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Topic Review
A Unified Framework for RGB-Infrared Transfer
Infrared(IR) images (both 0.7-3 µm and 8-15 µm) offer radiation intensity texture information that visible images lack, making them particularly helpful in daytime, nighttime, and complex scenes. Many researchers are studying how to translate RGB images into infrared images for deep learning-based visual tasks such as object tracking, crowd counting, panoramic segmentation, and image fusion in urban scenarios. The utilization of the RGB-IR dataset in the aforementioned tasks holds the potential to provide comprehensive multi-band fusion data for urban scenes, thereby facilitating precise modeling across different scenarios. In addressing the challenge of accurately generating high-radiance textures for the targets in the infrared spectrum, the proposed approach aims to ensure alignment between the generated infrared images and the radiation feature of ground-truth IR images.
  • 330
  • 18 Dec 2023
Topic Review
INtra-INter Spectral Attention Network for Pedestrian Detection
Pedestrian detection is a critical task for safety-critical systems, but detecting pedestrians is challenging in low-light and adverse weather conditions. Thermal images can be used to improve robustness by providing complementary information to RGB images.
  • 330
  • 04 Mar 2024
Topic Review
Learning Individualized Hyperparameter Settings
The performance of optimization algorithms, and consequently of AI/machine learning solutions, is strongly influenced by the setting of their hyperparameters. Over the last decades, a rich literature has developed proposing methods to automatically determine the parameter setting for a problem of interest, aiming at either robust or instance-specific settings. Robust setting optimization is already a mature area of research, while instance-level setting is still in its infancy, with contributions mainly dealing with algorithm selection.
  • 329
  • 03 Jul 2023
Topic Review
Artificial Intelligence and Photovoltaic Fault
The global transition to sustainable energy has positioned photovoltaic (PV) systems at the top of renewable energy solutions. Photovoltaic (PV) fault detection is crucial because undetected PV faults can lead to significant energy losses, with some cases experiencing losses of up to 10%. The efficiency of PV systems depends upon the reliable detection and diagnosis of faults. The integration of Artificial Intelligence (AI) techniques has been a growing trend in addressing these issues. 
  • 329
  • 20 Nov 2023
Topic Review
Integration of Deep Learning into the IoT
The internet of things (IoT) has emerged as a pivotal technological paradigm facilitating interconnected and intelligent devices across multifarious domains. The proliferation of IoT devices has resulted in an unprecedented surge of data, presenting formidable challenges concerning efficient processing, meaningful analysis, and informed decision making. Deep-learning (DL) methodologies, notably convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep-belief networks (DBNs), have demonstrated significant efficacy in mitigating these challenges by furnishing robust tools for learning and extraction of insights from vast and diverse IoT-generated data.
  • 329
  • 19 Dec 2023
Topic Review
Color Image Denoising Methods for Impulse Noise
One of the most critical tasks in computer vision applications is image denoising, which involves recovering an image from a degraded noisy version. Impulse noise in digital images is a random variation in the intensity of pixels caused by short-duration pulses of high energy. This type of noise can significantly degrade the quality of images and poses various challenges in real-world applications. 
  • 329
  • 09 Jan 2024
Topic Review
Severity Identification of Parkinson’s Disease
Disease severity identification using computational intelligence-based approaches is gaining popularity nowadays. Movement disorders caused by PD may not remain the same in different patients. Thus, it is essential to develop an automated tool to evaluate a patient’s gait.
  • 328
  • 14 Apr 2023
Topic Review
Deep Learning Methods of Small Object Detection
Remote sensing methodology has been increasingly applied in fields such as forest fire detection, iceberg detection, ship detection, floating object detection, and agriculture monitoring. Synthetic aperture radar (SAR) images can be used to construct two-dimensional images, which can be further reconstructed into multidimensional images if necessary. When the SAR focuses on the target application, such as biomass detection in the forest, ship detection in the ocean, and vehicle count on land, it comprises many small objects. Detecting these small images is less effortless than general object detection in typical images.
  • 328
  • 14 Jul 2023
Topic Review
Zero-Trust Marine Cyberdefense for IoT-Based Communications
Integrating Explainable Artificial Intelligence (XAI) into marine cyberdefense systems can address the lack of trustworthiness and low interpretability inherent in complex black-box Network Intrusion Detection Systems (NIDS) models. XAI has emerged as a pivotal focus in achieving a zero-trust cybersecurity strategy within marine communication networks. 
  • 328
  • 31 Jan 2024
Topic Review
Risk Traceability Using Blockchain Technology
Regulatory authorities, consumers, and producers alike are alarmed by the issue of food safety, which is a matter of international concern. The conventional approaches utilized in food quality management demonstrate deficiencies in their capacity to sufficiently address issues related to traceability, transparency, and accountability. The emergence of blockchain technology (BCT) has provided a feasible approach to tackle the challenge of regulating food safety. 
