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Topic Review
Surrogate-Based Optimisation
Surrogate-based optimisation (SBO) algorithms are a powerful technique that combine machine learning and optimisation to solve expensive optimisation problems. This type of problem appears when dealing with computationally expensive simulators or algorithms. By approximating the expensive part of the optimisation problem with a surrogate, the number of expensive function evaluations can be reduced.
  • 1.1K
  • 31 Mar 2022
Topic Review
Reinforcement Learning in Ad Hoc Vehicular Networks
Ad hoc vehicular networks have been identified as a suitable technology for intelligent communication amongst smart city stakeholders as the intelligent transportation system has progressed. In a highly mobile area, the growing usage of wireless technologies creates a challenging context. To increase communication reliability in this environment, it is necessary to use intelligent tools to solve the routing problem to create a more stable communication system. Reinforcement Learning (RL) is an excellent tool to solve this problem. 
  • 1.1K
  • 01 Jul 2022
Topic Review
Vision-Based Gait Recognition
Identifying people’s identity by using behavioral biometrics has attracted many researchers’ attention in the biometrics industry. Gait is a behavioral trait, whereby an individual is identified based on their walking style. Over the years, gait recognition has been performed by using handcrafted approaches. Due to several covariates’ effects, the competence of the approach has been compromised. Deep learning is an emerging algorithm in the biometrics field, which has the capability to tackle the covariates and produce highly accurate results. 
  • 1.1K
  • 12 Aug 2022
Topic Review
Coronavirus
Coronaviruses are indeed a huge family of viruses that are found both in humans and animals. Seven different types have been identified, including the ones that caused COVID-19 and the SARS and MERS illnesses.
  • 1.1K
  • 09 Nov 2022
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.
  • 1.1K
  • 06 May 2023
Topic Review
Random Forest, Feedforward Neural Network, GRU and FinGAT
Stock prediction has garnered considerable attention among investors, with a recent focus on the application of machine learning techniques to enhance predictive accuracy. Prior research has established the effectiveness of machine learning in forecasting stock market trends, irrespective of the analytical approach employed, be it technical, fundamental, or sentiment analysis. 
  • 1.1K
  • 18 Dec 2023
Topic Review
3D Object Detection with Differential Point Clouds
3D object detection based on point clouds has many applications in natural scenes, especially in autonomous driving. Point cloud data provide reliable geometric and depth information. 
  • 1.1K
  • 24 Dec 2022
Topic Review
Intelligent Question Answering System
Intelligent question answering system is an innovative information service system which integrates natural language processing, information retrieval, semantic analysis and artificial intelligence. The system mainly consists of three core parts, which are question analysis, information retrieval and answer extraction. Through these three parts, the system can provide users with accurate, fast and convenient answering services.
  • 1.1K
  • 20 Aug 2024
Topic Review
Self-Healing in Cyber–Physical Systems Using Machine Learning
The rapid advancement of networking, computing, sensing, and control systems has introduced a wide range of cyber threats, including those from new devices deployed during the development of scenarios. With advancements in automobiles, medical devices, smart industrial systems, and other technologies, system failures resulting from external attacks or internal process malfunctions are increasingly common. Restoring the system’s stable state requires autonomous intervention through the self-healing process to maintain service quality.
  • 1.1K
  • 12 Oct 2023
Topic Review
Sustainability, Digital Technologies and the Circular Economy
The textile and clothing (T&C) industry is not usually viewed as an exemplar of sustainable development and the circular economy (CE), as the industry has hitherto developed its products in a linear fashion, with relatively little recycling of the finished goods. 
  • 1.1K
  • 03 Jul 2023
Topic Review
Deep Neural Networks
The fundamental principles and structures of deep learning (DL) are examined herein. The specific roles and functions of the diverse layers that make up deep networks are discussed, and the importance of evaluation metrics, which serve as crucial tools for gauging the effectiveness of these models, are emphasized. Commonly used architectures in medical image segmentation are also introduced.
