IEEE

Fully Convolutional Change Detection Framework With Generative Adversarial Network for Unsupervised, Weakly Supervised and Regional Supervised Change Detection

Abstract: Deep learning for change detection is one of the current hot topics in the field of remote sensing. However, most end-to-end networks are proposed for supervised change detection, and ...
IEEE

Understanding and Learning Discriminant Features based on Multiattention 1DCNN for Wheelset Bearing Fault Diagnosis

Abstract: Recently, deep-learning-based fault diagnosis methods have been widely studied for rolling bearings. However, these neural networks are lack of interpretability for fault diagnosis tasks.
IEEE

Event-Triggered Model-Free Adaptive Control for Nonlinear Multiagent Systems Under Jamming Attacks

Abstract: This article addresses the security problem of tracking control for nonlinear multiagent systems against jamming attacks. It is assumed that the communication networks among agents are ...
IEEE

Dual-Band Aperture Shared Antenna Array With Decreased Radiation Pattern Distortion

Abstract: In this communication, a dual-band aperture-shared antenna array (ASAA) is developed for base station. This ASAA contains a 4 $\times $ 4 high-band (HB) antenna array, which operates from ...
IEEE

Operation and Control of a DC-Grid Offshore Wind Farm Under DC Transmission System Faults

Abstract: So far, all existing offshore wind farms have an ac collection system, and the collected power in the offshore wind farm is sent to an onshore ac grid through high-voltage ac (HVAC) or DC ...
IEEE

Expressiveness Analysis and Enhancing Framework for Geometric Knowledge Graph Embedding Models

Abstract: Existing geometric knowledge graph embedding methods employ various relational transformations, such as translation, rotation, and projection, to model different relation patterns, which ...
IEEE

Breast Cancer Classification Using Deep Learning Approaches and Histopathology Image: A Comparison Study

Abstract: Convolutional Neural Network (CNN) models are a type of deep learning architecture introduced to achieve the correct classification of breast cancer. This paper has a two-fold purpose. The ...
IEEE

A mathematical theory of communication

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6731005 ...
IEEE

A New Theory of Broad-band Matching

Abstract: This paper solves the problem of designing an optimum, passive, reactive two-port equalizer to match out a dissipative frequency sensitive load to a resistive generator. The method is simple ...
IEEE

Auto-AD: Autonomous Hyperspectral Anomaly Detection Network Based on Fully Convolutional Autoencoder

Abstract: Hyperspectral anomaly detection is aimed at detecting observations that differ from their surroundings, and is an active area of research in hyperspectral image processing. Recently, ...
IEEE

Remote Photoplethysmography for Heart Rate and Blood Oxygenation Measurement: A Review

Abstract: Usually measured through obtrusive contact-based methods, heart rate (HR) and peripheral oxygen saturation (SpO2) are critical physiological signs used by clinicians during emergency ...
IEEE

A mathematical theory of communication

Abstract: In this final installment of the paper we consider the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now. To a ...