Maryam Amirmazlaghani
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View article: A physics-informed deep learning approach for 3D acoustic impedance estimation from seismic data: application to an offshore field in the Southwest Iran
A physics-informed deep learning approach for 3D acoustic impedance estimation from seismic data: application to an offshore field in the Southwest Iran Open
View article: MemLoss: Enhancing Adversarial Training with Recycling Adversarial Examples
MemLoss: Enhancing Adversarial Training with Recycling Adversarial Examples Open
In this paper, we propose a new approach called MemLoss to improve the adversarial training of machine learning models. MemLoss leverages previously generated adversarial examples, referred to as 'Memory Adversarial Examples,' to enhance m…
View article: 3D densely connected CNN with multi-scale receptive fields and hybrid loss for brain tumor segmentation
3D densely connected CNN with multi-scale receptive fields and hybrid loss for brain tumor segmentation Open
Brain tumors, especially gliomas, are among the most common and aggressive types of tumors in the brain. Accurate segmentation of subcortical brain structures is crucial for studying these tumors, monitoring their progression, and evaluati…
View article: Self-Adaptive Revisiting Awareness for Enhancing Robustness and Generalization in Classification Task
Self-Adaptive Revisiting Awareness for Enhancing Robustness and Generalization in Classification Task Open
View article: Beyond Imperfections: A Conditional Inpainting Approach for End-to-End Artifact Removal in VTON and Pose Transfer
Beyond Imperfections: A Conditional Inpainting Approach for End-to-End Artifact Removal in VTON and Pose Transfer Open
Artifacts often degrade the visual quality of virtual try-on (VTON) and pose transfer applications, impacting user experience. This study introduces a novel conditional inpainting technique designed to detect and remove such distortions, i…
View article: Self-Adaptive Revisiting Awareness (Sara) Strategy: a Self-Adaptive Augmentation Technique for Enhancing Adversarial Robustness and Generalization Through Concentrated Focus on Modified Uncertain Samples
Self-Adaptive Revisiting Awareness (Sara) Strategy: a Self-Adaptive Augmentation Technique for Enhancing Adversarial Robustness and Generalization Through Concentrated Focus on Modified Uncertain Samples Open
View article: Self-Adaptive Revisiting Awareness (Sara) for Enhancing Robustness and Generalization in Classification Task
Self-Adaptive Revisiting Awareness (Sara) for Enhancing Robustness and Generalization in Classification Task Open
View article: 3d Densely Connected Cnn with Multi-Scale Receptive Fields and Hybrid Loss for Brain Tumor Segmentation
3d Densely Connected Cnn with Multi-Scale Receptive Fields and Hybrid Loss for Brain Tumor Segmentation Open
View article: Spot The Odd One Out: Regularized Complete Cycle Consistent Anomaly Detector GAN
Spot The Odd One Out: Regularized Complete Cycle Consistent Anomaly Detector GAN Open
This study presents an adversarial method for anomaly detection in real-world applications, leveraging the power of generative adversarial neural networks (GANs) through cycle consistency in reconstruction error. Previous methods suffer fr…
View article: Regularized Complete Cycle Consistent Gan for Anomaly Detection
Regularized Complete Cycle Consistent Gan for Anomaly Detection Open
View article: Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework
Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework Open
Deep neural network models are used today in various applications of artificial intelligence, the strengthening of which, in the face of adversarial attacks is of particular importance. An appropriate solution to adversarial attacks is adv…
View article: Color texture image retrieval based on Copula multivariate modeling in the Shearlet domain
Color texture image retrieval based on Copula multivariate modeling in the Shearlet domain Open
View article: Reconstruction of Gene Regulatory Networks Using Multiple Datasets
Reconstruction of Gene Regulatory Networks Using Multiple Datasets Open
Motivation: Laboratory gene regulatory data for a species are sporadic. Despite the abundance of gene regulatory network algorithms that employ single data sets, few algorithms can combine the vast but disperse sources of data and extract …
View article: Color Texture Image Retrieval Based on Copula Multivariate Modeling in\n the Shearlet Domain
Color Texture Image Retrieval Based on Copula Multivariate Modeling in\n the Shearlet Domain Open
In this paper, a color texture image retrieval framework is proposed based on\nShearlet domain modeling using Copula multivariate model. In the proposed\nframework, Gaussian Copula is used to model the dependencies between different\nsub-b…
View article: A Novel Distributed Approximate Nearest Neighbor Method for Real-time Face Recognition.
A Novel Distributed Approximate Nearest Neighbor Method for Real-time Face Recognition. Open
Nowadays, face recognition and more generally image recognition have many applications in the modern world and are widely used in our daily tasks. This paper aims to propose a distributed approximate nearest neighbor (ANN) method for real-…
View article: A Distributed Approximate Nearest Neighbor Method for Real-Time Face Recognition
A Distributed Approximate Nearest Neighbor Method for Real-Time Face Recognition Open
Nowadays, face recognition and more generally image recognition have many applications in the modern world and are widely used in our daily tasks. This paper aims to propose a distributed approximate nearest neighbor (ANN) method for real-…
View article: Author response for "Using autoregressive-dynamic conditional correlation model with residual analysis to extract dynamic functional connectivity"
Author response for "Using autoregressive-dynamic conditional correlation model with residual analysis to extract dynamic functional connectivity" Open
View article: Heteroscedastic watermark detector in the contourlet domain
Heteroscedastic watermark detector in the contourlet domain Open
A new contourlet domain image watermark detector is proposed in the present study. As the performance of the detector completely depends on the accuracy of the statistical model, the contourlet coefficients and statistical properties are s…
View article: Unsupervised Hypergraph Feature Selection via a Novel Point-Weighting Framework and Low-Rank Representation
Unsupervised Hypergraph Feature Selection via a Novel Point-Weighting Framework and Low-Rank Representation Open
Feature selection methods are widely used in order to solve the 'curse of dimensionality' problem. Many proposed feature selection frameworks, treat all data points equally; neglecting their different representation power and importance. I…
View article: A Novel Contourlet Domain Watermark Detector for Copyright Protection
A Novel Contourlet Domain Watermark Detector for Copyright Protection Open
Digital media can be distributed via Internet easily, so, media owners are eagerly seeking methods to protect their rights. A typical solution is digital watermarking for copyright protection. In this paper, we propose a novel contourlet d…