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Topic Review
Troubleshooting Chatbots Applied to ATM Technical Maintenance Support
The banking industry has been employing artificial intelligence (AI) technologies to enhance the quality of its services. AI algorithms, such as natural language understanding (NLU), have been integrated into chatbots to improve banking applications. 
  • 523
  • 21 Jun 2023
Topic Review
Digital Face Manipulation Creation and Detection
Deepfake refers to the sophisticated manipulation of audiovisual content using deep learning techniques, particularly generative adversarial networks (GANs). It enables the creation of hyper-realistic fake videos or images by seamlessly superimposing one person's face or voice onto another's. These manipulated media raise significant concerns about misinformation, privacy invasion, and the potential to deceive audiences. Deepfakes have sparked discussions about the ethical implications of digital media manipulation and the challenges of distinguishing between genuine and fabricated content in the digital age. Efforts to counter deepfake technology involve developing advanced detection methods and raising awareness about the prevalence of manipulated media.
  • 520
  • 25 Aug 2023
Topic Review
Feature Extraction Methods in Autonomous Driving
The upsurge of autonomous vehicles in the automobile industry will lead to better driving experiences while also enabling the users to solve challenging navigation problems. Reaching such capabilities will require significant technological attention and the flawless execution of various complex tasks, one of which is ensuring robust localization and mapping. Herein, a discussion of the contemporary methods of extracting relevant features from equipped sensors and their categorization as semantic, non-semantic, and deep learning methods is presented. Representativeness, low cost, and accessibility are crucial constraints in the choice of the methods to be adopted for localization and mapping tasks. 
  • 518
  • 28 Feb 2024
Topic Review
Ensemble Learning
Machine learning models are used to create and enhance various disease prediction frameworks. Ensemble learning is a machine learning technique that combines multiple classifiers to improve performance by making more accurate predictions than a single classifier. Although numerous studies have employed ensemble approaches for disease prediction, there is a lack of thorough assessment of commonly used ensemble approaches against highly researched diseases. 
  • 517
  • 29 Jun 2023
Topic Review
AI-Informed Decision Making
AI-assisted decision-making that impacts individuals raises critical questions about transparency and fairness in artificial intelligence (AI). Much research has highlighted the reciprocal relationships between the transparency/explanation and fairness in AI-assisted decision-making. Thus, considering their impact on user trust or perceived fairness simultaneously benefits responsible use of socio-technical AI systems, but currently receives little attention.
  • 516
  • 01 Jul 2022
Topic Review
Real-Time Deep Learning-Based Drowsiness Detection
Drowsy driving can significantly affect driving performance and overall road safety. Statistically, the main causes are decreased alertness and attention of the drivers. The combination of deep learning and computer-vision algorithm applications has been proven to be one of the most effective approaches for the detection of drowsiness. Robust and accurate drowsiness detection systems can be developed by leveraging deep learning to learn complex coordinate patterns using visual data. Deep learning algorithms have emerged as powerful techniques for drowsiness detection because of their ability to learn automatically from given inputs and feature extractions from raw data. Eye-blinking-based drowsiness detection was applied, which utilized the analysis of eye-blink patterns.
  • 516
  • 07 Aug 2023
Topic Review
Routing Services in Smart Cities
The vehicle routing problem (VRP) is a complex optimization problem, in which there exists a set of clients at various locations, each one with a shipment need, and a fleet of vehicles, departing from the central depot that shall optimally satisfy the needs of the clients. The aim of a typical VRP is to find out the optimal route to minimize the total costs. Furthermore, various factors affecting route planning, such as vehicle capacity, fuel consumption, traffic congestion, etc., have to be considered to accomplish the minimization of the total route costs.
  • 514
  • 31 Jan 2023
Topic Review
The Synergistic Relationship between AI and the Economy
Artificial intelligence (AI) is transforming various aspects of the economy, including manufacturing, healthcare, finance, and transportation. AI-powered systems are augmenting human decision-making, reducing operational costs, enhancing productivity, and creating new business models. However, the integration of AI into the economy also poses several challenges, such as job displacement, economic inequality, and ethical concerns. This research explores the complex relationship between AI and the economy, highlighting the opportunities and challenges that arise from their synergy.
  • 514
  • 18 May 2023
Topic Review
Augmented Reality-Artificial Intelligence Tools in Manufacturing
An important research area in the field of Industry 4.0 is to find a user-interface that is as convenient and intuitive to use as possible to ensure optimal human–machine interaction. Augmented Reality (AR) together with Advanced Image Recognition, powered by Artificial Intelligence (AI) seem to be a set of technologies supportive in this topic. Apart from user friendly interface, AR-AI tools are proved to provide time savings in manufacturing tasks, while simplifying the job at the same time, enabling inexperienced, unskilled, or less skilled employees to perform the work in the selected manual production processes.
