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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.
  • 566
  • 16 Aug 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. 
  • 566
  • 23 Oct 2023
Topic Review
ISTD Based on Background-SuppressionProximal Gradient and GPU Acceleration
Infrared Small-Target Detection (ISTD) is an important component of infrared search and tracking, aiming to exploit the thermal radiation difference between a target and its background to achieve long-range target detection. According to the definition by the Society of Photo-Optical Instrumentation Engineers (SPIE), small targets typically refers to objects in a 256 × 256 image with an area of fewer than 80 pixels, accounting for approximately 0.12% of the total image area.
  • 565
  • 25 Dec 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. 
  • 564
  • 07 Oct 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.
  • 564
  • 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.
  • 563
  • 10 Jan 2022
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.
  • 563
  • 26 Feb 2024
Topic Review
Deceptive Dark-Pattern Web Advertisements
Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users’ experience remains largely unexplored.
  • 558
  • 01 Feb 2024
Topic Review
Recognition of Grasping Patterns for Human–Robot Collaboration
Recent advances in the field of collaborative robotics aim to endow industrial robots with prediction and anticipation abilities. In many shared tasks, the robot’s ability to accurately perceive and recognize the objects being manipulated by the human operator is crucial to make predictions about the operator’s intentions.
  • 558
  • 16 Nov 2023
Topic Review
Abnormal Activity Recognition for Visual Surveillance
Due to the ever increasing number of closed circuit television (CCTV) cameras worldwide, it is the need of the hour to automate the screening of video content. Still, the majority of video content is manually screened to detect some anomalous incidence or activity. Automatic abnormal event detection such as theft, burglary, or accidents may be helpful in many situations. However, there are significant difficulties in processing video data acquired by several cameras at a central location, such as bandwidth, latency, large computing resource needs, and so on. 
  • 558
  • 11 Jan 2024
Topic Review
Learning Individualized Hyperparameter Settings
The performance of optimization algorithms, and consequently of AI/machine learning solutions, is strongly influenced by the setting of their hyperparameters. Over the last decades, a rich literature has developed proposing methods to automatically determine the parameter setting for a problem of interest, aiming at either robust or instance-specific settings. Robust setting optimization is already a mature area of research, while instance-level setting is still in its infancy, with contributions mainly dealing with algorithm selection.
  • 557
  • 03 Jul 2023
Topic Review
Ele-Monitoring Systems and Ontology-Based Models in Asthma Domain
Asthma is a chronic respiratory disease characterized by severe inflammation of the bronchial mucosa. Allergic asthma is the most common form of this health issue. Asthma is classified into allergic and non-allergic asthma, and it can be triggered by several factors such as indoor and outdoor allergens, air pollution, weather conditions, tobacco smoke, and food allergens, as well as other factors. Asthma symptoms differ in their frequency and severity since each patient reacts differently to these triggers. 
  • 556
  • 24 Jun 2022
Topic Review
Imaging Modalities for COVID-19 Diagnosis
The spread and severity of COVID-19 are alarming. The economy and life of countries worldwide have been greatly affected. The rapid and accurate diagnosis of COVID-19 directly affects the spread of the virus and the degree of harm. The X-ray and computed tomography (CT) can image the lungs of patients with COVID-19. Lung imaging can reveal the niduses’ spatial location and the infection’s extent. 
  • 553
  • 11 Jan 2023
Topic Review
Siamese Neural Network for Keystroke Dynamics-Based Authentication
User-specific behavioral biometrics is widely used to increase login security. The usage of behavioral biometrics can support verification without bothering the user with a requirement of an additional interaction.
  • 553
  • 03 Nov 2023
Topic Review
Home-Based Rehabilitation (Shoulder) Using Auxiliary Systems and AI
Advancements in modern medicine have bolstered the usage of home-based rehabilitation services for patients, particularly those recovering from diseases or conditions that necessitate a structured rehabilitation process. Understanding the technological factors that can influence the efficacy of home-based rehabilitation is crucial for optimizing patient outcomes. As technologies continue to evolve rapidly, it is imperative to document the current state-of-the-art and elucidate the key features of the hardware and software employed in these rehabilitation systems.
  • 551
  • 15 Aug 2023
Topic Review
Enhanced Cross-Domain Named Entity Recognition
Cross-domain named entity recognition (NER) is a crucial task in various practical applications, particularly when faced with the challenge of limited data availability in target domains. Existing methodologies primarily depend on feature representation or model parameter sharing mechanisms to enable the transfer of entity recognition capabilities across domains. 
  • 551
  • 12 Jan 2024
Topic Review
Cross-Parallel Vision Transformers for Medical Image Segmentation
Medical image segmentation primarily utilizes a hybrid model consisting of a Convolutional Neural Network and sequential Transformers. The latter leverage multi-head self-attention mechanisms to achieve comprehensive global context modelling. However, despite their success in semantic segmentation, the feature extraction process is inefficient and demands more computational resources, which hinders the network’s robustness. To address this issue, this research presents two innovative methods: PTransUNet (PT model) and C-PTransUNet (C-PT model). The C-PT module refines the Vision Transformer by substituting a sequential design with a parallel one. This boosts the feature extraction capabilities of Multi-Head Self-Attention via self-correlated feature attention and channel feature interaction, while also streamlining the Feed-Forward Network to lower computational demands.
  • 550
  • 18 Dec 2023
Topic Review
Application of AI Techniques for Predicting Weather Conditions
Artificial Intelligence is the area of computing that studies intelligent entities and tries, through various techniques, to teach the computer to perform activities that previously only intelligent entities could perform. There are several approaches and ways of doing this, and one of the most used is Artificial Neural Networks. This entry presents a study on techniques for using Artificial Intelligence. Furthermore, it presents two works that use Recurrent Neural Networks and LSTM to predict weather conditions, providing an analysis of the solution proposed in each approach and a comparison between them.
  • 550
  • 26 Feb 2024
Topic Review
Tasks for Multimodal Federated Learning
Multimodal federated learning (MFL) offers many advantages, such as privacy preservation and addressing the data silo problem. However, it also faces limitations such as communication costs, data heterogeneity, and hardware disparities compared to centralized multimodal learning. Therefore, in addition to the unique challenges of modal heterogeneity, the original multimodal learning tasks become more challenging when performed within a federated learning framework.
  • 547
  • 16 Aug 2023
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.
  • 546
  • 21 Sep 2022
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