access edge computing (MEC) networks. To address the uncertainties in communication time and edge servers’ available ...
IEEE17h
Physical Layer-Aware Route and Spectrum Allocation in Optical Networks by Multi-Objective Deep Reinforcement Learning - IEEE Xplore
We propose a multi-objective Reinforcement Learning approach for RSA in optical networks, integrating awareness of signal quality, delay, and load-balancing. It outperforms traditional algorithms with ...
IEEE2d
A Two-Layer Ensemble Deep Learning Model for Acoustic Seabed Sediment Classification - IEEE Xplore
Seabed sediment information is widely utilized in marine exploration and management. Recent breakthroughs of sonar technology and data processing method have spurred the development of automated ...
IEEE3d
Multi-Layer FSS Prediction Based on Machine Learning
This paper presents a machine learning-based method for predicting the electromagnetic properties of multilayer structures. The complexity introduced by the coupling of these layers is addressed ...
IEEE6d
Deep Learning-Based Classification of Areca Nut Yellow Leaf Disease with ResNet-50 CNN - IEEE Xplore
Detecting healthy arecanut leaves, yellow leaf disease in arecanut, and differentiating these from other types of leaves using deep learning involves designing an advanced neural network model for ...
IEEE11d
Human Activity Recognition via Wi-Fi CSI and VAE-CNN-BiLSTM Hybrid Deep Learning - IEEE Xplore
Human Activity Recognition (HAR) is vital across multiple applications, such as healthcare monitoring, smart home systems, and surveillance. Recently, Wi-Fi channel state information (CSI) has gained ...
IEEE12d
MorphBungee: A 65-nm 7.2-mm2 27-µJ/Image Digital Edge Neuromorphic Chip With on-Chip 802-Frame/s Multi-Layer Spiking Neural Network Learning | IEEE Journals & Magazine | IEEE ...
This paper presents a digital edge neuromorphic spiking neural network (SNN) processor chip for a variety of edge intelligent cognitive applications. This processor allows high-speed, high-accuracy ...
IEEE15d
Deep Learning-Driven Early Detection of Alzheimer’s Disease using CNN - IEEE Xplore
Researchers evaluate Convolutional Neural Networks as tools for early identification and staging of Alzheimer's disease (AD) using MRI data collected from the Open Access Series of Imaging Studies ...
IEEE17d
A CNN-Based End-to-End Learning Framework Toward Intelligent Communication Systems - IEEE Xplore
Deep learning has been applied in physical-layer communications systems in recent years and has demonstrated fascinating results that were comparable or even better than human expert systems. In this ...
IEEE18d
AI-Powered Defect Detection using Deep Learning: A Pattern-Agnostic Faster R-CNN Approach for SEM Images with GPU Acceleration - IEEE Xplore
Semiconductor manufacturing requires highly precise defect detection to ensure product quality and yield. This paper presents a deep learning-based defect detection framework using Faster R-CNN to ...
IEEE19d
3D-CNN and Autoencoder-Based Gas Detection in Hyperspectral Images - IEEE Xplore
The detection of gas emission levels is a crucial problem for ecology and human health. Hyperspectral image analysis offers many advantages over traditional gas detection systems with its detection ...