Urban traffic congestion necessitates innovative monitoring and control solutions. This study leverages UAV footage and deep learning techniques to classify and analyze traffic density levels autonomously. By employin...
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ISBN:
(数字)9798331522193
ISBN:
(纸本)9798331522209
Urban traffic congestion necessitates innovative monitoring and control solutions. This study leverages UAV footage and deep learning techniques to classify and analyze traffic density levels autonomously. By employing a pre-trained ResN et50 model enhanced with additional layers, the research optimizes traffic density classification using UAV-captured data. A custom dataset of traffic scenarios in Dammam, Saudi Arabia, was developed, incorporating diverse conditions through advanced normalization and data augmentation techniques to improve resilience and robustness. The modified ResN et50 model demonstrated high classification accuracy across varied traffic scenarios, validating its reliability and scalability for real-world applications. Key findings include the superior adaptability of UAV-based monitoring for real-time urban traffic assessment and the enhanced classification precision achieved through model optimization. This research underscores the potential of integrating UAV technology with deep learning to advance urban traffic management and foster more efficient urban planning strategies.
Fire incidents pose a significant security threat that requires attention from all stakeholders. For example, Taipei reported 893 fire incidents in 2023 alone. This study aims to enhance security surveillance by promp...
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Indirect Immunofluorescence (IIF) stained Human Epithelial (HEp-2) cells are considered the gold standard for detecting autoimmune diseases. Accurate cell segmentation, though often viewed as an intermediary step to d...
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Integrating renewable energy sources into smart grids increases supply and demand management because renewable energy sources are intermittent and variable. To overcome this type of challenge, short-term load forecast...
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This paper concentrates on the examination of a class of nonlocal initial value problems for Langevin fractional differential equations featuring the ψ-Caputo fractional derivative within Banach spaces. By utilizing ...
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Many deep architectures and self-supervised pre-training techniques have been proposed for human activity recognition (HAR) from wearable multimodal sensors. Scaling laws have the potential to help move towards more p...
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Multi-Agent Deep Reinforcement Learning (MADRL) has emerged as a powerful tool for optimizing decentralized decision-making systems in complex settings, such as Dynamic Spectrum Access (DSA). However, deploying deep l...
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Early water stress detection is crucial for increasing crop yield, optimizing agricultural practices, and improving water management. This research proposes a novel method for detecting early water stress in lettuces ...
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ISBN:
(纸本)9798400713170
Early water stress detection is crucial for increasing crop yield, optimizing agricultural practices, and improving water management. This research proposes a novel method for detecting early water stress in lettuces using Thermal Infrared (TIR) and RGB images in a controlled environment. The method initially removes the background of the lettuce canopy to eliminate the noise, then clusters the canopy's thermal data to determine temperature variation and applies a yellow pseudo-color to annotate the stressed areas in the RGB images. The logic behind the proposed method is that during water stress, the transpiration of the leaves' stomata is reduced, and the temperature of the leaves increases. The results show that the proposed method finds water stress sooner than visual symptoms expression, providing helpful information for improved crop management and better water use in agriculture.
Steganography, the art of information hiding, has continually evolved across visual, auditory and linguistic domains, adapting to the ceaseless interplay between steganographic concealment and steganalytic revelation....
Data encoding is a fundamental step in emerging computing paradigms, particularly in stochastic computing (SC) and hyperdimensional computing (HDC), where it plays a crucial role in determining the overall system perf...
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