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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. 
  • 553
  • 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.
  • 552
  • 03 Jul 2023
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. 
  • 549
  • 11 Jan 2023
Topic Review
Convolutional Neural Networks Applied to Face Mask Classification
The preventive measures taken to curb the spread of COVID-19 have emphasized the importance of wearing face masks to prevent potential infection with serious diseases during daily activities or for medical professionals working in hospitals. Due to the mandatory use of face masks, various methods employing artificial intelligence and deep learning have emerged to detect whether individuals are wearing masks.
  • 549
  • 24 Jan 2024
Topic Review
Imaging Techniques Used in Fish Bioimages
Detecting skeletal or bone-related deformities in model and aquaculture fish is vital for numerous biomedical studies. In biomedical research, model fish with bone-related disorders are potential indicators of various chemically induced toxins in their environment or poor dietary conditions. In aquaculture, skeletal deformities are affecting fish health, and economic losses are incurred by fish farmers. 
  • 548
  • 09 Jan 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.
  • 546
  • 01 Sep 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.
  • 546
  • 03 Nov 2023
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.
  • 544
  • 16 Nov 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.
  • 544
  • 26 Feb 2024
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.
  • 543
  • 15 Aug 2023
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.
  • 543
  • 16 Aug 2023
Topic Review
Alan Mathison Turing
Alan Mathison Turing was a British mathematician, logician, cryptanalyst, and theoretical biologist whose groundbreaking work laid the foundations of modern computer science and artificial intelligence. He is best known for conceptualizing the Turing machine, a formal model of computation, and for his crucial role in deciphering the German Enigma code during World War II. His legacy extends across the fields of mathematics, cognitive science, and the philosophy of mind, and he is widely regarded as one of the most influential thinkers of the twentieth century.
  • 542
  • 23 Jun 2025
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.
  • 539
  • 25 Dec 2023
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.
  • 538
  • 01 Feb 2024
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. 
  • 535
  • 24 Jun 2022
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.
  • 535
  • 18 Dec 2023
Topic Review
Soybean Monitoring and Management
The interest in deep learning in agriculture has been continuously growing since the inception of this type of technique in the early 2010s. Soybeans, being one of the most important agricultural commodities, has frequently been the target of efforts in this regard. It can be challenging to keep track of a constantly evolving state of the art.
  • 533
  • 23 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. 
  • 533
  • 12 Jan 2024
Topic Review
Higher Accuracy in YOLO Detection for Vehicle Inspection
Against the backdrop of ongoing urbanization, issues such as traffic congestion and accidents are assuming heightened prominence, necessitating urgent and practical interventions to enhance the efficiency and safety of transportation systems. A paramount challenge lies in realizing real-time vehicle monitoring, flow management, and traffic safety control within the transportation infrastructure to mitigate congestion, optimize road utilization, and curb traffic accidents.
  • 529
  • 22 Dec 2023
Topic Review
UNet and Conventional DL Systems for CAD
The ability of UNet-based deep learning models as shown before is very powerful in the imaging domain and can handle image noise, structure, scale, size, resolution, and further, the variability in the shapes.
  • 529
  • 22 Dec 2023
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