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Topic Review
Orientation Detection Mechanism Based on Artificial Visual System
As an important part of the nervous system, the human visual system can provide visual perception for humans. The research on it is of great significance to improve our understanding of biological vision and the human brain. Orientation detection, in which visual cortex neurons respond only to linear stimuli in specific orientations, is an important driving force in computer vision and biological vision. However, the principle of orientation detection is still unknown. 
  • 398
  • 18 Jan 2022
Topic Review
Vision-Based Human Action Recognition Field
Artificial intelligence’s rapid advancement has enabled various applications, including intelligent video surveillance systems, assisted living, and human–computer interaction. These applications often require one core task: video-based human action recognition.
  • 398
  • 23 Apr 2023
Topic Review
Machine Learning-Based Anomaly Detection in NFV
Network function virtualization (NFV) is a rapidly growing technology that enables the virtualization of traditional network hardware components, offering benefits such as cost reduction, increased flexibility, and efficient resource utilization. Moreover, NFV plays a crucial role in sensor and IoT networks by ensuring optimal resource usage and effective network management. 
  • 398
  • 15 Jun 2023
Topic Review
Cross-Domain Sentiment Analysis in IoT
Social media is a real-time social sensor to sense and collect diverse information, which can be combined with sentiment analysis to help IoT sensors provide user-demanded favorable data in smart systems. In the case of insufficient data labels, cross-domain sentiment analysis aims to transfer knowledge from the source domain with rich labels to the target domain that lacks labels. Most domain adaptation sentiment analysis methods achieve transfer learning by reducing the domain differences between the source and target domains, but little attention is paid to the negative transfer problem caused by invalid source domains. 
  • 398
  • 01 Sep 2023
Topic Review
J48SS
Interpretable decision tree model based on C4.5 capable of seamlessly using numerical, categorical, sequential, and time series information for classification purposes.
  • 398
  • 15 Apr 2021
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.
  • 396
  • 06 May 2023
Topic Review
AI-Driven Sentiment Analysis of Amazon Reviews Using BERT
Understanding customer emotions and preferences is paramount for success in the dynamic product design landscape. The pre-trained Bidirectional Encoder Representation from Transformers (BERT) model and the Text-to-Text Transfer Transformer (T5) are deployed to predict customer emotions. These models were trained on synthetically generated and manually labeled datasets to detect the specific features from review data, then sentiment analysis was performed to classify the data into positive, negative, and neutral reviews concerning their aspects. 
  • 396
  • 17 Feb 2024
Topic Review
Home-Based Devices for Detecting Obstructive Sleep Apnea
Obstructive Sleep Apnea (OSA) is a respiratory disorder characterized by frequent breathing pauses during sleep. The apnea–hypopnea index is a measure used to assess the severity of sleep apnea and the hourly rate of respiratory events. Despite numerous commercial devices available for apnea diagnosis and early detection, accessibility remains challenging for the general population, leading to lengthy wait times in sleep clinics. Consequently, research on monitoring and predicting OSA has surged. 
  • 395
  • 20 Feb 2024
Topic Review
Class Imbalance Problem in Credit Risk Prediction
Credit, as defined by financial institutions such as banks and lending companies, represents a vital loan certificate issued to individuals or businesses. This certification mechanism plays a pivotal role in ensuring the smooth functioning of the financial sector, contingent upon comprehensive evaluations of creditworthiness.
  • 395
  • 18 Mar 2024
Topic Review
Human Action Recognition Methods for Single-Modality Action Recognition
Human action recognition is widely used in computer vision research, such as intelligent video surveillance, intelligent human–computer interaction, robot control, video retrieval, pose estimation, and many other fields. Since the environments faced by human action recognition are diverse and complex, capturing effective features for action recognition is still a challenging problem.
  • 394
  • 19 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. 