  • 1.1K
  • 29 Nov 2023
Topic Review
Deep Reinforcement Learning for Vision-Based Navigation of UAVs
Unmanned Aerial Vehicles (UAVs), also known as drones, have advanced greatly in recent years. There are many ways in which drones can be used, including transportation, photography, climate monitoring, and disaster relief. The reason for this is their high level of efficiency and safety in all operations. While the design of drones strives for perfection, it is not yet flawless. When it comes to detecting and preventing collisions, drones still face many challenges. In this context, this research describes a methodology for developing a drone system that operates autonomously without the need for human intervention. This research applies reinforcement learning algorithms to train a drone to avoid obstacles autonomously in discrete and continuous action spaces based solely on image data. The research compare three different reinforcement learning strategies—namely, Deep Q-Networks (DQN), Proximal Policy Optimization (PPO), and Soft Actor-Critic (SAC)—that can assist in avoiding obstacles, both stationary and moving The novelty of this research lies in its comprehensive assessment of the advantages, limitations, and future research directions of obstacle detection and avoidance for drones, using different reinforcement learning techniques. The findings could have practical implications for the development of safer and more efficient drones in the future.
  • 1.1K
  • 13 Dec 2023
Topic Review
Corpus Statistics Empowered Document Classification
In natural language processing (NLP), document classification is an important task that relies on the proper thematic representation of the documents. Gaussian mixture-based clustering is widespread for capturing rich thematic semantics but ignores emphasizing potential terms in the corpus. Moreover, the soft clustering approach causes long-tail noise by putting every word into every cluster, which affects the natural thematic representation of documents and their proper classification. It is more challenging to capture semantic insights when dealing with short-length documents where word co-occurrence information is limited.
  • 1.1K
  • 05 Aug 2022
Topic Review
Arbitrary-Oriented Object Detection in Aerial Images
Objects in aerial images often have arbitrary orientations and variable shapes and sizes. As a result, accurate and robust object detection in aerial images is a challenging problem. 
  • 1.0K
  • 24 May 2023
Topic Review
Dynamic Fault Tree analysis method
The Entry briefly introduces the Dynamic Fault Tree analysis method proposed by P. Gao et al on the 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC).
  • 1.0K
  • 04 Apr 2022
Topic Review
Predictive Maintenance of Ball Bearing Systems
In the era of Industry 4.0 and beyond, ball bearings remain an important part of industrial systems. The failure of ball bearings can lead to plant downtime, inefficient operations, and significant maintenance expenses.
  • 1.0K
  • 01 Feb 2024
Topic Review
Obfuscated Memory Malware Detection
Obfuscated Memory Malware (OMM) presents significant threats to interconnected systems, including smart city applications, for its ability to evade detection through concealment tactics. Existing OMM detection methods primarily focus on binary detection. 
  • 1.0K
  • 24 Jul 2023
Topic Review
Artificial Intelligence Challenges
Artificial intelligence (AI) has been widely used in recent years. During analyses of the challenges of AI, numerous problems have been reported, some of which are security, safety, fairness, energy consumption, and ethics, to mention a few. The widespread usage of AI leads to arising new challenges.
  • 1.0K
  • 05 May 2022
Topic Review
The Methods of Fall Detection
Falls by an older person are a significant public health issue because they can result in disabling fractures and cause severe psychological problems that diminish a person’s level of independence. Falls can be fatal, particularly for the elderly. Fall Detection Systems (FDS) are automated systems designed to detect falls experienced by older adults or individuals. Early or real-time detection of falls may reduce the risk of major problems.
  • 1.0K
  • 09 Jun 2023
Topic Review
Carbonate Reservoirs Permeability Prediction
Permeability is a crucial property that can be used to indicate whether a material can hold fluids or not. Predicting the permeability of carbonate reservoirs is always a challenging and expensive task while using traditional techniques. Traditional methods often demand a significant amount of time, resources, and manpower, which are sometimes beyond the limitations of under developing countries.
  • 1.0K
  • 10 Oct 2023
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