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Topic Review
Personalized Advertising Design Based on Individual’s Appearance
Market segmentation is a crucial marketing strategy that involves identifying and defining distinct groups of buyers to target a company’s marketing efforts effectively. Visual elements, such as color and shape, in advertising can effectively communicate the product or service being promoted and influence consumer perceptions of its quality. Similarly, a person’s outward appearance plays a pivotal role in nonverbal communication, significantly impacting human social interactions and providing insights into individuals’ emotional states.
  • 393
  • 13 Sep 2023
Topic Review
Multi-Scene Mask Detection
Deep learning for mask detection has important demand in medical and industrial production, which reflects the application of neural networks and image sensors in daily life. During an epidemic of respiratory viruses, mask detection can effectively supervise the wearing of masks, thereby reducing the risk of virus transmission.
  • 392
  • 04 Dec 2023
Topic Review
Improving Visual Defect Detection
Reliable functionality in anomaly detection in thermal image datasets is crucial for defect detection of industrial products. Nevertheless, achieving reliable functionality is challenging, especially when datasets are image sequences captured during equipment runtime with a smooth transition from healthy to defective images. This causes contamination of healthy training data with defective samples. Anomaly detection methods based on autoencoders are susceptible to a slight violation of a clean training dataset and lead to challenging threshold determination for sample classification. 
  • 391
  • 06 Sep 2023
Topic Review
NSGA-PINN for Physics-Informed Neural Network Training
Non-dominated sorting genetic algorithm (NSGA)-Physics-informed neural networks (PINNs), a multi-objective optimization framework for the effective training of PINNs. 
  • 391
  • 10 Nov 2023
Topic Review
High-Fidelity Synthetic Face Generation for Rosacea Skin Condition
Similarly to the majority of deep learning applications, diagnosing skin diseases using computer vision and deep learning often requires a large volume of data. However, obtaining sufficient data for particular types of facial skin conditions can be difficult, due to privacy concerns. As a result, conditions like rosacea are often understudied in computer-aided diagnosis. The limited availability of data for facial skin conditions has led to the investigation of alternative methods of computer-aided diagnosis. Generative adversarial networks (GANs), mainly variants of StyleGANs, have demonstrated promising results in generating synthetic facial images.
  • 391
  • 14 Feb 2024
Topic Review
Multi-Label Classification Based on Associations
Associative classification (AC) has been shown to outperform other methods of single-label classification for over 20 years. In order to create rules that are both more precise and simpler to grasp, AC combines the rules of mining associations with the task of classification.
  • 390
  • 08 Dec 2023
Topic Review
LiDAR Local Domain Adaptation for Autonomous Vehicles
Perception algorithms for autonomous vehicles demand large, labeled datasets. Real-world data acquisition and annotation costs are high, making synthetic data from simulation a cost-effective option. However, training on one source domain and testing on a target domain can cause a domain shift attributed to local structure differences, resulting in a decrease in the model’s performance. Domain adaptation is a form of transfer learning that aims to minimize the domain shift between datasets.
  • 389
  • 05 Jan 2024
Topic Review
Graph Clustering Algorithms
Graph clustering has received considerable attention, and its applications are numerous, ranging from the detection of social communities to the clustering of computer networks. It is classified as an NP-class problem, and several algorithms have been proposed with specific objectives. There also exist various quality metrics for evaluating them. Having clusters with the required density can be beneficial because it permits the effective deployment of resources.
  • 389
  • 26 Jan 2024
Topic Review
Machine-Learning Methods for Speech and Handwriting Detection
Brain–Computer Interfaces (BCIs) have become increasingly popular due to their potential applications in diverse fields, ranging from the medical sector (people with motor and/or communication disabilities), cognitive training, gaming, and Augmented Reality/Virtual Reality (AR/VR), among other areas. BCI which can decode and recognize neural signals involved in speech and handwriting has the potential to greatly assist individuals with severe motor impairments in their communication and interaction needs. Innovative and cutting-edge advancements in this field have the potential to develop a highly accessible and interactive communication platform for these people.
  • 389
  • 30 Jun 2023
Topic Review
Emotion Recognition Systems
Emotion recognition systems (ERS) are an emerging technology with immense potential, exemplifying the innovative utilization of artificial intelligence (AI) within the context of the fourth industrial revolution (IR 4.0). Given that personalization is a key feature of the fifth industrial revolution (IR 5.0), ERS has the potential to serve as an enabler for IR 5.0. Furthermore, the COVID-19 pandemic has increased the relevance of this technology as work processes were adapted for social distancing and the use of face masks. Even in the post-pandemic era, many individuals continue to wear face masks. Therefore, ERS offers a technological solution to address communication challenges in a masked world. The existing body of knowledge on ERS primarily focuses on exploring modalities or modes for emotion recognition, system development, and the creation of applications utilizing emotion recognition functions.
