Modjtaba Rouhani
YOU?
Author Swipe
View article: A context aware multiclass loss function for semantic segmentation with a focus on intricate areas and class imbalances
A context aware multiclass loss function for semantic segmentation with a focus on intricate areas and class imbalances Open
Image segmentation models play an important role in many machine vision systems by providing a more interpretable representation of images to computers. The accuracy of these models is vital, as it can directly impact the overall performan…
View article: Performance Comparison of Different HTM-Spatial Pooler Algorithms Based on Information-Theoretic Measures
Performance Comparison of Different HTM-Spatial Pooler Algorithms Based on Information-Theoretic Measures Open
Hierarchical temporal memory (HTM) is a promising unsupervised machine-learning algorithm that models key principles of neocortical computation. One of the main components of HTM is the spatial pooler (SP), which encodes binary input strea…
View article: Correntropy-Based Constructive One Hidden Layer Neural Network
Correntropy-Based Constructive One Hidden Layer Neural Network Open
One of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises. In this paper, we propose a new incremental constructive network based o…
View article: Information-theoretic analysis of Hierarchical Temporal Memory-Spatial Pooler algorithm with a new upper bound for the standard information bottleneck method
Information-theoretic analysis of Hierarchical Temporal Memory-Spatial Pooler algorithm with a new upper bound for the standard information bottleneck method Open
Hierarchical Temporal Memory (HTM) is an unsupervised algorithm in machine learning. It models several fundamental neocortical computational principles. Spatial Pooler (SP) is one of the main components of the HTM, which continuously encod…
View article: A metaheuristic multi-objective interaction-aware feature selection method
A metaheuristic multi-objective interaction-aware feature selection method Open
Multi-objective feature selection is one of the most significant issues in the field of pattern recognition. It is challenging because it maximizes the classification performance and, at the same time, minimizes the number of selected feat…
View article: Fine-tuned Generative Adversarial Network-based Model for Medical Image Super-Resolution
Fine-tuned Generative Adversarial Network-based Model for Medical Image Super-Resolution Open
In the field of medical image analysis, there is a substantial need for high-resolution (HR) images to improve diagnostic accuracy. However, it is a challenging task to obtain HR medical images, as it requires advanced instruments and sign…
View article: Performance comparison of different HTM-spatial pooler algorithms based on information-theoretic measures
Performance comparison of different HTM-spatial pooler algorithms based on information-theoretic measures Open
This paper provided an information-theoretic framework for the performance comparison of different types of HTM-Spatial Pooler (SP) algorithms for the first time. There are two primary goals. The first goal is to measure SP's performance a…
View article: An Evolutionary Correlation-aware Feature Selection Method for Classification Problems
An Evolutionary Correlation-aware Feature Selection Method for Classification Problems Open
The population-based optimization algorithms have provided promising results in feature selection problems. However, the main challenges are high time complexity. Moreover, the interaction between features is another big challenge in FS pr…
View article: Epileptic Seizures Detection Using Deep Learning Techniques: A Review
Epileptic Seizures Detection Using Deep Learning Techniques: A Review Open
A variety of screening approaches have been proposed to diagnose epileptic seizures, using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities. Artificial intelligence encompasses a variety of areas, and one of its…
View article: A geometric-based data reduction approach for large low dimensional datasets: Delaunay triangulation in SVM algorithms
A geometric-based data reduction approach for large low dimensional datasets: Delaunay triangulation in SVM algorithms Open
Training a support vector machine (SVM) on large datasets is a slow daunting process. Further, SVM becomes slow in the testing phase, due to its large number of support vectors (SVs). This paper proposes an effective geometric algorithm ba…
View article: WSMN: An optimized multipurpose blind watermarking in Shearlet domain using MLP and NSGA-II
WSMN: An optimized multipurpose blind watermarking in Shearlet domain using MLP and NSGA-II Open
View article: A deep neural network classifier for P300 BCI speller based on Cohen’s class time-frequency distribution
A deep neural network classifier for P300 BCI speller based on Cohen’s class time-frequency distribution Open
This paper presents a new method of predicting the P300 component of an electroencephalography (EEG)signal to recognize the characters in a P300 brain-computer interface (BCI) speller accurately. This method consistsof a deep learning mode…
View article: 2020 4th Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)
2020 4th Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Open
View article: Epileptic seizure detection using deep learning techniques: A Review
Epileptic seizure detection using deep learning techniques: A Review Open
A variety of screening approaches have been proposed to diagnose epileptic seizures, using Electroencephalography (EEG) and Magnetic Resonance Imaging (MRI) modalities. Artificial intelligence encompasses a variety of areas, and one of its…
View article: WSMN: An optimized multipurpose blind watermarking in Shearlet domain\n using MLP and NSGA-II
WSMN: An optimized multipurpose blind watermarking in Shearlet domain\n using MLP and NSGA-II Open
Digital watermarking is a remarkable issue in the field of information\nsecurity to avoid the misuse of images in multimedia networks. Although access\nto unauthorized persons can be prevented through cryptography, it cannot be\nsimultaneo…
View article: Fuzzy Sliding Mode Controller for Slip Control of Antilock Brake Systems
Fuzzy Sliding Mode Controller for Slip Control of Antilock Brake Systems Open
Anti-lock braking system is designed to optimize braking procedure while maintaining automobile steerability through controlling wheels slip. However, due to nonlinearity and uncertainty of ABS structure, designing the controller for wheel…
View article: A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm
A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm Open
The support vector machine (SVM) is a powerful tool for classification problems. Unfortunately, the training phase of the SVM is highly sensitive to noises in the training set. Noises are inevitable in real-world applications. To overcome …
View article: Fast and de-noise support vector machine training method based on fuzzy clustering method for large real world datasets
Fast and de-noise support vector machine training method based on fuzzy clustering method for large real world datasets Open
Classifying large and real-world datasets is a challenging problem in machine learning algorithms. Among the machine learning methods, the support vector machine (SVM) is a well-known approach with high generalization ability. Unfortunatel…