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Topic Review Peer Reviewed
AI-Driven Non-Destructive Testing Insights
Non-destructive testing (NDT) is essential for evaluating the integrity and safety of structures without causing damage. The integration of artificial intelligence (AI) into traditional NDT methods can revolutionize the field by automating data analysis, enhancing defect detection accuracy, enabling predictive maintenance, and facilitating data-driven decision-making. This entry provides a comprehensive overview of AI-enhanced NDT, detailing AI models and their applications in techniques like ultrasonic testing and ground-penetrating radar. Case studies demonstrate that AI can improve defect detection accuracy and reduce inspection times. Challenges related to data quality, ethical considerations, and regulatory standards were discussed as well. By summarizing established knowledge and highlighting advancements, this entry serves as a valuable reference for engineers and researchers, contributing to the development of safer and more efficient infrastructure management practices. 
  • 571
  • 22 Nov 2024
Topic Review
Hybrid Multi-Label Classification Model for Medical Applications
Multi-label classification is typically used in different data mining applications, like labeling videos, images, music, and texts. Multi-label classification classifies documents into various classes simultaneously based on their properties.
  • 570
  • 16 Aug 2023
Topic Review
Incremental Scene Classification Using Dual Knowledge Distillation
Conventional deep neural networks face challenges in handling the increasing amount of information in real-world scenarios where it is impractical to gather all the training data at once. Incremental learning, also known as continual learning, provides a solution for lightweight and sustainable learning with neural networks.
  • 570
  • 08 Feb 2024
Topic Review
Algorithms for Histopathology Image Detection and Segmentation
Histopathology image analysis is considered as a gold standard for the early diagnosis of serious diseases such as cancer. The advancements in the field of computer-aided diagnosis (CAD) have led to the development of several algorithms for accurately segmenting histopathology images.
  • 570
  • 27 Nov 2023
Topic Review
Facial Expression Recognition System Using Convolutional Neural Network
Recognizing facial expressions plays a crucial role in various multimedia applications, such as human–computer interactions and the functioning of autonomous vehicles. An individual’s facial expressions (FEs) or countenance convey their psychological reactions and intentions in response to a social or personal event. These expressions convey non-verbal stealth messages. With technological advancements, human behavior can be understood through facial expression recognition (FER). To express emotions, humans use facial expressions as their primary nonverbal communication method.
  • 569
  • 17 Nov 2023
Topic Review
Particle Swarm Optimisation for Emotion Recognition Systems
Particle Swarm Optimisation (PSO) is a popular technique in the field of Swarm Intelligence (SI) that focuses on optimisation. Researchers have explored multiple algorithms and applications of PSO, including exciting new technologies, such as Emotion Recognition Systems (ERS), which enable computers or machines to understand human emotions.
  • 568
  • 26 Oct 2023
Topic Review
Smoke and Fire Detection Approaches
Forest fires rank among the costliest and deadliest natural disasters globally. Identifying the smoke generated by forest fires is pivotal in facilitating the prompt suppression of developing fires. Nevertheless, succeeding techniques for detecting forest fire smoke encounter persistent issues, including a slow identification rate, suboptimal accuracy in detection, and challenges in distinguishing smoke originating from small sources.
  • 566
  • 17 Nov 2023
Topic Review
Brain Tumor  Segmentation
Brain tumor segmentation plays a crucial role in the diagnosis, treatment planning, and monitoring of brain tumors. Accurate segmentation of brain tumor regions from multi-sequence magnetic resonance imaging (MRI) data is of paramount importance for precise tumor analysis and subsequent clinical decision making. The ability to delineate tumor boundaries in MRI scans enables radiologists and clinicians to assess tumor size, location, and heterogeneity, facilitating treatment planning and evaluating treatment response. Traditional manual segmentation methods are time-consuming, subjective, and prone to inter-observer variability. Therefore, the automatic segmentation algorithm has received widespread attention as an alternative solution. For instance, the self-organizing map (SOM) is an unsupervised exploratory data analysis tool that leverages principles of vector quantization and similarity measurement to automatically partition images into self-similar regions or clusters. Segmentation methods based on SOM have demonstrated the ability to distinguish high-level and low-level features of tumors, edema, necrosis, cerebrospinal fluid, and healthy tissue.
