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Topic Review
Deep Learning for Motor Imagery Brain–Computer Interface
The field of brain–computer interface (BCI) enables us to establish a pathway between the human brain and computers, with applications in the medical and nonmedical field. Brain computer interfaces can have a significant impact on the way humans interact with machines. In recent years, the surge in computational power has enabled deep learning algorithms to act as a robust avenue for leveraging BCIs. 
  • 262
  • 17 Oct 2023
Topic Review
Fire Detection Based on Deep Learning Approaches
The field of image recognition has witnessed the rise of a particular type of deep neural network (DNN), CNN. Learnable neural networks comprise numerous layers, each of which performs a separate function when extracting or identifying features. Computer vision, a compelling form of AI, is ubiquitous, and is often experienced without us realizing it. Image processing is the area of computer vision and science devoted to imitating elements of the human visual system and enabling computers to discern and process objects in images and videos similarly to humans. Several deep learning (DL) techniques have been effectively applied in various fields of fire and face detection research.
  • 262
  • 02 Jan 2024
Topic Review
Keystroke Dynamics in Personal Characteristics Protection
The rapid development of information and communication technologies and the widespread use of the Internet has made it imperative to implement advanced user authentication methods based on the analysis of behavioural biometric data. In contrast to traditional authentication techniques, such as the simple use of passwords, these new methods face the challenge of authenticating users at more complex levels, even after the initial verification. This is particularly important as it helps to address risks such as the possibility of forgery and the disclosure of personal information to unauthorised individuals. Users can be categorised using keystroke dynamics, in terms of the age group they belong to and in terms of their educational level, with high accuracy rates, which is a strong indication for the creation of applications to enhance user security and facilitate their use of Internet services.
  • 261
  • 06 Nov 2023
Topic Review
Data Completeness and Imputation Methods on Supervised Classifiers
Data completeness is one of the most common challenges that hinder the performance of data analytics platforms. Different studies have assessed the effect of missing values on different classification models based on a single evaluation metric, namely, accuracy. However, accuracy on its own is a misleading measure of classifier performance because it does not consider unbalanced datasets.
  • 261
  • 21 Dec 2023
Topic Review
Hydroponic Monitoring and Controlling System Using ANFIS
Most people are now aware of the importance of a healthy lifestyle, including the importance of consuming vegetables. As a result, the demand for vegetables has increased, and so their production needs to be increased. Currently, most plantations use soil as a growing medium, which is time-consuming and requires a significant amount of space. To modernize cultivation, hydroponic techniques should be adopted. A smart hydroponic system was developed using the adaptive neuro-fuzzy inference system (ANFIS) method, which allows for automatic adjustments based on the collected dataset and remote control through internet of things (IoT) technology.
  • 261
  • 11 Jan 2024
Topic Review
Spiking Neural Networks and Neuromorphic Modeling
Use of Spiking Neural Networks (SNNs) that can capture a model of organisms’ nervous systems, may be simply justified by their unparalleled energy/computational efficiency.
  • 260
  • 19 Sep 2023
Topic Review
Decentralized Federated Learning and Knowledge Graph Embedding
Anomaly detection plays a crucial role in data security and risk management across various domains, such as financial insurance security, medical image recognition, and Internet of Things (IoT) device management. Researchers rely on machine learning to address potential threats in order to enhance data security.
  • 260
  • 15 Dec 2023
Topic Review
Few-Shot Object Detection
Few-shot object detection (FSOD) aims at designing models that can accurately detect targets of novel classes in a scarce data regime. 
  • 259
  • 16 Oct 2023
Topic Review
Securing ATM Payment Transactions
Credit/debit cards are a ubiquitous form of payment at present. They offer a number of advantages over cash, including convenience, security, and fraud protection. In contrast, the inherent vulnerabilities of credit/debit cards and transaction methods have led many payment institutions to focus on strengthening the security of these electronic payment methods. Also, the increasing number of electronic payment transactions around the world have led to a corresponding increase in the amount of money lost due to fraud and cybercrime. This loss of money has a significant impact on businesses and consumers, and it necessitates the development of rigid and robust security designs for securing underlying electronic transaction methods.
  • 259
  • 14 Nov 2023
Topic Review
Multilingual Evidence for Fake News Detection
The rapid spread of deceptive information on the internet can have severe and irreparable consequences. As a result, it is important to develop technology that can detect fake news. Although significant progress has been made in this area, current methods are limited because they focus only on one language and do not incorporate multilingual information. Multiverse—a new feature based on multilingual evidence that can be used for fake news detection and improve existing approaches.