  • 394
  • 22 Nov 2023
Topic Review
Opium Poppy Detection in Unmanned Aerial Vehicle Imagery
Opium poppy is a medicinal plant, and its cultivation is illegal without legal approval in China. Unmanned aerial vehicle (UAV) is an effective tool for monitoring illegal poppy cultivation. Unmanned aerial vehicle (UAV) is more flexible and mobile than remote sensing satellite, and their high-resolution images can help to detect poppies in areas that are hard to see. 
  • 392
  • 18 Feb 2024
Topic Review
Remote Health Monitoring Systems for Elderly People
Remote Health Monitoring Systems (RHMS) can manage, maintain and monitor a specific set of tasks efficiently over a network with reduced cost and errors. Wearable sensors and vision-based sensors detect any abnormalities in the patient’s behavior, prompting immediate action from caregivers or doctors, enabling them to take necessary measures promptly to address the situation.
  • 391
  • 16 Aug 2023
Topic Review
Deep Learning Architectures for Multivariate Time-Series Forecasting
Deep learning algorithms, renowned for their ability to extract intricate patterns from complex datasets, have proven particularly adept at handling the multifaceted time-series data characteristic of smart city IoT applications. Deep learning architectures model complex relationships through a series of nonlinear layers—the set of nodes of each intermediate layer capturing the corresponding feature representation of the input.
  • 391
  • 27 Oct 2023
Topic Review
IDS Using Feature Extraction with ML in IoT
With the continuous increase in Internet of Things (IoT) device usage, more interest has been shown in internet security, specifically focusing on protecting these vulnerable devices from malicious traffic. Such threats are difficult to distinguish, so an advanced intrusion detection system (IDS) is becoming necessary. Machine learning (ML) is one of the promising techniques as a smart IDS in different areas, including IoT. However, the input to ML models should be extracted from the IoT environment by feature extraction models, which play a significant role in the detection rate and accuracy.
  • 391
  • 22 Nov 2023
Topic Review
Multitask-based Shared Feature Learning
Speech emotion recognition (SER), a rapidly evolving task that aims to recognize the emotion of speakers, has become a key research area in affective computing. Various languages in multilingual natural scenarios extremely challenge the generalization ability of SER, causing the model performance to decrease quickly, and driving researchers to ask how to improve the performance of multilingual SER. To solve this problem, an explainable Multitask-based Shared Feature Learning (MSFL) model is proposed for multilingual SER. The introduction of multi-task learning (MTL) can provide related task information of language recognition for MSFL, improve its generalization in multilingual situations, and further lay the foundation for learning MSFs.
  • 390
  • 11 Jan 2023
Topic Review
Unique Properties of the Immune System
The human body is unquestionably one of the most complex systems known to humanity. There are three main regulation systems in the human body (the nervous system, the endocrine system and the immune system). These three systems are integrated into one ultimate information communication network within the human body. However, each regulation system has its specific roles and unique properties. Consequently, each of these regulation systems has served as inspiration for computational models to efficiently solve real-world problems. An overview of these models and their applications is presented.
  • 390
  • 01 Feb 2023
Topic Review
Equilibrium Optimizer Algorithm
The equilibrium optimizer (EO) is a recently developed physics-based optimization technique for complex optimization problems.
  • 390
  • 04 Sep 2023
Topic Review
Cube Surface Light Field Representation
The core idea of the cube surface light field representation is to parameterize the light rays on the two intersections with the cube surface and use the color value at the first intersection of the light ray and the object's surface to be the color of this light ray, constructing a pure ray-based 4D light field representation of the scenes.
  • 389
  • 01 Aug 2022
Topic Review
Single-Agent Reinforcement Learning and Multi-Agent Reinforcement Learning
Flexible job shop scheduling (FJSP) is regarded as an effective measure to deal with the challenge of mass personalized and customized manufacturing in the era of Industry 4.0, and is widely extended to many real applications. Single-Agent Reinforcement Learning (SARL) is the algorithm only contains one agent that makes all the decisions for a control system. Multi-Agent Reinforcement Learning (MARL) is the algorithm comprises multiple agents that interact with the environment through their respective policies.
  • 389
  • 08 Jan 2024
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