22,025+ open-access research outputs.
A learning-based image relighting framework is proposed for automatically changing the lighting conditions of facial images from one lighting source to another. Given only a 2D unseen facial testing i…
In this study, a framework for Android malware detection based on permissions is presented. This framework uses multiple linear regression methods. Application permissions, which are one of the most c…
The apparent tardiness cost (ATC) is a dispatching rule that demonstrates excellent performance in minimizing the total weighted tardiness (TWT) in single-machine scheduling. The ATC rule’s performanc…
Radio Access Network (RAN) disaggregation allows operators to mix-and-match multivendor components and bring RAN services from one end to the other. Despite this goal, issues of resource misuse or per…
Depth estimation from a single image is a challenging task, yet this field has a promising prospect in automatic driving and augmented reality. However, the prediction accuracy is degraded significant…
In classification tasks, training labels are usually specified as one-hot targets which represent each class equally and exclusively. However, this labeling rule is not suitable in some situations. Fo…
Physical servers are available as-a-service in bare-metal public and private cloud platforms, and their demand has been proliferating because of the high levels of privacy and security guarantees they…
Human visual Attention modelling is a persistent interdisciplinary research challenge, gaining new interest in recent years mainly due to the latest developments in deep learning. That is particularly…
The mild symptoms in Mild Cognitive Impairment (MCI), a precursor of dementia, often go unnoticed and are assumed as normal aging signs. Such negligence result in late visits which consequently, lead …
Pedestrian detection is an important branch of computer vision, and has important applications in the fields of autonomous driving, artificial intelligence and video surveillance. With the rapid devel…
Support Vector Machine (SVM) is a supervised machine learning algorithm, which is used for robust and accurate classification. Despite its advantages, its classification speed deteriorates due to its …
Network Intrusion Detection Systems (NIDSs) using pattern matching have a fatal weakness in that they cannot detect new attacks because they only learn existing patterns and use them to detect those a…
Predicting heart disease is regarded as one of the most difficult challenges in the health-care profession. To predict cardiac disease, researchers employed a variety of algorithms including LDA, RF, …
Data transformation is a laborious and time-consuming task for analysts. Programming by example (PBE) is a technique that can simplify this difficult task for data analysts by automatically generating…
The outbreak of Covid-19 and the enforcement of lockdown, social distancing, and other precautionary measures lead to a global increase in online shopping. The increasing significance of online shoppi…
As the number of Internet of Things (IoT) devices and applications increases, the capacity of the IoT access networks is considerably stressed. This can create significant performance bottlenecks in v…
Building energy management has been recognized as of significant importance on improving the overall system efficiency and reducing the greenhouse gas emission. However, the building energy management…
Aircraft trajectory prediction is a challenging problem in air traffic control, especially for conflict detection. Traditional trajectory predictors require a variety of inputs such as flight-plans, a…
The naive Bayesian classification method has received significant attention in the field of supervised learning. This method has an unrealistic assumption in that it views all attributes as equally im…
Developing Question Answering systems (QA) is one of the main goals in Artificial Intelligence. With the advent of Deep Learning (DL) techniques, QA systems have witnessed significant advances. Althou…
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