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Topic Review
High-Fidelity Synthetic Face Generation for Rosacea Skin Condition
Similarly to the majority of deep learning applications, diagnosing skin diseases using computer vision and deep learning often requires a large volume of data. However, obtaining sufficient data for particular types of facial skin conditions can be difficult, due to privacy concerns. As a result, conditions like rosacea are often understudied in computer-aided diagnosis. The limited availability of data for facial skin conditions has led to the investigation of alternative methods of computer-aided diagnosis. Generative adversarial networks (GANs), mainly variants of StyleGANs, have demonstrated promising results in generating synthetic facial images.
  • 142
  • 14 Feb 2024
Topic Review
Image-Compression Techniques
Image compression is a vital component for domains in which the computational resources are usually scarce such as automotive or telemedicine fields. Also, when discussing real-time systems, the large amount of data that must flow through the system can represent a bottleneck. Therefore, the storage of images, alongside the compression, transmission, and decompression procedures, becomes vital. In recent years, many compression techniques that only preserve the quality of the region of interest of an image have been developed, the other parts being either discarded or compressed with major quality loss. 
  • 230
  • 08 Feb 2024
Topic Review
Anomaly Detection in Software-Defined Networks
One solution enabling the implementation of modern methods for managing and monitoring telecommunication networks is the concept of software-defined networks (SDN). It introduces a centralized architecture for managing computer networks that is fully programmable. With the increasing availability of computational power, contemporary machine learning has undergone a paradigm shift, placing a heightened emphasis on deep learning methodologies. The pervasive automation of various processes necessitates a critical re-evaluation of contemporary network implementations, specifically concerning security protocols and the imperative need for swift, precise responses to system failures.
  • 180
  • 08 Feb 2024
Topic Review
Incremental Scene Classification Using Dual Knowledge Distillation
Conventional deep neural networks face challenges in handling the increasing amount of information in real-world scenarios where it is impractical to gather all the training data at once. Incremental learning, also known as continual learning, provides a solution for lightweight and sustainable learning with neural networks.
  • 259
  • 08 Feb 2024
Topic Review
Compressive Sensing in Image/Video Compression
Compressive Sensing (CS) has emerged as a transformative technique in image compression, offering innovative solutions to challenges in efficient signal representation and acquisition. 
  • 155
  • 08 Feb 2024
Topic Review
Authentication Paradigms in the Internet of Things
In the rapidly expanding domain of the Internet of Things (IoT), ensuring the implementation of robust security measures such as authentication has become paramount to safeguarding sensitive data and maintaining the integrity of connected devices. Symmetry in the IoT commonly denotes the uniformity or equilibrium in data distribution and processing across devices or nodes in a network. Leveraging symmetric patterns can enhance the robustness and scalability of IoT authentication. 
  • 170
  • 08 Feb 2024
Topic Review
Distributed Denial of Service Attacks
Mobile Edge Computing (MEC) has revolutionized the landscape of the telecommunication industry by offering low-latency, high-bandwidth, and real-time processing. With this advancement comes a broad range of security challenges, the most prominent of which is Distributed Denial of Service (DDoS) attacks, which threaten the availability and performance of MEC’s services. In most cases, Intrusion Detection Systems (IDSs), a security tool that monitors networks and systems for suspicious activity and notify administrators in real time of potential cyber threats, have relied on shallow Machine Learning (ML) models that are limited in their abilities to identify and mitigate DDoS attacks.
  • 131
  • 07 Feb 2024
Topic Review
Task Scheduling in Cloud Computing
Cloud computing resources have become one of the trending technologies that permit the user to manage diverse resources and a huge amount of data in the cloud. Task scheduling is considered one of the most significant challenges and ineffective management results in performance degradation. It is necessary to schedule the task effectively with maximum resource utilization and minimum execution time. 
  • 152
  • 07 Feb 2024
Topic Review
Strawberry Ripeness Classification
Image analysis-based artificial intelligence (AI) models leveraging convolutional neural networks (CNN) take a significant role in evaluating the ripeness of strawberry, contributing to the maximization of productivity. However, the convolution, which constitutes the majority of the CNN models, imposes significant computational burdens. Additionally, the dense operations in the fully connected (FC) layer necessitate a vast number of parameters and entail extensive external memory access. Therefore, reducing the computational burden of convolution operations and alleviating memory overhead is essential in embedded environment.
  • 168
  • 07 Feb 2024
Topic Review
Deep Learning Frameworks and Tools
Deep learning (DL) has been applied successfully in medical imaging such as reconstruction, classification, segmentation, and detection.
  • 183
  • 07 Feb 2024
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