Jafar Tanha
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View article: DSN-STC: Leveraging Siamese networks for optimized short text clustering
DSN-STC: Leveraging Siamese networks for optimized short text clustering Open
In this paper, we present a novel deep Siamese network with a multi-scale hybrid feature extraction architecture, named DSN-STC (Deep Siamese Network for Short Text Clustering), that significantly improves the clustering of short text. A k…
View article: Uncertainty-weighted semi-supervised learning with dynamic entropy masking and Bhattacharyya-regularized loss
Uncertainty-weighted semi-supervised learning with dynamic entropy masking and Bhattacharyya-regularized loss Open
Semi-supervised learning (SSL) leverages labeled and unlabeled data for modern classification tasks. However, existing SSL approaches often underutilize moderately uncertain samples and may propagate errors from highly uncertain pseudo-lab…
View article: YM-WML: A new Yolo-based segmentation Model with Weighted Multi-class Loss for medical imaging
YM-WML: A new Yolo-based segmentation Model with Weighted Multi-class Loss for medical imaging Open
Medical image segmentation poses significant challenges due to class imbalance and the complex structure of medical images. To address these challenges, this study proposes YM-WML, a novel model for cardiac image segmentation. The model in…
View article: Corrections to “A Semi-Supervised Learning Approach to Quality-Based Web Service Classification”
Corrections to “A Semi-Supervised Learning Approach to Quality-Based Web Service Classification” Open
Presents corrections to the paper, (Corrections to “A Semi-Supervised Learning Approach to Quality-Based Web Service Classification”).
View article: A Novel Multimodal Deep Learning Approach With Loss Function for Detection of Sleep Apnea Events
A Novel Multimodal Deep Learning Approach With Loss Function for Detection of Sleep Apnea Events Open
Sleep apnea, a common and potentially serious sleep disorder, is characterized by repeated pauses in breathing during sleep. These pauses, known as apneas, can last from a few seconds to minutes and may occur multiple times per hour. This …
View article: Lung Cancer classification using an ensemble of CNNs Method in CT Scan Images
Lung Cancer classification using an ensemble of CNNs Method in CT Scan Images Open
About five million people lose their lives every year to lung cancer, making it one of the leading causes of mortality worldwide. In the last few years, a lot of methods of detection of lung cancer were improved however these could not eff…
View article: Modeling Chandy–Lamport Distributed Snapshot Algorithm Using Colored Petri Net
Modeling Chandy–Lamport Distributed Snapshot Algorithm Using Colored Petri Net Open
Distributed global snapshot (DGS) is one of the fundamental protocols in distributed systems. It is used for different applications like collecting information from a distributed system and taking checkpoints for process rollback. The Chan…
View article: A Semi-Supervised Learning Approach to Quality-Based Web Service Classification
A Semi-Supervised Learning Approach to Quality-Based Web Service Classification Open
The Internet provides a platform for sharing services, and web service brokers help users to choose the suitable service among similar services based on ranking. The quality of service is important in evaluating the services the user needs…
View article: An Attention-Based Convolutional Recurrent Neural Networks for Scene Text Recognition
An Attention-Based Convolutional Recurrent Neural Networks for Scene Text Recognition Open
Text recognition is critical in various domains, including driving assistance, handwriting recognition, and aiding the visually impaired. In recent years, deep learning-based methods have demonstrated outstanding performance in Scene Text …
View article: IMBoost: A New Weighting Factor for Boosting to Improve the Classification Performance of Imbalanced Data
IMBoost: A New Weighting Factor for Boosting to Improve the Classification Performance of Imbalanced Data Open
Imbalanced datasets pose significant challenges in the field of machine learning, as they consist of samples where one class (majority) dominates over the other class (minority). Although AdaBoost is a popular ensemble method known for its…
View article: An experimental review of the ensemble-based data stream classification algorithms in non-stationary environments
An experimental review of the ensemble-based data stream classification algorithms in non-stationary environments Open
Data streams are sequences of fast-growing and high-speed data points that typically suffer from the infinite length, large volume, and specifically unstable data distribution. These potential issues of data streams bold the necessity of d…
View article: A semi-supervised clustering approach using labeled data
A semi-supervised clustering approach using labeled data Open
Over recent decades, there has been a growing interest in semi-supervised clustering. Compared to the supervised or unsupervised clustering methods for solving different real-life problems, reviewed articles show that semi-supervised clust…
View article: Boosting methods for multi-class imbalanced data classification: an experimental review
Boosting methods for multi-class imbalanced data classification: an experimental review Open
Since canonical machine learning algorithms assume that the dataset has equal number of samples in each class, binary classification became a very challenging task to discriminate the minority class samples efficiently in imbalanced datase…
View article: COVID-19 Infection Forecasting based on Deep Learning in Iran
COVID-19 Infection Forecasting based on Deep Learning in Iran Open
Since December 2019 coronavirus disease (COVID-19) is outbreak from China and infected more than 4,666,000 people and caused thousands of deaths. Unfortunately, the infection numbers and deaths are still increasing rapidly which has put th…
View article: Relationship among prognostic indices of breast cancer using classification techniques
Relationship among prognostic indices of breast cancer using classification techniques Open
The main focus of this article is to identify relationships among prognostic indices for different breast cancer groups, using classification algorithms in the field of data mining. Typically, data mining algorithms are used to discover th…