Irene Yu-Hua Gu
Irene Gu är professor i Institutioner för Elektroteknik. Hon har fått doktorsexamen från Eindhoven University of Technology, Nederländerna 1992. Från 1992 till 1994 var hon forskare vid Philips Research Institute IPO, Nederländerna och postdoc vid Staffordshire University, Storbritannien. Hon var universitetslektor vid University of Birmingham, Storbritannien, 1995-1996 innan han började på Chalmers. Från September 1996 har hon varit vid Institutionen för Signaler och System (nuvarande namn: Institutionen för elektroteknik), Chalmers tekniska högskola, och blir professor sedan 2004. Hon har publicerat över 200 tidskrifts- och konferensartiklar, och har medförfattat en bok om "signal processing of power quality disturbances".
Irene Gus huvudsakliga forskning inkluderar statistisk bildanalys och video behandling, maskininlärning och djupinlärning, visuell objektspårning och klassificering, signalanalys och signalbehandling med applikationer till elkraftsystem, och biomedicinsk bildanalys för AI-assisterad hjärnsjukdomsdiagnos.
Hennes nuvarande huvudsakliga forskningsaktiviteter inkluderar: biomedicinsk bildanalys för diagnos av hjärntumörer och Alzheimers sjukdom; "privacy"-kyddad maskininlärning för fordon / trafiksäkerhet och transportsystem; signalbehandling och maskininlärning med applikationer till stor dataanalys i kraftsystem (hitta underliggande orsaker och mönster från störnings- och variationsmätdata).
Visar 229 publikationer
Hierarchical LSTM-Based Classification of Household Heating Types Using Measurement Data
A novel federated deep learning scheme for glioma and its subtype classification
Support vector machine for classification of households' heating type using load curves
Introduction to Deep Learning in Clinical Neuroscience
A Feasibility Study on Deep Learning Based Brain Tumor Segmentation Using 2D Ellipse Box Areas
A Framework Based on Machine Learning for Analytics of Voltage Quality Disturbances
VISUALIZING THE RESULTS FROM UNSUPERVISED DEEP LEARNING FOR THE ANALYSIS OF POWER-QUALITY DATA
Deep Feature Clustering for Seeking Patterns in Daily Harmonic Variations
Deep semi-supervised learning for brain tumor classification
Improved Peak Load Estimation from Single and Multiple Consumer Categories
Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification
Artificial intelligence and ambient intelligence
Deepside: A general deep framework for salient object detection
Refinet: A Deep Segmentation Assisted Refinement Network for Salient Object Detection
Human Fall Detection using Co-Saliency-Enhanced Deep Recurrent Convolutional Neural Networks
Generative Adversarial Model-Guided Deep Active Learning for Voltage Dip Labelling
Spectral salient object detection
An efficient 3D deep convolutional network for Alzheimer's disease diagnosis using MR images
A Robust Transform-Domain Deep Convolutional Network for Voltage Dip Classification
Improved characterization of Multi-Stage Voltage Dips based on the Space Phasor Model
3D Multi-Scale Convolutional Networks for Glioma Grading Using MR Images
Co-Saliency-Enhanced Deep Recurrent Convolutional Networks for Human Fall Detection in E-Healthcare
A LSTM-based Deep Learning Method with Application to Voltage Dip Classification
Human fall detection using segment-level CNN features and sparse dictionary learning
Visual information-based activity recognition and fall detection for assisted living and ehealthcare
Saliency Detection by Fully Learning A Continuous Conditional Random Field
On waveform distortion in the frequency range of 2 kHz–150 kHz—Review and research challenges
Optimal Gradient Encoding Schemes for Diffusion Tensor and Kurtosis Imaging
A Novel Framework for repeated measurements in diffusion tensor imaging
Learning full-range affinity for diffusion-based saliency detection
Robust visual tracking via inverse nonnegative matrix factorization
Fall detection in RGB-D videos by combining shape and motion features
Causal and Anti-Causal Segmentation of Voltage Dips in Power Distribution Networks
Exploiting Riemannian Manifolds for Daily Activity Classification in Video Towards Health Care
Robust manifold-preserving diffusion-based saliency detection by adaptive weight construction
Geodesic Distance Transform-based Salient Region Segmentation for Automatic Traffic Sign Recognition
SALIENT OBJECT DETECTION USING NORMALIZED CUT AND GEODESICS
Fall Detection in RGB-D Videos for Elderly Care
Novel segmentation technique for measured three-phase voltage dips
K-Optimal Gradient Encoding Scheme for Fourth-Order Tensor-Based Diffusion Profile Imaging
Normalized Cut-based Saliency Detection by Adaptive Multi-Level Region Merging
