Image representation is an important topic in computer vision and pattern recognition. It plays a fundamental role in a range of applications toward understanding visual contents. Moment-based image representation has been reported to be effective in ...

Despite the rapid growth and advancement in the Internet of Things (IoT), there are critical challenges that need to be addressed before the full adoption of the IoT. Data privacy is one of the hurdles towards the adoption of IoT as there might be ...

Many proximity-based tracing (PCT) protocols have been proposed and deployed to combat the spreading of COVID-19. In this article, we take a systematic approach to analyze PCT protocols. We identify a list of desired properties of a contact tracing design ...

Vehicular Edge Computing (VEC), based on the Edge Computing motivation and fundamentals, is a promising technology supporting Intelligent Transport Systems services, smart city applications, and urban computing. VEC can provide and manage computational ...

As a subfield of machine learning, reinforcement learning (RL) aims at optimizing decision making by using interaction samples of an agent with its environment and the potentially delayed feedbacks. In contrast to traditional supervised learning that ...

With the proliferation of social sensing, large amounts of observation are contributed by people or devices. However, these observations contain disinformation. Disinformation can propagate across online social networks at a relatively low cost, but ...

The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS traces, and ...

Deep Learning algorithms have achieved state-of-the-art performance for Image Classification. For this reason, they have been used even in security-critical applications, such as biometric recognition systems and self-driving cars. However, recent works ...

In the era of Industry 4.0, the Internet-of-Things (IoT) performs the driving position analogous to the initial industrial metamorphosis. IoT affords the potential to couple machine-to-machine intercommunication and real-time information-gathering within ...

Embedding static graphs in low-dimensional vector spaces plays a key role in network analytics and inference, supporting applications like node classification, link prediction, and graph visualization. However, many real-world networks present dynamic ...

Due to their high computational power and internal memory bandwidth, graphic processing units (GPUs) have been extensively studied by the database systems research community. A heterogeneous query processing system that employs CPUs and GPUs at the same ...

We study the fact-checking problem, which aims to identify the veracity of a given claim. Specifically, we focus on the task of Fact Extraction and VERification (FEVER) and its accompanied dataset. The task consists of the subtasks of retrieving the ...

Face super-resolution (FSR), also known as face hallucination, which is aimed at enhancing the resolution of low-resolution (LR) face images to generate high-resolution face images, is a domain-specific image super-resolution problem. Recently, FSR has ...

Volatility forecasting is an important aspect of finance as it dictates many decisions of market players. A snapshot of state-of-the-art neural network–based financial volatility forecasting was generated by examining 35 studies, published after 2015. ...

Malicious software (malware) is a major cyber threat that has to be tackled with Machine Learning (ML) techniques because millions of new malware examples are injected into cyberspace on a daily basis. However, ML is vulnerable to attacks known as ...

String constraint solving refers to solving combinatorial problems involving constraints over string variables. String solving approaches have become popular over the past few years given the massive use of strings in different application domains like ...

Information flow tracking was proposed more than 40 years ago to address the limitations of access control mechanisms to guarantee the confidentiality and integrity of information flowing within a system, but has not yet been widely applied in practice ...

Understanding and optimizing memory usage of software applications is a difficult task, usually involving the analysis of large amounts of memory-related complex data. Over the years, numerous software visualizations have been proposed to help developers ...

Binary code fingerprinting is crucial in many security applications. Examples include malware detection, software infringement, vulnerability analysis, and digital forensics. It is also useful for security researchers and reverse engineers since it ...

In recent years, with rapid technological advancement in both computing hardware and algorithm, Artificial Intelligence (AI) has demonstrated significant advantage over human being in a wide range of fields, such as image recognition, education, ...

Unmanned Aerial Vehicles (UAVs) are becoming one of the main technological supports for commercial applications, embracing many domains ranging from human safety to the medical field, agriculture and environment, multimedia production, and even commercial ...

Studying information diffusion in SNS (Social Networks Service) has remarkable significance in both academia and industry. Theoretically, it boosts the development of other subjects such as statistics, sociology, and data mining. Practically, diffusion ...

Representing dynamic textures (DTs) plays an important role in many real implementations in the computer vision community. Due to the turbulent and non-directional motions of DTs along with the negative impacts of different factors (e.g., environmental ...