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Topic Review
Mobile-Hypertensive Retinopathy
Hypertensive retinopathy (HR) is a serious eye disease that causes the retinal arteries to change. This change is mainly due to the fact of high blood pressure. Cotton wool patches, bleeding in the retina, and retinal artery constriction are affected lesions of HR symptoms.
  • 1.2K
  • 29 May 2023
Topic Review
Deep Learning in Water Leak Detection
The escalating global water usage and the increasing strain on major cities due to water shortages highlights the critical need for efficient water management practices. In water-stressed regions worldwide, significant water wastage is primarily attributed to leakages, inefficient use, and aging infrastructure. Undetected water leakages in buildings’ pipelines contribute to the water waste problem. 
  • 1.2K
  • 22 Nov 2023
Topic Review
Data-Driven Learning Methods for Network Intrusion Detection Systems
An effective anomaly-based intelligent IDS (AN-Intel-IDS) must detect both known and unknown attacks. Hence, there is a need to train AN-Intel-IDS using dynamically generated, real-time data in an adversarial setting. Furthermore, the lack of real-time data produces potentially biased models that are less effective in predicting unknown attacks. Therefore, training AN-Intel-IDS using imbalanced and adversarial learning is instrumental to their efficacy and high performance. Unfortunately, the public datasets available to train AN-Intel-IDS are ineluctably static, unrealistic, and prone to obsolescence. Furthermore, the lack of real-time data produces potentially biased models that are less effective in predicting unknown attacks. Therefore, training AN-Intel-IDS using imbalanced and adversarial learning is instrumental to their efficacy and high performance. 
  • 1.2K
  • 28 Feb 2022
Topic Review
Cloud Computing Failure Prediction
To date, despite the significant improvement in the performance of the hardware elements of the cloud infrastructure, the failure rate remains substantial. Moreover, the cloud is not as reliable as the cloud service providers, such as Amazon AWS and Ali Cloud, claimed, which is more than 99.9%. For example, multiple instances of failure have been reported, such as the failure of Amazon’s cloud data servers in early October 2012, which resulted in the collapse of Reddit, Airbnb, and Flipboard, the loss of Amazon AWS S3 on 28 February 2017, and the crash of Microsoft cloud services on 22 March 2017. Such failures show that cloud service providers are not as reliable as they claim.
  • 1.2K
  • 06 Apr 2022
Topic Review
Approaches of Automated Heart Disease Prediction
Cardiovascular diseases (CVDs) are the leading cause of death globally. Detecting this kind of disease represents the principal concern of many scientists, and techniques belonging to various fields have been developed to attain accurate predictions. 
  • 1.2K
  • 26 Oct 2023
Topic Review
Methods for Supervised Learning in Diagnosis of COVID-19
The methods for supervised learning in diagnosis of COVID-19 refer to the samples used for model training being labeled. The label information is fully utilized to guide network model training. The advantage is that the model accuracy can be effectively improved by learning a large amount of label information and the model is easy to evaluate. The current state of deep learning for COVID-19 classification and segmentation tasks from aspects of supervised learning is summarized, including summarizing the application of VGG, ResNet, DenseNet and lightweight networks to the classification task of COVID-19, and summarizing the application of the attention mechanism, multiscale mechanism, residual connectivity mechanism, and dense connectivity mechanism to the segmentation task of COVID-19.
  • 1.2K
  • 22 Mar 2023
Topic Review
The Dichotomy of Neural Networks and Cryptography
Neural networks and cryptographic schemes have come together in war and peace; a cross-impact that forms a dichotomy deserving a comprehensive review study. Neural networks can be used against cryptosystems; they can play roles in cryptanalysis and attacks against encryption algorithms and encrypted data. This side of the dichotomy can be interpreted as a war declared by neural networks. On the other hand, neural networks and cryptographic algorithms can mutually support each other. Neural networks can help improve the performance and the security of cryptosystems, and encryption techniques can support the confidentiality of neural networks. The latter side of the dichotomy can be referred to as the peace. 
  • 1.2K
  • 07 Jul 2022
Topic Review
Time-Series Forecasting Models
The time-series forecasting method is a suitable pricing solution for Digital Signage Advertising (DSA), as it improves the pricing decision by modeling the changes in the environmental factors and audience attention level toward signage for optimal pricing. However, it is difficult to determine an optimal price forecasting model for DSA with the increasing number of available time-series forecasting models in recent years. Based on the 84 research articles reviewed, the data characteristics analysis in terms of linearity, stationarity, volatility, and dataset size is helpful in determining the optimal model for time-series price forecasting.
  • 1.2K
  • 03 Nov 2021
Topic Review
Swarm Intelligence Based Load Balancing Techniques
Swarm Intelligence aims to combine relatively high approximate techniques to guide local optimization strategies in order to explore a solution space successfully and efficiently.