  • 513
  • 24 Jun 2022
Topic Review
A Promising Downsampling Alternative in a Neural Network
Downsampling, which aims to improve computational efficiency by reducing the spatial resolution of feature maps, is a critical operation in neural networks. Upsampling also plays an important role in neural networks. It is often used for image super-resolution, segmentation, and generation tasks via the reconstruction of high-resolution feature maps during the decoding stage in the neural network.
  • 513
  • 04 Dec 2023
Topic Review
Approach for Overlapped Segmentation of Bacterial Cell Images
Scanning electron microscopy (SEM) techniques have been extensively performed to image and study bacterial cells with high-resolution images. Bacterial image segmentation in SEM images is an essential task to distinguish an object of interest and its specific region.
  • 512
  • 15 Dec 2022
Topic Review
Development of AI in Surgery after SARS-CoV-2 Pandemic
SARS-CoV-2 has significantly transformed the healthcare environment, and it has triggered the development of electronic health and artificial intelligence mechanisms, for instance. 
  • 511
  • 04 Nov 2021
Topic Review
Mental Fatigue Detection Using Physiological Signals
Fatigue is a state characterized by both physical and mental exhaustion, resulting from prolonged activity, inadequate rest, or excessive cognitive demands. Physiological signals offer a valuable insight into the body’s internal state. Monitoring and interpreting these signals provide real-time information about an individual’s physical and mental condition, enabling early fatigue detection. 
  • 511
  • 10 Nov 2023
Topic Review
Neural Architecture Search: A Computer Vision Perspective
Deep learning (DL) has been widely studied using various methods across the globe, especially with respect to training methods and network structures, proving highly effective in a wide range of tasks and applications, including image, speech, and text recognition. One important aspect of this advancement is involved in the effort of designing and upgrading neural architectures, which has been consistently attempted thus far. However, designing such architectures requires the combined knowledge and know-how of experts from each relevant discipline and a series of trial-and-error steps. In this light, automated neural architecture search (NAS) methods are increasingly at the center of attention.
  • 510
  • 06 May 2023
Topic Review
Electrocardiogram Signal Denoising
The electrocardiogram (ECG) is widely used in medicine because it can provide basic information about different types of heart disease. 
  • 510
  • 29 Nov 2023
Topic Review
The Methods of Fall Detection
Falls by an older person are a significant public health issue because they can result in disabling fractures and cause severe psychological problems that diminish a person’s level of independence. Falls can be fatal, particularly for the elderly. Fall Detection Systems (FDS) are automated systems designed to detect falls experienced by older adults or individuals. Early or real-time detection of falls may reduce the risk of major problems.
  • 509
  • 09 Jun 2023
Topic Review
Gabor Filters
The use of Gabor filters in image processing has been well-established, and these filters are recognized for their exceptional feature extraction capabilities. These filters are usually applied through convolution.
  • 509
  • 19 Dec 2023
Topic Review
Explainable AI (XAI) Explanation Techniques
Interest in artificial intelligence (AI) has been increasing rapidly over the past decade and has expanded to essentially all domains. Along with it grew the need to understand the predictions and suggestions provided by machine learning. Explanation techniques have been researched intensively in the context of explainable AI (XAI), with the goal of boosting confidence, trust, user satisfaction, and transparency.
  • 508
  • 19 Jun 2023
Topic Review
Intelligence Edge Computing
Intelligence Edge Computing (IEC) is the key enabler of emerging 5G technologies networks and beyond. IEC is considered to be a promising backbone of future services and wireless communication systems in 5G integration. In addition, IEC enables various use cases and applications, including autonomous vehicles, augmented and virtual reality, big data analytic, and other customer-oriented services. 
  • 507
  • 23 Jun 2021
Topic Review
Machine-Learning Forensics
A world-wide trend has been observed that there is widespread adoption across all fields to embrace smart environments and automation. Smart environments include a wide variety of Internet-of-Things (IoT) devices, so many challenges face conventional digital forensic investigation (DFI) in such environments. These challenges include data heterogeneity, data distribution, and massive amounts of data, which exceed digital forensic (DF) investigators’ human capabilities to deal with all of these challenges within a short period of time.
  • 506
  • 21 Sep 2023
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