Human Fall Detection via Shape Analysis on Riemannian Manifolds with Applications to Elderly Care
Visual Tracking via Nonnegative Regularization Multiple Locality Coding
Icosahedral gradient encoding scheme for an arbitrary number of measurements
Traffic Sign Recognition using Salient Region Features: A Novel Learning-based Coarse-to-Fine Scheme
Video-based Tracking and Quantified Assessment of Spontaneous Limb Movements in Neonates
Tests and analysis of a novel segmentation method using measurement data
Fourth order tensor-based diffusion MRI signal modeling
Detection and Recognition of Traffic Signs from Videos using Saliency-Enhanced Features
Human Activity Recognition in Images Using SVMs and Geodesics on Smooth Manifolds
Effective Small Dim Target Detection by Local Connectedness Constraint
Graph Construction for Salient Object Detection in Videos
Head Pose Classification by Multi-Class AdaBoost with Fusion of RGB and Depth Images
Video-Based Detection and Analysis of Driver Distraction and Inattention
Spectral salient object detection
Domain-Shift Tracking: Online Learning and Visual Object Tracking on Smooth Manifolds
Practical Applications of Automatic Image Analysis of Overhead Power Lines
Pedestrian Detection using Augmented Training Data
Adaptive Multi-Level Region Merging for Salient Object Detection
Riemannian Manifold-Based Support Vector Machine for Human Activity Classification in Images
On High Order Tensor-based Diffusivity Profile Estimation
Domain-Shift Manifold Online Learning and Tracking of Video Objects
Geodesic Saliency Propagation for Image Salient Region Detection
Super-resolution reconstruction of high dynamic range images in a perceptually uniform domain
Superpixel based Color Contrast and Color Distribution Driven Salient Object Detection
Optimal Diffusion Tensor Imaging with Repeated Measurements
Superpixel based color contrast and color distribution driven salient object detection
Practical applications of automatic image analysis for overhead lines
weighted least squares estimation of 4th order diffusion tensors
A Novel framework for high order tensor-based diffusivity profile estimation
An Enhanced Segmentation Method by Combining Super Resolution and Level Set
Super-resolution reconstruction of high dynamic range images with perceptual weighting of errors
One-class support vector machine-assisted robust tracking
A new joint sliding-window ESPRIT and DFT scheme for waveform distortion assessment in power systems
One-Class SVM Assisted Accurate Tracking
Adaptive appearance learning for visual object tracking
Chapter 10 (in Part 2): Detecting Landmine Fields from Low-Resolution Aerial Infrared Images
Robust Visual Object Tracking using Multi-Mode Anisotropic Mean Shift and Particle Filters
A Method to Evaluate Harmonic Model-Based Estimations under Non-White Measured Noise
Joint Feature Correspondences and Appearance Similarity for Robust Visual Object Tracking
Visual tracking for video surveillance and vehicle safety
Analysis of Power Disturbances from Monitoring Multiple Levels and Locations in a Power System
Joint Causal and Anti-Causal Segmentation and Location of Transitions in Power Disturbances
Wood Defect Classification based on Image Analysis and Support Vector Machine
Trends, Challenges and Opportunities in Power Quality Research
Feature Characterization of Power Quality Events According to Their Underlying Causes
Robust Object Tracking using Particle Filters and Multi-Region Mean Shift
Joint random sample consensus and multiple motion models for robust video tracking
Enhanced Landmine Detection From Low Resolution IR Image Sequences
Estimating Interharmonics by Using Sliding-Window ESPRIT
Automatic Classification of Wood Defects using Support Vector Machines
Face Tracking Using Rao-Blackwellized Particle Filter and Pose-Dependent Probabilistic PCA
Edge-Preserving Segmentation and Fusion of Medical Images by using Enhanced Mean Shift
Online subspace learning in Grassmann manifold for moving object tracking in video
Tracking moving objects in video using enhanced mean shift and region-based motion field
Laboratory Tests and Web Based Surveillance to Determine the Ice- and Snow Performance of Insulators
ML Nonlinear Smoothing for Image Segmentation and Its Relationship to The Mean Shift
On the Analysis of Voltage and Current Transients in Three-Phase Power Systems
Support Vector Machine for Classification of Voltage Disturbances
Trace of flicker sources by using the quantity of flicker power
Emerging signal processing techniques for power quality applications
AUTOMATIC CLASSIFICATION OF VOLTAGE EVENTS USING THE SUPPORT VECTOR MACHINE METHOD
Object Tracking using Incremental 2D-PCA Learning and ML Eestimation
