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Topic Review
Low-Cost Water Quality Sensors for IoT
In many countries, water quality monitoring is limited due to the high cost of logistics and professional equipment such as multiparametric probes. However, low-cost sensors integrated with the Internet of Things (IoT) can enable real-time environmental monitoring networks, providing valuable water quality information to the public.
  • 638
  • 06 May 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.
  • 330
  • 06 May 2023
Topic Review
Classification of Low Illumination Image Enhancement Methods
As a critical preprocessing technique, low-illumination image enhancement has a wide range of practical applications. It aims to improve the visual perception of a given image captured without sufficient illumination. Conventional low-illumination image enhancement methods are typically implemented by improving image brightness, enhancing image contrast, and suppressing image noise simultaneously. According to the learning method used, people can classify existing low-illumination enhancement methods into four categories, i.e., supervised learning, unsupervised learning, semi-supervised learning, and zero-shot learning methods.
  • 320
  • 06 May 2023
Topic Review
AI Applications in Plant Genomic Prediction
Artificial intelligence (AI), boosted through deep learning (DL), has achieved significant breakthroughs and is a powerful tool for managing large complex datasets such as crop genetic markers genome and their association with crop phenotypes. AI techniques can be applied to analyze large amounts of genomic data and identify patterns that are difficult for humans to detect. These patterns can then be used to develop more accurate predictive models. 
  • 320
  • 05 May 2023
Topic Review
Machine Learning in Healthcare Industry
Machine learning is a mechanism that enables machines to learn automatically without explicit programming. The main area of machine learning is to use advanced algorithms and statistical techniques to access the data and predict accuracy instead of a rule-based system. The dataset is a primary component of machine learning accuracy prediction. As a result, the data are more relevant and the prediction is more accurate. Machine learning has been used in different fields, such as finance, retail, and the healthcare industry. The rising use of machine learning in healthcare provides more opportunities for disease diagnosis and treatment. Machine learning has a great feature of continuous improvement for data accurate prediction and classification purposes for disease analysis.
  • 486
  • 05 May 2023
Topic Review
Moving Target Defense Techniques
Represented by reactive security defense mechanisms, cyber defense possesses a static, reactive, and deterministic nature, with overwhelmingly high costs to defend against ever-changing attackers. To change this situation, researchers have proposed moving target defense (MTD), which introduces the concept of an attack surface to define cyber defense in a brand-new manner, aiming to provide a dynamic, continuous, and proactive defense mechanism. With the increasing use of machine learning in networking, researchers have discovered that MTD techniques based on machine learning can provide omni-bearing defense capabilities and reduce defense costs at multiple levels. 
  • 427
  • 05 May 2023
Topic Review
Metaverse for Digital Anti-Aging Healthcare
Metaverse is the buzz technology of the moment raising attention both from academia and industry. Many stakeholders are considering an extension of their existing applications into the metaverse environment for more usability. The healthcare industry is gradually making use of the metaverse to improve quality of service and enhance living conditions. The convergence of artificial intelligence (AI), blockchain (BC), Internet of Things (IoT), immersive technologies, and digital twin in the metaverse environment presents new scopes for the healthcare industry. By leveraging these technologies, healthcare providers can improve patient outcomes, reduce healthcare costs, and create new healthcare experiences for a better life, thus facilitating the anti-aging process. AI can be used to analyze large-scale medical data and make personalized treatment plans, while blockchain can create a secure and transparent healthcare data ecosystem. 
  • 475
  • 05 May 2023
Topic Review
Convolutional Neural Network in Histopathology
Deep learning (DL) and convolutional neural networks (CNNs) have achieved state-of-the-art performance in many medical image analysis tasks. Histopathological images contain valuable information that can be used to diagnose diseases and create treatment plans. Therefore, the application of DL for the classification of histological images is a rapidly expanding field of research.
  • 628
  • 04 May 2023
Topic Review
Classification of Uncrewed Aerial Vehicles
Uncrewed aerial vehicles (UAVs), also known as drones, are ubiquitous and their use cases extend today from governmental applications to civil applications such as the agricultural, medical, and transport sectors, etc. In accordance with the requirements in terms of demand, it is possible to carry out various missions involving several types of UAVs as well as various onboard sensors. 
  • 5.6K
  • 04 May 2023
Topic Review
FamilyGuard
The residential environment is constantly evolving technologically. With this evolution, sensors have become intelligent interconnecting home appliances, personal computers, and mobile devices. Despite the benefits of this interaction, these devices are also prone to security threats and vulnerabilities. Ensuring the security of smart homes is challenging due to the heterogeneity of applications and protocols involved in this environment. This entry proposes the FamilyGuard architecture to add a new layer of security and simplify management of the home environment by detecting network traffic anomalies.
  • 331
  • 02 May 2023
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