All Outputs (44)

Early dementia detection with speech analysis and machine learning techniques (2024)
Journal Article
Jahan, Z., Khan, S. B., & Saraee, M. (in press). Early dementia detection with speech analysis and machine learning techniques. #Journal not on list, 5(1), 65. https://doi.org/10.1007/s43621-024-00217-2

This in-depth study journey explores the context of natural language processing and text analysis in dementia detection, revealing their importance in a variety of fields. Beginning with an examination of the widespread and influence of text data. Th... Read More about Early dementia detection with speech analysis and machine learning techniques.

Regularized Contrastive Masked Autoencoder Model for Machinery Anomaly Detection Using Diffusion-Based Data Augmentation (2023)
Journal Article
Zahedi, E., Saraee, M., Masoumi, F. S., & Yazdinejad, M. (in press). Regularized Contrastive Masked Autoencoder Model for Machinery Anomaly Detection Using Diffusion-Based Data Augmentation. #Journal not on list, 16(9), 431. https://doi.org/10.3390/a16090431

Unsupervised anomalous sound detection, especially self-supervised methods, plays a crucial role in differentiating unknown abnormal sounds of machines from normal sounds. Self-supervised learning can be divided into two main categories: Generative a... Read More about Regularized Contrastive Masked Autoencoder Model for Machinery Anomaly Detection Using Diffusion-Based Data Augmentation.

Designing and Implementing a Blockchain-based Platform for the Exchange of Peerto-Peer Energy Trading and Modelling Vehicle-to-Grid(V2G) Residential Community (2023)
Journal Article
Debrah, P., & Saraee, M. (2023). Designing and Implementing a Blockchain-based Platform for the Exchange of Peerto-Peer Energy Trading and Modelling Vehicle-to-Grid(V2G) Residential Community. #Journal not on list, 6(1), 68

The expansion of renewable energy on the national grid has been a struggle throughout the past decade. Rooftop solar photovoltaics (PV) and electric vehicle to Grid (V2G) can function as either load or distributed energy sources. Consequently, presum... Read More about Designing and Implementing a Blockchain-based Platform for the Exchange of Peerto-Peer Energy Trading and Modelling Vehicle-to-Grid(V2G) Residential Community.

Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips (2023)
Journal Article
Anih, J., Kolekar, S., Dargahi, T., Babaie, M., Saraee, M., & Wetherell, J. (2023). Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips. IEEE Access, 11, 38385-38398. https://doi.org/10.1109/access.2023.3261245

The commercial adoption of Autonomous Vehicles (AVs) and the positive impact they are expected to have on traffic safety depends on appropriate insurance products due to the high potential losses. A significant proportion of these losses are expected... Read More about Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips.

DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy (2022)
Journal Article
Adeboye, O., Dargahi, T., Babaie, M., Saraee, M., & Yu, C. (2022). DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy. IEEE Access, https://doi.org/10.1109/ACCESS.2022.3222834

Autonomous Vehicles (AVs) are equipped with several sensors which produce various forms of data, such as geo-location, distance, and camera data. The volume and utility of these data, especially camera data, have contributed to the advancement of h... Read More about DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy.

Features in extractive supervised single-document summarization : case of Persian news (2019)
Journal Article
Rezaei, H., Moeinzadeh, S., Shahgholian, A., & Saraee, M. (2019). Features in extractive supervised single-document summarization : case of Persian news

Text summarization has been one of the most challenging areas of research in NLP. Much effort has been made to overcome this challenge by using either the abstractive or extractive methods. Extractive methods are more popular, due to their simplicity... Read More about Features in extractive supervised single-document summarization : case of Persian news.

Analyzing data streams using a dynamic compact stream pattern algorithm (2019)
Journal Article
Oyewale, A., Hughes, C., & Saraee, M. (2019). Analyzing data streams using a dynamic compact stream pattern algorithm

A growing number of applications that generate massive streams of data need intelligent data processing and online analysis. Data & Knowledge Engineering (DKE) has been known to stimulate the exchange of ideas and interaction between these two rela... Read More about Analyzing data streams using a dynamic compact stream pattern algorithm.

Geometrical-based approach for robust human image detection (2018)
Journal Article
Al-Hazaimeh, O., Al-Nawashi, M., & Saraee, M. (2019). Geometrical-based approach for robust human image detection. Multimedia Tools and Applications, 78(6), 7029-7053. https://doi.org/10.1007/s11042-018-6401-y

In recent years, object detection and classification has been gaining more attention, thus, there are several human object detection algorithms being used to locate and recognize human objects in images. The research of image processing and analyzing... Read More about Geometrical-based approach for robust human image detection.

Finding influential users for different time bounds in social networks using multi-objective optimization (2018)
Journal Article
Mohammadi, A., & Saraee, M. (2018). Finding influential users for different time bounds in social networks using multi-objective optimization. Swarm and Evolutionary Computation, 40, 158-165. https://doi.org/10.1016/j.swevo.2018.02.003

Online social networks play an important role in marketing services. Influence maximization is a major challenge, in which the goal is to find the most influential users in a social network. Increasing the number of influenced users at the end of a d... Read More about Finding influential users for different time bounds in social networks using multi-objective optimization.

