Seyed Mehdi Hazrati Fard

University of Waterloo | UWaterloo · Department of Statistics and Actuarial Science

Tourists share opinions about Points of Interest (POIs) through online posts and social media platforms. Opinion mining is a popular technique for extracting feedback from tourists who visited various places hidden in reviews, which are used in several tourist applications that generally reflect their preference towards POI. On the other hand, a tr...

Over the decades, Artificial Intelligence (AI) and machine learning has become a transformative solution in many sectors, services, and technology platforms in a wide range of applications, such as in smart healthcare, financial, political, and surveillance systems. In such applications, a large amount of data is generated about diverse aspects of...

With the increasing use of precision agriculture and technological development, the agricultural sector has been majorly transformed. Precision agriculture uses technological innovations such as sensors, drones, and data analysis tools to improve the productivity of resources and management decisions on the farm. Since these technologies collect a...

Telehealth systems have evolved into more prevalent services that can serve people in remote locations and at their homes via smart devices and 5G systems. Protecting the privacy and security of users is crucial in such online systems. Although there are many protocols to provide security through strong authentication systems, sophisticated IoT att...

Artificial intelligence (AI) applications are an integral and emerging component of digital agriculture. AI can help ensure sustainable production in agriculture by enhancing agricultural operations and decision-making. Recommendations about soil condition and pesticides or automatic devices for milking and apple picking are examples of AI applicat...

With the rapid growth of population and the increasing demand for food worldwide, improving productivity in farming procedures is essential. Smart farming is a concept that emphasizes the use of modern technologies such as the Internet of Things (IoT) and artificial intelligence (AI) to enhance productivity in farming practices. In a smart farming...

The growth in the use of Information and Communications Technology (ICT) and Artificial intelligence (AI) has improved the productivity and efficiency of modern agriculture, which is commonly referred to as precision farming. Precision farming solutions are dependent on collecting a large amount of data from farms. Despite the many advantages of pr...

With the widespread using Internet in any device and service, several homes and workplace applications have been provided to avoid attacks. Connecting a system or device to an insecure network can create the possibility of being infected by unwanted files. Detecting such files is a vital task in any system. Employing machine learning (ML) is the mo...

Studying face verification has seen tremendous growth over the past years. During the last decade, with the improvement of system processors and memories, deep learning was growth widely and the applications of Convolutional Neural Network (CNN) affected all image processing tasks. But, needing much space to save several parameters of learned model...

Extracting best feature set to reinforce discrimination is always a challenge in machine learning. In this paper, a method named General Locally Linear Combination (GLLC) is proposed to extract automatic features using a deep autoencoder and also to reconstruct a sample based on the other samples sparsely in a low-dimensional space. Extracting feat...

Recent research have depicted that hidden Markov model (HMM) is a persuasive option for malware detection. However, some advanced metamorphic malware are able to overcome the traditional methods based on HMMs. This proposed approach provides a two-layer technique to overcome these challenges. Malware contain various sequences of opcodes some...

Previous research has shown that hidden Markov model (HMM) is a compelling option for malware identification. However, some advanced metamorphic malware have proven to be more challenging to detect with these techniques. In this paper, we separated the importance of the some part of the malware files to train the HMMs aiming at extracting the signi...

nowadays, we face to new malware and other programs we have to protect systems against them. Malware detection is an important issue in computer's field. In this paper we propose a new method to detect malware by API calls. We have developed a fully automated system to extract API call as features effectively from executable files using n-gram stat...

Identifying the most characterizing features of observed data is critical for minimizing the classification error. Feature selection is the process of identifying a small subset of highly predictive features out of a large set of candidate features. In the literature, many feature selection methods approach the task as a search problem, where each...

Malware is a malicious code which is developed to harm a computer or network. The number of malwares is growing so fast and this amount of growth makes the computer security researchers invent new methods to protect computers and networks. There are three main methods used to malware detection: Signature based, Behavioral based and Heuristic ones....

Automatic recognition of handwritten numerals has been widely proposed in various languages. However, some languages such as Persian still need more consideration. In this paper, we proposed a handwritten Persian numerals dataset, which is gathered from people with different range of educational level. Thus, it is more general than other similar Pe...

Feature subset selection plays a key role in both dimensionality and noise reduction. Moreover, it is often used to enhance accuracy in classification and clustering problems while decreasing their complexity. Inspired by Markov Decision Process, the presented paper considers feature subset selection as a one player game and uses Reinforcement Lear...

In supervised learning scenarios, feature selection has been studied widely in the literature. Here, feature selection is considered as an empirical strategy of restricting state space and lessen the complexity of hypothesis. In this work we introduce the environment as a one player game and improve a reinforcement learning method to traverse the s...