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Topic Review
Existing Approaches for Single-Image Super-Resolution
Deep learning has been introduced to single-image super-resolution (SISR). These techniques have taken over the benchmarks of SISR tasks. Nevertheless, most architectural designs necessitate substantial computational resources, leading to a prolonged inference time on embedded systems or rendering them infeasible for deployment.
  • 262
  • 04 Jul 2023
Topic Review
Deep Learning for Protein-Protein Interaction
Deep learning is steadily leaving its transformative imprint across multiple disciplines. Within computational biology, it is expediting progress in the understanding of Protein–Protein Interactions (PPIs), key components governing a wide array of biological functionalities.
  • 296
  • 04 Jul 2023
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.
  • 256
  • 03 Jul 2023
Topic Review
Sustainability, Digital Technologies and the Circular Economy
The textile and clothing (T&C) industry is not usually viewed as an exemplar of sustainable development and the circular economy (CE), as the industry has hitherto developed its products in a linear fashion, with relatively little recycling of the finished goods. 
  • 468
  • 03 Jul 2023
Topic Review
Artificial Intelligence-Assisted Programming Tasks
Artificial intelligence (AI)-assisted programming can enable software engineers to work more efficiently and effectively with the existing software tools such as OpenAI ChatGPT, Github Copilot, DeepMind AlphaCode, Amazon Codewhisperer, Replit Ghostwriter, Microsoft IntelliCode and Codedium, especially in situations where complex algorithms are being used that involve large amounts of code (i.e., Big Code regime). It also strikes a balance between productivity and ensuring safety, security, and reliability within the programming development environment. There are two main categories of AI-assisted programming tasks related to software naturalness: generation and understanding. The former includes code generation, code completion, code translation, code refinement, and code summarization. The latter is concerned with understanding code and includes defect detection and clone detection.
  • 574
  • 03 Jul 2023
Topic Review
Steel Plates Faults Prediction Methods
Fault prediction is a vital task to decrease the costs of equipment maintenance and repair, as well as to improve the quality level of products and production efficiency. Steel plates fault prediction is a significant materials science problem that contributes to avoiding the progress of abnormal events.
  • 312
  • 03 Jul 2023
Topic Review
Smart Parking System Based on Edge-Cloud-Dew Computing Architecture
In a smart parking system, the license plate recognition service controls the car’s entry and exit and plays the core role in the parking lot system. When the Internet is interrupted, the parking lot’s business will also be interrupted. Hence, an Edge-Cloud-Dew architecture for the mobile industry was proposed in order to tackle this critical problem. The architecture has an innovative design, including LAN-level deployment, Platform-as-a-Dew Service (PaaDS), the dew version of license plate recognition, and the dew type of machine learning model training. Based on these designs, the architecture presents many benefits, such as: (1) reduced maintenance and deployment issues and increased dew service reliability and sustainability; (2) effective release of the network constraint on cloud computing and increase in the horizontal and vertical scalability of the system; (3) enhancement of dew computing to resolve the heavy computing process problem; and (4) proposal of a dew type of machine learning training mechanism without requiring periodic retraining, but with acceptable accuracy. 
  • 408
  • 03 Jul 2023
Topic Review
Critical Nodes in Temporal Networks
Many real-world systems can be expressed in temporal networks with nodes playing different roles in structure and function, and edges representing the relationships between nodes. Identifying critical nodes can help us control the spread of public opinions or epidemics, predict leading figures in academia, conduct advertisements for various commodities and so on. 
  • 300
  • 03 Jul 2023
Topic Review
Deep Learning Models for Road Pothole Detection
For self-driving cars, crack detection is crucial because these vehicles rely on sensors to perceive and navigate the environment. Crack visualization has certain methods, such as the use of a deep-learning architecture, capable of processing images at multiple scales. The inability to judge the difference between potholes or patches results in the sudden break or non-breaking elements at inappropriate places because of a confused state of the neural network. In this regard, detecting potholes in self-driving vehicles or road maintenance is vital for future intelligent transportation systems.
  • 285
  • 03 Jul 2023
Topic Review
Multi-UAV Path Planning Algorithms
While several developments have taken place in the field of autonomus guidance and navigation techniques for Unmanned Aerial Vehicle (UAV) systems, obtaining an optimal path planning algorithm remains elusive. With multiple UAVs involvement in missions, these difficulties increase significantly leading to the need for collision free navigation routes from the UAVs' initial positions to target points. Consequently, this entry focuses specifically on Multi-UAV Path Planning Algorithms utilizing Bio -Inspired Algorithms. The findings indicated that bio-inspired algorithms possess substantial potential in addressing multipoint path planning issues and delineate new prospects and implications for the enhancement of this active research domain.
  • 386
  • 03 Jul 2023
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