  • 566
  • 04 Mar 2024
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.
  • 566
  • 15 Nov 2023
Topic Review
The Role of AI in Renewable Energy
Renewable energy sources such as solar and wind power are becoming increasingly important as we seek to reduce our reliance on fossil fuels and mitigate the effects of climate change. At the same time, artificial intelligence (AI) is rapidly advancing and finding applications in a wide range of fields, including renewable energy. The role of AI in the future of renewable energy, including its potential to optimize energy systems, improve the efficiency of renewable energy technologies, and reduce maintenance costs were described. The open challenges and future directions for the use of AI in the renewable energy sector, as well as the countries that are pioneers in this field were discussed.
  • 565
  • 22 May 2023
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.
  • 565
  • 01 Sep 2023
Topic Review
Blockchain and Machine Learning-Based Hybrid IDS
The cyberspace is a convenient platform for creative, intellectual, and accessible works that provide a medium for expression and communication. Malware, phishing, ransomware, and distributed denial-of-service attacks pose a threat to individuals and organisations. To detect and predict cyber threats effectively and accurately, an intelligent system must be developed. Cybercriminals can exploit Internet of Things devices and endpoints because they are not intelligent and have limited resources.
  • 565
  • 19 Sep 2023
Topic Review
Multi-Domain Feature Alignment for Face Anti-Spoofing
Face anti-spoofing is critical for enhancing the robustness of face recognition systems against presentation attacks. Existing methods predominantly rely on binary classification tasks. An adversarial learning process is designed to narrow the differences between domains, achieving the effect of aligning the features of multiple sources, thus resulting in multi-domain alignment.
  • 564
  • 07 Oct 2023
Topic Review
Gait Recognition
Gait recognition aims to identify a person based on his unique walking pattern. Compared with silhouettes and skeletons, skinned multi-person linear (SMPL) models can simultaneously provide human pose and shape information and are robust to viewpoint and clothing variances. 
  • 563
  • 27 Nov 2023
Topic Review
Customer Advocacy
The rise of online social networks has revolutionized the way businesses and consumers interact, creating new opportunities for customer word-of-mouth (WoM) and brand advocacy. 
  • 562
  • 07 Oct 2023
Topic Review
Text Emotions on Non-English Datasets
Machine learning approaches, in particular graph learning methods, have achieved great results in the field of natural language processing, in particular text classification tasks. However, many of such models have shown limited generalization on datasets in different languages. 
  • 562
  • 23 Oct 2023
Topic Review
Optimizing Session-Aware Recommenders
Recommendation mechanisms have emerged as vital tools for the filtering of information in various aspects of life. They are widely used in commercial platforms, including e-commerce sites like Amazon. Session-based or session-aware recommendation is more attractive due to the recommendation accuracy.
  • 562
  • 26 Feb 2024
Topic Review
Single-Image Super-Resolution Models to Video Super-Resolution
The quality of videos varies due to the different capabilities of sensors. Video super-resolution (VSR) is a technology that improves the quality of captured video.
  • 561
  • 16 Aug 2023
Topic Review
Diabetic Retinopathy Lesion Identification and Multiple Instance Learning
Accurate identification of lesions and their use across different medical institutions are the foundation and key to the clinical application of automatic diabetic retinopathy (DR) detection. Existing detection or segmentation methods can achieve acceptable results in DR lesion identification, but they strongly rely on a large number of fine-grained annotations that are not easily accessible and suffer severe performance degradation in the cross-domain application.
  • 560
  • 11 Oct 2023
Topic Review
Sustainable Ship Management Post COVID-19
COVID-19 is spreading out in the world now. Passenger ships such as cruise ships are very critical in this situation. Boats’ hazardous areas need to be identified in advance and managed carefully to prevent the virus. Three technologies are required to support the sustainable management of ships in the post-COVID-19 era. They are ship indoor positioning, close contact identification, and risk area calculation. Ship environment-aware indoor positioning algorithms are proposed for the first time for the moving ship environment, followed by a clustering algorithm for close contact identification. Then, the risk area is calculated using the convex hull algorithm. Finally, a sustainable management approach for ships post COVID-19 is proposed.
  • 558
  • 10 Jan 2022
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