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Topic Review
Lightweight IoT Intrusion Detection Systems
Cyber security has become increasingly challenging due to the proliferation of the Internet of Things (IoT), where a massive number of tiny, smart devices push trillion bytes of data to the Internet and is expected to reach 73.1 ZB (zettabytes) by 2025. IoT devices have limited computational capabilities and thus researchers have shifted their focus onto designing lightweight intrusion-detection system (IDS) that can deliver the needed security requirements while operating on those thin devices.
  • 296
  • 29 Aug 2023
Topic Review
Railway Track Fault Detection
Railway track faults may lead to railway accidents and cause human and financial loss. Spatial, temporal, and weather elements, and wear and tear, lead to ballast, loose nuts, misalignment, and cracks leading to accidents. Manual inspection of such defects is time-consuming and prone to errors. Automatic inspection provides a fast, reliable, and unbiased solution. However, highly accurate fault detection is challenging due to the lack of public datasets, noisy data, inefficient models, etc. 
  • 300
  • 29 Aug 2023
Topic Review
Zero-Shot Semantic Segmentation with No Supervision Leakage
Zero-shot semantic segmentation (ZS3), the process of classifying unseen classes without explicit training samples, poses a significant challenge. Despite notable progress made by pre-trained vision-language models, they have a problem of “supervision leakage” in the unseen classes due to their large-scale pre-trained data.
  • 376
  • 29 Aug 2023
Topic Review
Reduce Certificate Frauds in the Academic Field
In the digital age, ensuring the authenticity and security of academic certificates is a critical challenge faced by educational institutions, employers, and individuals alike. Traditional methods for verifying academic credentials are often cumbersome, time-consuming, and susceptible to fraud. However, the emergence of blockchain technology offers a promising solution to address these issues.
  • 320
  • 28 Aug 2023
Topic Review
Digital Face Manipulation Creation and Detection
Deepfake refers to the sophisticated manipulation of audiovisual content using deep learning techniques, particularly generative adversarial networks (GANs). It enables the creation of hyper-realistic fake videos or images by seamlessly superimposing one person's face or voice onto another's. These manipulated media raise significant concerns about misinformation, privacy invasion, and the potential to deceive audiences. Deepfakes have sparked discussions about the ethical implications of digital media manipulation and the challenges of distinguishing between genuine and fabricated content in the digital age. Efforts to counter deepfake technology involve developing advanced detection methods and raising awareness about the prevalence of manipulated media.
  • 410
  • 25 Aug 2023
Topic Review
DDoS Detection Using DL Models and Explanation Methods
With the rise of distributed denial of service (DDoS) attacks, several machine learning-based attack detection models have been used to mitigate malicious behavioral attacks. Understanding how machine learning models work is not trivial. This is particularly true for complex and nonlinear models, such as deep learning models that have high accuracy. The struggle to explain these models creates a tension between accuracy and explanation. Different methods have been used to explain deep learning models and address ambiguity issues.
  • 297
  • 25 Aug 2023
Topic Review
Transformer Framework and YOLO Framework for Object Detection
Object detection for remote sensing is a fundamental task in image processing of remote sensing; as one of the core components, small or tiny object detection plays an important role. 
  • 402
  • 25 Aug 2023
Topic Review
Classification of Sleep Stages Using Telemetry Polysomnography
Accurate sleep stage detection is crucial for diagnosing sleep disorders and tailoring treatment plans. Polysomnography (PSG) is considered the gold standard for sleep assessment as it captures diverse physiological signals. Recent advancements have shown that simpler machine learning models, when coupled with sophisticated feature extraction techniques, can yield accurate and reliable results comparable to those achieved by complex deep learning methods. These simpler models not only reduce the computational burden but also offer greater interpretability, a feature that is highly valued in clinical settings for both diagnostic and treatment purposes. Therefore, integrating simpler machine learning algorithms with advanced feature extraction can serve as an effective and efficient approach for sleep stage classification in research and clinical applications.
  • 415
  • 25 Aug 2023
Topic Review
Privacy-Preserving Blockchain Technologies
The main characteristics of blockchains, such as security and traceability, have enabled their use in many distinct scenarios, such as the rise of new cryptocurrencies and decentralized applications (dApps). However, part of the information exchanged in the typical blockchain is public, which can lead to privacy issues. To avoid or mitigate these issues, some blockchains are applying mechanisms to deal with data privacy. Trusted execution environments, the basis of confidential computing, and secure multi-party computation are two technologies that can be applied in that sense. 
  • 581
  • 24 Aug 2023
Topic Review
Augmented Reality in Tourism Industry (2002-2022)
Augmented reality has emerged as a transformative technology, with the potential to revolutionize the tourism industry.
  • 677
  • 24 Aug 2023
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