  • 1.1K
  • 28 Mar 2022
Topic Review
Oriented Crossover in Genetic Algorithms
A genetic algorithm is a formula for resolving optimization issues that incorporate a constraint and natural selection similar to the biological process that propels evolution.
  • 1.1K
  • 11 May 2023
Topic Review
Deep Learning Techniques in Fault Diagnosis and Prognosis
The fault diagnosis and prognosis (FDP) technique based on data-driven machine learning (ML) methods recognizes or learns the health features of the system from historical data, and tries to discover and mine the information hidden in the data, so that it can accurately analyze and predict future system behavior without precisely knowing the forward physical model.
  • 1.1K
  • 06 Feb 2023
Topic Review
Balanced Learning for Road Crack Segmentation
Road crack segmentation based on high-resolution images is an important task in road service maintenance. The undamaged road surface area is much larger than the damaged area on a highway. This imbalanced situation yields poor road crack segmentation performance for convolutional neural networks.
  • 1.1K
  • 22 Jul 2022
Topic Review
Simulate Gene Expression and Infer Gene Regulatory Networks
The ability to simulate gene expression and infer gene regulatory networks has vast potential applications in various fields, including medicine, agriculture, and environmental science. Machine learning approaches to simulate gene expression and infer gene regulatory networks have gained significant attention as a promising area of research.
  • 1.1K
  • 30 Aug 2023
Topic Review
AUV Adaptive Sampling Methods
Autonomous underwater vehicles (AUVs) are unmanned marine robots that have been used for a broad range of oceanographic missions. They are programmed to perform at various levels of autonomy, including autonomous behaviours and intelligent behaviours. Adaptive sampling is one class of intelligent behaviour that allows the vehicle to autonomously make decisions during a mission in response to environment changes and vehicle state changes. Having a closed-loop control architecture, an AUV can perceive the environment, interpret the data and take follow-up measures. Thus, the mission plan can be modified, sampling criteria can be adjusted, and target features can be traced.
  • 1.1K
  • 12 Nov 2020
Topic Review
Real-Time Vehicle Detection Based on YOLOv5
An improved YOLOv5 model is used to detect vehicles in aerial images, which effectively enhances the detection performance of tiny objects and obscured vehicles.
  • 1.1K
  • 30 Jun 2023
Topic Review
Sustainable Food Production
Fault diagnosis and prognosis methods are the most useful tools for risk and reliability analysis in food processing systems. Proactive diagnosis techniques such as failure mode and effect analysis (FMEA) are important for detecting all probable failures and facilitating the risk analysis process. However, significant uncertainties exist in the classical-FMEA when it comes to ranking the risk priority numbers (RPNs) of failure modes. Such uncertainties may have an impact on the food sector’s operational safety and maintenance decisions.
  • 1.1K
  • 28 Mar 2022
Topic Review
Contextual Route Recommendation System
The traffic composition in developing countries comprises of variety of vehicles which include cars, buses, trucks, and motorcycles. Motorcycles dominate the road with 77.5% compared to other types. Meanwhile, route recommendation such as navigation and Advanced Driver Assistance Systems (ADAS) is limited to particular vehicles only. Traffic condition prediction aims to discuss the proper method to result a better prediction analysis. Route recommendation aims to explore the existing work on how to provide the best route for users. The two domains would be the parts of our framework to result contextual route recommendations in heterogeneous traffic flow.
  • 1.1K
  • 28 Mar 2022
Topic Review
Light Field Image Super-Resolution
Light fields play important roles in industry, including in 3D mapping, virtual reality and other fields. However, as a kind of high-latitude data, light field images are difficult to acquire and store. Compared with traditional 2D planar images, 4D light field images contain information from different angles in the scene, and thus the super-resolution of light field images needs to be performed not only in the spatial domain but also in the angular domain. In the early days of light field super-resolution research, many solutions for 2D image super-resolution, such as Gaussian models and sparse representations, were also used in light field super-resolution. With the development of deep learning, light field image super-resolution solutions based on deep-learning techniques are becoming increasingly common and are gradually replacing traditional methods.
  • 1.1K
  • 27 Jul 2022
Topic Review
Remote Keyless Using Pre-Trained Deep Neural Network
Keyless systems have replaced the old-fashioned methods of inserting physical keys into keyholes to unlock the door, which are inconvenient and easily exploited by threat actors. Keyless systems use the technology of radio frequency (RF) as an interface to transmit signals from the key fob to the vehicle.
  • 1.1K
  • 10 Nov 2022
Topic Review
Machine Learning Used to Combat COVID-19
Coronavirus disease (COVID-19) has had a significant impact on global health since the start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed worldwide with over 6.3 million deaths as a result. Artificial Intelligence (AI) solutions such as machine learning and deep learning have played a major part in this pandemic for the diagnosis and treatment of COVID-19.
  • 1.1K
  • 20 Sep 2022
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