SSAM : towards supervised sentiment and aspect modeling on different levels of labeling (2017)
Journal Article
Zahedi, E., & Saraee, M. (2018). SSAM : towards supervised sentiment and aspect modeling on different levels of labeling. Soft Computing, 22(23), 7989-8000. https://doi.org/10.1007/s00500-017-2746-9

Abstract In recent years people want to express their opinion on every online service or product, and there are now a huge number of opinions on the social media, online stores and blogs. However, most of the opinions are presented in plain text and... Read More about SSAM : towards supervised sentiment and aspect modeling on different levels of labeling.

Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine (2016)
Journal Article
Rashno, A., Nazari, B., Sadri, S., & Saraee, M. (2017). Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine. Neurocomputing, 226, 66-79. https://doi.org/10.1016/j.neucom.2016.11.030

one of the most important tasks of Mars rover, a robot which explores the Mars surface, is the process of automatic segmentation of images taken by front-line Panoramic Camera (Pancam). This procedure is highly significant since the transformation co... Read More about Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments (2016)
Journal Article
Al-Nawashi, M., Al-Hazaimeh, O., & Saraee, M. (2016). A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments. Neural Computing and Applications, 27(4), https://doi.org/10.1007/s00521-016-2363-z

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system thatcan perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic re... Read More about A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification (2016)
Journal Article
Sartakhti, J., Afrabandpey, H., & Saraee, M. (2017). Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification. Soft Computing, 21(15), 4361-4373. https://doi.org/10.1007/s00500-016-2067-4

Least squares twin support vector machine (LSTSVM) is a relatively new version of support vector machine (SVM) based on non-parallel twin hyperplanes. Although, LSTSVM is an extremely efficient and fast algorithm for binary classification, its p... Read More about Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification.

Time-sensitive influence maximization in social networks (2015)
Journal Article
Mohammadi, A., Saraee, M., & Mirzaei, A. (2015). Time-sensitive influence maximization in social networks. Journal of Information Science, 41(6), 765-778. https://doi.org/10.1177/0165551515602808

One of the fundamental issues in social networks is the influence maximization problem, where the goal is to identify a small subset of individuals such that they can trigger the largest number of members in the network. In real-world social networks... Read More about Time-sensitive influence maximization in social networks.

PSA : a hybrid feature selection approach for Persian text classification (2015)
Journal Article
Bagheri, A., Saraee, M., & Nadi, S. (2015). PSA : a hybrid feature selection approach for Persian text classification. Journal of computing and security (Online), 1(4), 261-272

In recent decades, as enormous amount of data being accumulated, the number of text documents is increasing vastly. E-mails, web pages, texts, news and articles are only part of this grow. Thus the need for text mining techniques, including automatic... Read More about PSA : a hybrid feature selection approach for Persian text classification.

A novel feature selection method for text classification using association rules and clustering (2014)
Journal Article
Sheydaei, N., Saraee, M., & Shahgholian, A. (2015). A novel feature selection method for text classification using association rules and clustering. Journal of Information Science, 41(1), 3-15. https://doi.org/10.1177/0165551514550143

Readability and accuracy are two important features of a good classifier. For reasons such as acceptable accuracy, rapid training and high interpretability, associative classifiers have been recently used in many categorization tasks. These features... Read More about A novel feature selection method for text classification using association rules and clustering.

Persian sentiment analyzer : a framework based on a novel feature selection method (2014)
Journal Article
feature selection method. International Journal of Artificial Intelligence, 12(2), 115-129

In the recent decade, with the enormous growth of digital content in internet and databases, sentiment analysis has received more and more attention between information retrieval and natural language processing researchers. Sentiment analysis aims... Read More about Persian sentiment analyzer : a framework based on a novel feature selection method.

MRAR : mining multi-relation association rules (2014)
Journal Article
Ramezani, R., Saraee, M., & Nematbakhsh, M. (2014). MRAR : mining multi-relation association rules. Journal of computing and security (Online), 1(2), 133-158

In this paper, we introduce a new class of association rules (ARs) named “Multi-Relation Association Rules” which in contrast to primitive ARs (that are usually extracted from multi-relational databases), each rule item consists of one entity and... Read More about MRAR : mining multi-relation association rules.

A fuzzy method for discovering cost-effective actions from data (2014)
Journal Article
Kalanat, N., Shamsinejadbabaki, P., & Saraee, M. (2014). A fuzzy method for discovering cost-effective actions from data. Journal of Intelligent and Fuzzy Systems, 28(2), 757-765. https://doi.org/10.3233/IFS-141357

Data mining techniques are often confined to the delivery of frequent patterns and stop short of suggesting how to act on these patterns for business decision-making. They require human experts to post-process the discovered patterns manually. Theref... Read More about A fuzzy method for discovering cost-effective actions from data.

ADM-LDA : an aspect detection model based on topic modelling using the structure of review sentences (2014)
Journal Article
Bagheri, A., Saraee, M., & de Jong, F. (2014). ADM-LDA : an aspect detection model based on topic modelling using the structure of review sentences. Journal of Information Science, 40(5), 621-636. https://doi.org/10.1177/0165551514538744

Probabilistic topic models are statistical methods whose aim is to discover the latent structure in a large collection of documents. The intuition behind topic models is that, by generating documents by latent topics, the word distribution for each t... Read More about ADM-LDA : an aspect detection model based on topic modelling using the structure of review sentences.