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Topic Review
Machine Learning-based Driver Drowsiness Detection Using Visual Features
Drowsiness-related car accidents continue to have a significant effect on road safety. Many of these accidents can be eliminated by alerting the drivers once they start feeling drowsy. Image-based systems are the most commonly used techniques for detecting driver drowsiness. Facial parameters such as the eyes, mouth, and head can be used to identify many visual behaviors that fatigued people exhibit.
  • 540
  • 06 Jun 2023
Topic Review
Enhancing Social Media Platforms with Machine Learning
Network analysis aids management in reducing overall expenditures and maintenance workload. Social media platforms frequently use neural networks to suggest material that corresponds with user preferences. Machine learning is one of many methods for social network analysis. Machine learning algorithms operate on a collection of observable features that are taken from user data. Machine learning and neural network-based systems represent a topic of study that spans several fields. Computers can now recognize the emotions behind particular content uploaded by users to social media networks thanks to machine learning.
  • 539
  • 19 Jun 2023
Topic Review
Deep Learning for Automated Visual Inspection
This article evaluates the state of the art of deep-learning-based automated visual inspection in manufacturing and maintenance applications and contrasts it to academic research in the field of computer vision. By doing so itidentifies to what extent computer vision innovations are already being used and which potential improvements could be realized by further transferring promising concepts. Existing work is either focused on specific industry sectors or methodologies but not on industrial VI as a whole or is outdated by almost two decades. We surveyed 196 open access publications from 2010 to March 2023 from the fields of manufacturing and maintenance with no restriction regarding industries. Our main findings were: The vast majority of publications utilize supervised learning approaches on relatively small datasets with convolutional neural networks. The timegap between publication of new approaches in deep learning-based computer vision and its first application in industrial visual inspection is approximately three years First vision transformer models emerge in 2022 and seem to outperform established models but their excellent self-supervised learning capabilities are not explored to date
  • 539
  • 26 Feb 2024
Topic Review
Infrared and Visible Image Fusion Technologies
Infrared and visible image fusion is to combine the information of thermal radiation and detailed texture from the two images into one informative fused image. Deep learning methods have been widely applied in this task; however, those methods usually fuse multiple extracted features with the same fusion strategy, which ignores the differences in the representation of these features, resulting in the loss of information in the fusion process. Infrared and visible image fusion techniques can be divided into two categories: traditional methods and deep learning-based methods. Traditional methods have been proposed for the fusion of pixel-level or fixed features. 
  • 535
  • 03 Feb 2023
Topic Review
Automated Fact Verification Systems
The rapid growth in Artificial Intelligence (AI) has led to considerable progress in Automated Fact Verification (AFV). This process involves collecting evidence for a statement, assessing its relevance, and predicting its accuracy.
  • 533
  • 01 Dec 2023
Topic Review
Ontology-Based Regression Testing
Regression testing is a relevant research field focused on ensuring software works correctly after being modified or when new functionalities are added. The widespread use of information technology techniques has enabled the rapid development of applications.
  • 530
  • 04 Nov 2021
Topic Review
Obfuscated Memory Malware Detection
Obfuscated Memory Malware (OMM) presents significant threats to interconnected systems, including smart city applications, for its ability to evade detection through concealment tactics. Existing OMM detection methods primarily focus on binary detection. 
  • 530
  • 24 Jul 2023
Topic Review
Transformer Framework and YOLO Framework for Object Detection
Object detection for remote sensing is a fundamental task in image processing of remote sensing; as one of the core components, small or tiny object detection plays an important role. 
  • 529
  • 25 Aug 2023
Topic Review
6-DoF Object Pose Estimation
Accurately estimating the six-degree-of-freedom (6-DoF) of objects is a critical task in various applications, including robotics, autonomous driving, and virtual reality. For instance, the precise estimation of spatial coordinates and rotational orientation of an object is essential for robotic tasks such as manipulation, navigation, and assembly.
  • 529
  • 13 Oct 2023
Topic Review
Automatic Speech Recognition in Portuguese Language
Automatic speech recognition (ASR), commonly known as speech-to-text, is the process of transcribing audio recordings into text, i.e., transforming speech into the respective sequence of words. 
  • 528
  • 15 Jun 2023
Topic Review
Data Extraction Approach for Empirical Agent-Based Model Development
Agent-based model (ABM) development needs information on system components and interactions. Qualitative narratives contain contextually rich system information beneficial for ABM conceptualization. Traditional qualitative data extraction is manual, complex, and time- and resource-consuming. Moreover, manual data extraction is often biased and may produce questionable and unreliable models. A possible alternative is to employ automated approaches borrowed from Artificial Intelligence.