  • 388
  • 14 Nov 2023
Topic Review
Quantifying Digital Biomarkers for Well-Being
Wearable devices have become ubiquitous, collecting rich temporal data that offers valuable insights into human activities, health monitoring, and behavior analysis. Leveraging these data, researchers have developed innovative approaches to classify and predict time-based patterns and events in human life. Time-based techniques allow the capture of intricate temporal dependencies, which is the nature of the data coming from wearable devices.
  • 388
  • 27 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.
  • 388
  • 02 Feb 2024
Topic Review
Application of Deep Learning in Cancer Diagnoses
The application of deep learning technology to realize cancer diagnosis based on medical images is one of the research hotspots in the field of artificial intelligence and computer vision. Deep learning has succeeded greatly in medical image-based cancer diagnosis. 
  • 387
  • 19 Jul 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.
  • 387
  • 26 Oct 2023
Topic Review
Explainable AI for Health Care
Artificial intelligence (AI) have facilitated its widespread adoption in primary medical services, addressing the demand–supply imbalance in healthcare. Vision Transformers (ViT) have emerged as state-of-the-art computer vision models, benefiting from self-attention modules. However, compared to traditional machine learning approaches, deep learning models are complex and are often treated as a “black box” that can cause uncertainty regarding how they operate. Explainable artificial intelligence (XAI) refers to methods that explain and interpret machine learning models’ inner workings and how they come to decisions, which is especially important in the medical domain to guide healthcare decision-making processes. 
  • 387
  • 18 Jan 2024
Topic Review
Perceptual Encryption-Based Image Communication System for Tuberculosis Diagnosis
Block-based perceptual encryption (PE) algorithms are becoming popular for multimedia data protection because of their low computational demands and format-compliancy with the JPEG standard. In conventional methods, a colored image as an input is a prerequisite to enable smaller block size for better security. However, in domains such as medical image processing, unavailability of color images makes PE methods inadequate for their secure transmission and storage. A PE method that is applicable for both color and grayscale images is proposed. The EfficientNetV2-based model is implemented for automatic tuberculosis (TB) diagnosis in chest X-ray images.
  • 386
  • 21 Sep 2022
Topic Review
Concept Prerequisite Learning with PTM and GNN
Prerequisite chains are crucial to acquiring new knowledge efficiently. Many studies have been devoted to automatically identifying the prerequisite relationships between concepts from educational data. Though effective to some extent, these methods have neglected two key factors: most works have failed to utilize domain-related knowledge to enhance pre-trained language models, thus making the textual representation of concepts less effective; they also ignore the fusion of semantic information and structural information formed by existing prerequisites.
  • 386
  • 04 Sep 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.
  • 386
  • 07 Sep 2023
Topic Review
Detecting Misalignment State of Angle Cocks
As one of the key components in the braking system, the angle cock is the switch of the train ventilation duct, which realizes the braking through the air transmission between carriages, so that the train can achieve the purpose of regulating speed or stopping.
  • 385
  • 05 Sep 2023
Topic Review
Linked Data Interfaces
In the era of big data, linked data interfaces play a critical role in enabling access to and management of large-scale, heterogeneous datasets. This research investigates forty-seven interfaces developed by the semantic web community in the context of the Web of Linked Data, displaying information about general topics and digital library contents. The interfaces are classified based on their interaction paradigm, the type of information they display, and the complexity reduction strategies they employ. The main purpose to be addressed is the possibility of categorizing a great number of available tools so that comparison among them becomes feasible and valuable. The analysis reveals that most interfaces use a hybrid interaction paradigm combining browsing, searching, and displaying information in lists or tables. Complexity reduction strategies, such as faceted search and summary visualization, are also identified. Emerging trends in linked data interface focus on user-centric design and advancements in semantic annotation methods, leveraging machine learning techniques for data enrichment and retrieval. Additionally, an interactive platform is provided to explore and compare data on the analyzed tools. Overall, there is no one-size-fits-all solution for developing linked data interfaces and tailoring the interaction paradigm and complexity reduction strategies to specific user needs is essential.
  • 385
  • 08 Sep 2023
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