Region-based Statistical Background Modeling for Foreground Object Segmentation
Performance Tests of a Support Vector Machine used for Classification of Voltage Disturbances
Bayesian traffic dynamics and packet loss prediction for video over IP networks
Analysis and Classification of Power Quality Disturbances: Ideas, Methods and Technquies
3D Face Recognition Using Affine Integral Invariants
Signal Processing of Power Quality Disturbances
PCR-Based Multi-Object Tracking for Video Surveillance
Video Segmentation using Joint Space-Time-Range Adaptive Mean Shift
An Eigenbackground Subtraction Method using Recursive Error Compensation
Joint Space-Time-Range Mean Shift-based Image and Video Segmentation (Chapter 6)
Music signal synthesis using sinusoid models and sliding-window ESPRIT
Categorization and Analysis of Power System Transients
New-adaptive frame-expansion-based packet video coding for erasure channels
Error-resilient packet video coding using harmonic frame-expansions and temporal prediction
Characterization of Voltage Variations in the Very-Short Time-Scale
Statistical-Based Sequential Method for Fast Online Detection of Fault-Induced Voltage Dips
A Bayesian framework-based end-to-end packet loss prediction in IP networks
Advanced signal processing techniques for power quality variations and events
Statistical Modeling of Complex Background for Foreground Object Detection
Adaptive Background Subtraction based on Feedback from Fuzzy Classification
Further classification of voltage dips and interruptions
Positive and negative sequence estimation for unbalanced voltage dips
Event-based transient categorization and analysis in electric power systems
Classification of Bird Species by Using Key Song Searching: A Comparative Study
Hue Feature-Based Stereo Scheme for Detecting Half-occlusion and order-reversal of objects
Bridge the gap: signal processing for power quality applications
Landmine field detection using joint temporal and spatial-scale detectors
Global optimisation of video quality by improved rate control on IP-networks
Principal Color Representation for Tracking Persons
foreground object detection from videos containing complex background
Multiresolution Feature Extraction using a Family of Isotropic Bandpass Filters
Detecting and Location Land Mine Fields from Vehicle - and Air-Borne Measured Images
Robust Change Detection and Segmentation for Background Maintenance
Expert System for Classification and Analysis of Power System Events
Foreground Object Detection in Changing Background based on Color Co-Occurrence Statistics
Automatic Analysis of Power Quality Mearurements
Automatic Classification of Power System Events using Rms Voltage Measurements
Color Image Segmentation using Adaptive mean Shift Filters
Voltage Dip Detection and Power System Transients
Expert system for Voltage Dip Classification and Analysis
Infrared Detection of Buried Land Mines Based on Texture Modeling
Nonlinear smoothing filter using adaptive radial clustering
Detection of Landmine Candidates from Airborne and Vehicle-borne IR Images
A 3-D Matched Filter for Detection of Landmines using Spatio-Temporal Thermal Modeling
The Use of Time-Varying AR Models for the Characterization of Voltage Disturbances
Analyzing power disturbances using the residuals of AR models
Nonlinear Image Enhancement by Randomized Local Clustering
Transformer saturation after a voltage dip
Coarse-to-fine Planar Object Identification using Invariant Curve Features and B-spline Modeling
Classification of power system events: Voltage dips
Time-Frequency and Time-scale Domain Analysis of Voltage Disturbances
Classification of Power System Transients: Synchronized Switching
Analysis of Voltage Dips for Event Identification
A Fault Location Technique using High Frequency Fault Clearing Transients
Aspects of an Airborne System for Detection of Landmines using Multispectral Imaging
Corner-Based Curve Feature Extraction for Object Retrieval
Object Tracking and Motion Estimation from Image Sequence Using B-Spline
Object Recognition and Motion Estimation via Joint Segmentation and B-spline Contour Modeling
A New Adaptive Median Filtering Algorithm for Image Enhancement
A New Multiband Volterra Filtering Algorithm and Its Applications to Communication Systems
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Visar 6 forskningsprojekt
Privacy-Protected Machine Learning for Transport Systems
Artificial Intelligence Meets Effective Electricity: Deep Learning for Power Systems Analytics
Machine-learning algorithms to categorize consumers
Deep learning for AI-Assisted Brain Tumor Diagnosis
Tillämpning av "deep learning" metoder på stora datamängder i elkraftsystem