research
∙
02/03/2023
Cluster-CAM: Cluster-Weighted Visual Interpretation of CNNs' Decision in Image Classification
Despite the tremendous success of convolutional neural networks (CNNs) i...
share
research
∙
01/12/2023
Fair and skill-diverse student group formation via constrained k-way graph partitioning
Forming the right combination of students in a group promises to enable ...
research
∙
10/16/2022
Demystifying CNNs for Images by Matched Filters
The success of convolution neural networks (CNN) has been revolutionisin...
research
∙
09/15/2022
VS-CAM: Vertex Semantic Class Activation Mapping to Interpret Vision Graph Neural Network
Graph convolutional neural network (GCN) has drawn increasing attention ...
research
∙
05/26/2022
Analytical Interpretation of Latent Codes in InfoGAN with SAR Images
Generative Adversarial Networks (GANs) can synthesize abundant photo-rea...
research
∙
08/26/2021
Convolutional Neural Networks Demystified: A Matched Filtering Perspective Based Tutorial
Deep Neural Networks (DNN) and especially Convolutional Neural Networks ...
research
∙
08/23/2021
Understanding the Basis of Graph Convolutional Neural Networks via an Intuitive Matched Filtering Approach
Graph Convolutional Neural Networks (GCNN) are becoming a preferred mode...
research
∙
05/27/2021
On the Sparsity Bound for the Existence of a Unique Solution in Compressive Sensing by the Gershgorin Theorem
Since compressive sensing deals with a signal reconstruction using a red...
research
∙
03/11/2021
Improved Coherence Index-Based Bound in Compressive Sensing
Within the Compressive Sensing (CS) paradigm, sparse signals can be reco...
research
∙
07/27/2020
A Probabilistic Spectral Analysis of Multivariate Real-Valued Nonstationary Signals
A class of multivariate spectral representations for real-valued nonstat...
research
∙
05/16/2020
The Support Uncertainty Principle and the Graph Rihaczek Distribution: Revisited and Improved
The classical support uncertainty principle states that the signal and i...
research
∙
03/27/2020
RANSAC-Based Signal Denoising Using Compressive Sensing
In this paper, we present an approach to the reconstruction of signals e...
research
∙
01/02/2020
Graph Signal Processing – Part III: Machine Learning on Graphs, from Graph Topology to Applications
Many modern data analytics applications on graphs operate on domains whe...
research
∙
10/12/2019
Portfolio Cuts: A Graph-Theoretic Framework to Diversification
Investment returns naturally reside on irregular domains, however, stand...
research
∙
09/23/2019
Graph Signal Processing – Part II: Processing and Analyzing Signals on Graphs
The focus of Part I of this monograph has been on both the fundamental p...
research
∙
09/12/2019
Unitary Shift Operators on a Graph
A unitary shift operator (GSO) for signals on a graph is introduced, whi...
research
∙
08/05/2019
A Unifying Analysis of Shift Operators on a Graph
The maximum entropy principle is employed to introduce a general class o...
research
∙
07/08/2019
Vertex-Frequency Graph Signal Processing
Graph signal processing deals with signals which are observed on an irre...
research
∙
07/08/2019
Graph Signal Processing -- Part I: Graphs, Graph Spectra, and Spectral Clustering
The area of Data Analytics on graphs promises a paradigm shift as we app...
research
∙
07/01/2019
Quantization in Compressive Sensing: A Signal Processing Approach
Influence of the finite-length registers and quantization effects on the...
research
∙
03/31/2019
On the Decomposition of Multivariate Nonstationary Multicomponent Signals
With their ability to handle an increased amount of information, multiva...
research
∙
03/26/2019