  • 528
  • 29 Sep 2023
Topic Review
Classification of Sleep Stages Using Telemetry Polysomnography
Accurate sleep stage detection is crucial for diagnosing sleep disorders and tailoring treatment plans. Polysomnography (PSG) is considered the gold standard for sleep assessment as it captures diverse physiological signals. Recent advancements have shown that simpler machine learning models, when coupled with sophisticated feature extraction techniques, can yield accurate and reliable results comparable to those achieved by complex deep learning methods. These simpler models not only reduce the computational burden but also offer greater interpretability, a feature that is highly valued in clinical settings for both diagnostic and treatment purposes. Therefore, integrating simpler machine learning algorithms with advanced feature extraction can serve as an effective and efficient approach for sleep stage classification in research and clinical applications.
  • 527
  • 25 Aug 2023
Topic Review
Video Summarization
During the last few years, several technological advances have led to an increase in the creation and consumption of audiovisual multimedia content. Users are overexposed to videos via several social media or video sharing websites and mobile phone applications. For efficient browsing, searching, and navigation across several multimedia collections and repositories, e.g., for finding videos that are relevant to a particular topic or interest, this ever-increasing content should be efficiently described by informative yet concise content representations. A common solution to this problem is the construction of a brief summary of a video, which could be presented to the user, instead of the full video, so that she/he could then decide whether to watch or ignore the whole video. Such summaries are ideally more expressive than other alternatives, such as brief textual descriptions or keywords. 
  • 527
  • 16 Oct 2023
Topic Review
Recommender System for the Tourism Domain
Tourism is a widespread activity and a huge industry, in their travels, tourists have to select among numerous alternatives of landmarks, places and in general points of interest (POIs) they can visit. This can be challenging for travellers that have no prior experience of or “inside knowledge” regarding their destination, and even more so for short-term visits. As a result, a booming industry of travel-related recommender systems (RSs) has been developed, in order to provide users with recommendations most relevant to their interests. Recommender systems are considered to be personalized and non-personalized. Personalized recommender systems extrapolate user’s preferences to create efficient recommendations based on the users’ past interaction with the system. On the contrary, non-personalized recommenders suggest items that are most relevant and popular among all users.
  • 526
  • 23 Oct 2023
Topic Review
Breast Density and Pre-Trained Convolutional Neural Network
Breast density describes the amount of fibrous and glandular tissue in a breast compared with the amount of fatty tissue. The breast density is assigned to one of four classes in the mammogram report based on the ACR BI-RADS standard. Convolutional Neural Network (CNN) are a type of artificial neural network usually used for classification and computer vision tasks. Therefore, CNNs are considered efficient tools for medical imaging classification.
  • 525
  • 21 Jun 2022
Topic Review
Semantic Image Segmentation with Scantly Annotated Data
Semantic image segmentation is the task of assigning to each pixel the class of its enclosing object or region as its label, thereby creating a segmentation mask. The success of deep networks for the semantic segmentation of images is limited by the availability of annotated training data. The manual annotation of images for segmentation is a tedious and time-consuming task that often requires sophisticated users with significant domain expertise to create high-quality annotations over hundreds of images.
  • 525
  • 18 Jul 2022
Topic Review
COVID-19 Vaccines Related User’s Response Categorization
Respiratory viruses known as coronaviruses infect people and cause death. The multiple crown-like spikes on the virus’s surface give them the name “corona”. The pandemic has resulted in a global health crisis and it is expected that every year people will have to fight against different COVID-19 variants. In this critical situation, the existence of COVID-19 vaccinations provides hope for mankind. Despite severe vaccination campaigns and recommendations from health experts and the government, people have perceptions regarding vaccination risks and share their views and experiences on social media platforms. Social attitudes to these types of vaccinations are influenced by their positive and negative effects. The analysis of such opinions can help to determine social trends and formulate policies to increase vaccination acceptance. 
  • 524
  • 21 Oct 2022
Topic Review
Quantum Machine Learning
Quantum computing has been proven to excel in factorization issues and unordered search problems due to its capability of quantum parallelism. This unique feature allows exponential speed-up in solving certain problems. However, this advantage does not apply universally, and challenges arise when combining classical and quantum computing to achieve acceleration in computation speed.
  • 524
  • 01 Jun 2023
Topic Review
GIS and Reinforcement Learning for Aquaculture Disease Transmission
Aquaculture, a critical domain in sustainable food production, is increasingly relying on Geographic Information Systems (GIS) for disease transmission analysis. GIS, an advanced digital mapping and analytical tool, not only helps visualize the geographical spread of diseases but also discerns patterns and offers predictive insights. By integrating a variety of datasets, from environmental to biological, GIS enables comprehensive analysis of disease risk zones, facilitating preemptive measures and efficient resource allocation.
  • 524
  • 23 Nov 2023
Topic Review
Vision-Based Gait Recognition
Identifying people’s identity by using behavioral biometrics has attracted many researchers’ attention in the biometrics industry. Gait is a behavioral trait, whereby an individual is identified based on their walking style. Over the years, gait recognition has been performed by using handcrafted approaches. Due to several covariates’ effects, the competence of the approach has been compromised. Deep learning is an emerging algorithm in the biometrics field, which has the capability to tackle the covariates and produce highly accurate results. 
  • 523
  • 12 Aug 2022
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