ACM Computing Surveys

Alongside huge volumes of research on deep learning models in NLP in the recent years, there has been much work on benchmark datasets needed to track modeling progress. Question answering and reading comprehension have been particularly prolific in this ...

Smart objects are increasingly widespread and their ecosystem, also known as the Internet of Things (IoT), is relevant in many application scenarios. The huge amount of temporally annotated data produced by these smart devices demands efficient techniques ...

Generative adversarial network (GAN) studies have grown exponentially in the past few years. Their impact has been seen mainly in the computer vision field with realistic image and video manipulation, especially generation, making significant ...

Recent advancements in intelligent surveillance systems for video analysis have been a topic of great interest in the research community due to the vast number of applications to monitor humans’ activities. The growing demand for these systems aims ...

Recent years have experienced sustained focus in research on software defect prediction that aims to predict the likelihood of software defects. Moreover, with the increased interest in continuous deployment, a variant of software defect prediction called ...

GraphQL is a query language and execution engine for web application programming interfaces (APIs) proposed as an alternative to improve data access problems and versioning of representational state transfer APIs. In this article, we thoroughly study the ...

Modern natural language processing (NLP) methods employ self-supervised pretraining objectives such as masked language modeling to boost the performance of various downstream tasks. These pretraining methods are frequently extended with recurrence, ...

Human recognition with biometrics is a rapidly emerging area of computer vision. Compared to other well-known biometric features such as the face, fingerprint, iris, and palmprint, the ear has recently received considerable research attention. The ear ...

Traditional machine learning, mainly supervised learning, follows the assumptions of closed-world learning, i.e., for each testing class, a training class is available. However, such machine learning models fail to identify the classes, which were not ...

Convolutional neural networks (CNNs) have shown promising results and have outperformed classical machine learning techniques in tasks such as image classification and object recognition. Their human-brain like structure enabled them to learn ...

The recent serious cases of spreading false information have posed a significant threat to the social stability and even national security, urgently requiring all circles to respond adequately. Therefore, this survey illustrates how to fight against false ...

A blockchain is a form of distributed ledger technology where transactions as data state changes are permanently recorded securely and transparently without the need for third parties. Besides, introducing smart contracts to the blockchain has added ...

Neurodevelopmental Disorders (NDD) are a group of conditions with onset in the developmental period characterized by deficits in the cognitive and social areas. Conversational agents have been increasingly explored to support therapeutic interventions for ...

Parallelism is often required for performance. In these situations an excess of non-determinism is harmful as it means the program can have several different behaviours or even different results. Even in domains such as high-performance computing where ...

Recent applications of autonomous agents and robots have brought attention to crucial trust-related challenges associated with the current generation of artificial intelligence (AI) systems. AI systems based on the connectionist deep learning neural ...

Data redundancy is ubiquitous in the inputs and intermediate results of Deep Neural Networks (DNN). It offers many significant opportunities for improving DNN performance and efficiency and has been explored in a large body of work. These studies have ...

With recent advances in mobile robotics, autonomous systems, and artificial intelligence, there is a growing expectation that robots are able to solve complex problems. Many of these problems require multiple robots working cooperatively in a multi-robot ...

Although there are methods of artificial intelligence (AI) applied to virtual reality (VR) solutions, there are few studies in the literature. Thus, to fill this gap, we performed a systematic literature review of these methods. In this review, we apply a ...

The smart grid (SG), regarded as the complex cyber-physical ecosystem of infrastructures, orchestrates advanced communication, computation, and control technologies to interact with the physical environment. Due to the high rewards that threats to the ...

Side-channel attacks exploit a physical observable originating from a cryptographic device in order to extract its secrets. Many practically relevant advances in the field of side-channel analysis relate to security evaluations of cryptographic functions ...

The Web Proxy Auto-Discovery protocol (wpad ¹) is widely used despite being flawed. Its purpose is to enable a client machine to autonomously identify an appropriate proxy, if any, to connect to. This can be useful in corporate networks, for example. Its ...

The data produced by various services should be stored and managed in an appropriate format for gaining valuable knowledge conveniently. This leads to the emergence of various data models, including relational, semi-structured, and graph models, and so ...