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Topic Review
AMC Using Residual Learning and Squeeze–Excitation Blocks
Automatic modulation classification (AMC) is a vital process in wireless communication systems that is fundamentally a classification problem. It is employed to automatically determine the type of modulation of a received signal. Deep learning (DL) methods have gained popularity in addressing the problem of modulation classification, as they automatically learn the features without needing technical expertise.
  • 322
  • 10 Oct 2023
Topic Review
Traffic Pattern in Smart Cities
Smart cities have large-scale infrastructures that have been developed to monitor a wide variety of urban occurrences. This is done to improve the quality of urban life. In most instances, they place a very restricted and specific emphasis on (e.g., monitoring the traffic). They are expensive, need the management of specialists, and are not universally well-liked among residents since they focus on topics that are not (often) of public importance. 
  • 321
  • 23 Oct 2023
Topic Review
Semantic Change Detection for High Resolution RS Images
Change detection in high resolution (HR) remote sensing images faces more challenges than in low resolution images because of the variations of land features, which prompts research on faster and more accurate change detection methods. 
  • 321
  • 22 Dec 2023
Topic Review
Challenge of  UAV-Based Vehicle Re-Identification
Vehicle re-identification research under surveillance cameras has yielded impressive results. However, the challenge of unmanned aerial vehicle (UAV)-based vehicle re-identification (ReID) presents a high degree of flexibility, mainly due to complicated shooting angles, occlusions, low discrimination of top–down features, and significant changes in vehicle scales. 
  • 320
  • 06 Nov 2023
Topic Review
Predicting an Optimal Medication/Prescription Regimen Using Multi-Output Models
The discordant chronic comorbidities care (DC33) model shows how a change in a patient treatment plan can negatively impact symptoms and necessitate revisiting the plan. These interactions make treatment decisions, prioritization, and adherence for DCCs very complex and challenging for patients and their healthcare providers.
  • 320
  • 23 Jan 2024
Topic Review
Distributed Bayesian Inference for Large-Scale IoT Systems
The Internet of Things (IoT) has emerged as a transformative force in contemporary society, substantially impacting various facets of daily life. Nevertheless, the IoT ecosystem’s rapid expansion is accompanied by a significant increase in data generation, known as Big Data. This expansion presents a complex challenge, necessitating advanced, scalable, and efficient data processing techniques. Given the complex nature of large-scale data analysis in IoT systems, distributed Bayesian inference arises as a practical and efficient solution in this domain. Bayesian methods, which are influential in deriving informed conclusions and predictions from complex datasets, are widely recognized for their probabilistic underpinnings.
  • 319
  • 28 Dec 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. 
  • 318
  • 11 Jan 2023
Topic Review
Arabic Mispronunciation Recognition System Using LSTM Network
The widespread use of CALL (computer-assisted language learning) systems attests to their success in helping people improve their language and speech skills. CALL is predominantly concerned with addressing pronunciation errors in non-native speakers’ speech. Accurate mispronunciation detection, voice recognition, and accurate pronunciation evaluation are all activities that may be accomplished with CALL.
  • 318
  • 05 Sep 2023
Topic Review
Adversarial Attacks in Camera-Based Vision Systems
Vision-based perception modules are increasingly deployed in many applications, especially autonomous vehicles and intelligent robots. These modules are being used to acquire information about the surroundings and identify obstacles. Hence, accurate detection and classification are essential to reach appropriate decisions and take appropriate and safe actions at all times. Adversarial attacks can be categorized into digital and physical attacks.
  • 318
  • 11 Dec 2023
Topic Review
Reinforcement Learning, Knowledge Distillation, and Channel Pruning
The methods used for model compression and acceleration are primarily divided into five categories—network pruning, parameter quantization, low-rank decomposition, lightweight network design, and knowledge distillation—such that the scope of actions and design ideas for each method are different.
  • 318
  • 12 Dec 2023
Topic Review
Document-Level Multimodal Sentiment Analysis
An increasing number of people tend to convey their opinions in different modalities. For the purpose of opinion mining, sentiment classification based on multimodal data becomes a major focus. Sentiment analysis at the document level aims to identify the opinion on a main topic expressed by a whole document.
  • 317
  • 01 Jun 2023
Topic Review
Deep Learning for Alzheimer’s Disease
Alzheimer’s and related diseases are significant health issues of this era. The interdisciplinary use of deep learning in this field has shown great promise and gathered considerable interest. 
  • 317
  • 25 Jun 2023
Topic Review
An AI-Based Framework for Translating American Sign Language
Communication is an essential part of life, without which life would be very difficult. Each living being in the world communicates in their own way. American Sign Language (ASL) is a sign language used by deaf and hearing impaired people in the United States and Canada, devised in part by Thomas Hopkins Gallaudet and Laurent Clerc based on sign language in France.
  • 317
  • 31 Oct 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.
  • 317
  • 26 Feb 2024
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.
  • 315
  • 03 Nov 2023
Topic Review
Logical Reasoning Machine Reading Comperhension
Logical reasoning requires correct understanding of the logical relationships between different sentences, pointing out a positive example that enhances the reliability of a conclusion or a negative example that weakens the reliability of a conclusion. The need for this capability places higher demands on the performance of existing reading comprehension models since the inference capability of a large number of models relies heavily on entities and their numerical weights. 
  • 315
  • 22 Dec 2023
Topic Review
Deep-Learning and Privacy Techniques for Data-Driven Soft Sensors
The continuously increasing number of mobile devices actively being used in the world amounted to approximately 6.8 billion by 2022. Consequently, this implies a substantial increase in the amount of personal data collected, transported, processed, and stored. An integrated personal health data management system was designed and implemented, which considers data-driven software and hardware sensors, comprehensive data privacy techniques, and machine-learning-based algorithmic models. 
  • 314
  • 13 Mar 2023
Topic Review
Applications of Blockchain-Based Federated Learning
Federated learning (FL) and blockchains exhibit significant commonality, complementarity, and alignment in various aspects, such as application domains, architectural features, and privacy protection mechanisms. Blockchain-based federated learning (BFL) has gained the capability and prospects for applications in highly privacy-sensitive industries. 
  • 314
  • 08 Mar 2024
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.
  • 314
  • 23 Aug 2023
Topic Review
Enhancing Ensemble Learning Using CNN for Spoof Fingerprints
Convolutional Neural Networks (CNNs) have demonstrated remarkable success with great accuracy in classification problems. Using an ensemble of neural networks offers a simple yet effective measure to improve performance and robustness beyond that of a single network.
  • 313
  • 18 Jan 2024
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