  • 259
  • 02 Feb 2024
Topic Review
Robot Landing Method on Overhead P[ower Transmission Lines
Hybrid inspection robots have been attracting increasing interest in recent years, and are suitable for inspecting long-distance overhead power transmission lines (OPTLs), combining the advantages of flying robots (e.g., UAVs) and climbing robots (e.g., multiple-arm robots). Due to the complex work conditions (e.g., power line slopes, complex backgrounds, wind interference), landing on OPTL is one of the most difficult challenges faced by hybrid inspection robots.
  • 258
  • 01 Sep 2023
Topic Review
Deep Learning Models in Prostate Cancer Diagnosis
Prostate imaging refers to various techniques and procedures used to visualize the prostate gland for diagnostic and treatment purposes. Deep learning (DL) architectures have shown promising effectiveness and relative efficiency in prostate cancer (PCa) diagnosis due to their ability to analyze complex patterns and extract features from medical imaging data.
  • 258
  • 27 Sep 2023
Topic Review
Decomposition for Multivariant Traffic Time Series
Data-driven modeling methods have been widely used in many applications or studies of traffic systems with complexity and chaos. The empirical mode decomposition (EMD) family provides a lightweight analytical method for non-stationary and non-linear data.  A large amount of traffic data in practice are usually multidimensional, so the EMD family cannot be used directly for those data.
  • 256
  • 07 Jun 2023
Topic Review
Healthcare Trust Evolution with Explainable Artificial Intelligence
The developments in IoT, big data, fog and edge networks, and AI technologies have had a profound impact on a number of industries, including medical. The use of artificial intelligence (AI) for therapeutic purposes has been hampered by its inexplicability. Explainable Artificial Intelligence (XAI), a revolutionary movement, has arisen to solve this constraint. By using decision-making and prediction outputs, XAI seeks to improve the explicability of standard AI models.
  • 256
  • 12 Nov 2023
Topic Review
Deep Learning Networks and YOHO English Speech Dataset
The rapid momentum of deep neural networks (DNNs) has yielded state-of-the-art performance in various machine-learning tasks using speaker identification systems. Speaker identification is based on the speech signals and the features that can be extracted from them.
  • 255
  • 07 Sep 2023
Topic Review
Fault Detection Approaches for Lithium-Ion Batteries
Battery fires have become more common owing to the increased use of lithium-ion batteries. Therefore, monitoring technology is required to detect battery anomalies because battery fires cause significant damage to systems. Researchers used Mahalanobis distance (MD) and independent component analysis (ICA) to detect early battery faults in a real-world energy storage system (ESS). The fault types included historical data of battery overvoltage and humidity anomaly alarms generated by the system management program. These are typical preliminary symptoms of thermal runaway, the leading cause of lithium-ion battery fires. The alarms were generated by the system management program based on thresholds. If a fire occurs in an ESS, the humidity inside the ESS will increase very quickly, which means that threshold-based alarm generation methods can be risky. In addition, industrial datasets contain many outliers for various reasons, including measurement and communication errors in sensors. These outliers can lead to biased training results for models. 
  • 255
  • 18 Feb 2024
Topic Review
Deep Learning-Based IVIF Approaches
Infrared and visible image fusion (IVIF) aims to render fused images that maintain the merits of both modalities. 
  • 254
  • 17 Oct 2023
Topic Review
AI-Based Fault Diagnosis of Centrifugal Pump
The fault-related impulses in the centrifugal pump (CP) vibration signal are often attenuated due to the background interference noises, thus affecting the sensitivity of the traditional statistical features towards faults. Furthermore, extracting health-sensitive information from the vibration signal needs human expertise and background knowledge.
  • 254
  • 10 Nov 2023
Topic Review
Smart Sensing-Based Intelligent Healthcare System for Diabetes Patients
An Artificial Intelligence (AI)-enabled human-centered smart healthcare monitoring system can be useful in life saving, specifically for diabetes patients. Diabetes and heart patients need real-time and remote monitoring and recommendation-based medical assistance. Such human-centered smart healthcare systems can not only provide continuous medical assistance to diabetes patients but can also reduce overall medical expenses. In the last decade, machine learning has been successfully implemented to design more accurate and precise medical applications. 
  • 252
  • 08 Dec 2023
Topic Review
Single-Image Super-Resolution
Single-image super-resolution (SISR) aims to reconstruct a high-resolution (HR) image from a low-resolution (LR) one. Among the state-of-the-art realistic image super-resolution (SR) intelligent algorithms, generative adversarial networks (GANs) have achieved impressive visual performance.
  • 251
  • 15 Nov 2023
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