  • 327
  • 22 Nov 2023
Topic Review
Data Mining Techniques for Students’ Performance Predictive Analysis
The utilization of data mining techniques for the prompt prediction of academic success has gained significant importance in the current era. There is an increasing interest in utilizing these methodologies to forecast the academic performance of students, thereby facilitating educators to intervene and furnish suitable assistance when required.
  • 327
  • 22 Dec 2023
Topic Review
Optimizing Session-Aware Recommenders
Recommendation mechanisms have emerged as vital tools for the filtering of information in various aspects of life. They are widely used in commercial platforms, including e-commerce sites like Amazon. Session-based or session-aware recommendation is more attractive due to the recommendation accuracy.
  • 327
  • 26 Feb 2024
Topic Review
Authentication Methods for Mobile Device Users
With the advent of smart mobile devices, end users get used to transmitting and storing their individual privacy in them, which, however, has aroused prominent security concerns inevitably. Numerous researchers have primarily proposed to utilize motion sensors to explore implicit authentication techniques. 
  • 326
  • 14 Sep 2023
Topic Review
Text Generation Models and Imbalanced Sentiment Analysis
The significance of sentiment analysis has extended across a wide range of fields, finding extensive use in various applications. As digital communication continues to expand, the ability of sentiment analysis to interpret complex human emotions and opinions becomes increasingly important, proving invaluable in fields ranging from social sciences to customer service and beyond. In this era of increasing digitization, leveraging the power of data through sentiment analysis offers unique insights, making significant contributions to sectors such as those previously summarized in various studies, namely, healthcare, social policy, e-commerce, and digital humanities.
  • 326
  • 18 Sep 2023
Topic Review
Federated Learning Based on Deep Reinforcement Learning
Federated learning (FL) is a distributed machine learning paradigm that enables a large number of clients to collaboratively train models without sharing data.
  • 325
  • 24 Nov 2023
Topic Review
Building Footprint Extraction in Very-High-Resolution Remote Sensing Images
With the rapid development of very-high-resolution (VHR) remote-sensing technology, automatic identification and extraction of building footprints are significant for tracking urban development and evolution. Nevertheless, while VHR can more accurately characterize the details of buildings, it also inevitably enhances the background interference and noise information, which degrades the fine-grained detection of building footprints. In order to tackle the above issues, the attention mechanism is intensively exploited to provide a feasible solution. The attention mechanism is a computational intelligence technique inspired by the biological vision system capable of rapidly and automatically catching critical information.
  • 325
  • 27 Nov 2023
Topic Review
ISTD Based on Background-SuppressionProximal Gradient and GPU Acceleration
Infrared Small-Target Detection (ISTD) is an important component of infrared search and tracking, aiming to exploit the thermal radiation difference between a target and its background to achieve long-range target detection. According to the definition by the Society of Photo-Optical Instrumentation Engineers (SPIE), small targets typically refers to objects in a 256 × 256 image with an area of fewer than 80 pixels, accounting for approximately 0.12% of the total image area.
  • 324
  • 25 Dec 2023
Topic Review
Quantization Methods of  Defense against Membership Inference Attacks
Machine learning deployment on edge devices has faced challenges such as computational costs and privacy issues. Membership inference attack (MIA) refers to the attack where the adversary aims to infer whether a data sample belongs to the training set. In other words, user data privacy might be compromised by MIA from a well-trained model. Therefore, it is vital to have defense mechanisms in place to protect training data, especially in privacy-sensitive applications such as healthcare. 
  • 323
  • 19 Sep 2023
Topic Review
Negotiation Protocol with Pre-Domain Narrowing
Consensus building among agents is crucial in multi-agent system because each agent acts independently according to its utility function, and conflict among agents can occur. Therefore, automated negotiation is an essential technology for efficiently resolving conflicts and forming consensuses while also keeping agents' privacy. As the domain to be negotiated is large, the computational cost of reaching a consensus increases and the agreement rate decreases. Some negotiation protocols have been proposed wherein a mediator collects the utility information of each agent and creates multiple alternatives of agreements to handle large-scale multi-issue negotiations. However, in such protocols, a limitation is placed on agents' privacy because all agents have to disclose their private information by following the mediator and predecided negotiation rules.
  • 322
  • 05 Jun 2023
Topic Review
Green Artificial Intelligence and Digitalization Facilitate
Green AI (Artificial Intelligence) and digitalization facilitate the “Dual-Carbon” goal of low-carbon, high-quality economic development. Green AI is moving from “cloud” to “edge” devices like TinyML, which supports devices from cameras to wearables, offering low-power IoT computing. 
  • 322
  • 26 Sep 2023
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