This paper mainly discusses how to effectively use multi-core embedded digital signal processor (DSP) technology to realize parallel computation of image tracking algorithm and memory optimization in high precision mi...
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Revolutionizing industries with aerial vehicles using mobile for surveillance is the proposed title of this paper. The availability of drones has created several opportunities, particularly in the areas of agriculture...
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ISBN:
(数字)9798350379990
ISBN:
(纸本)9798350391558;9798350379990
Revolutionizing industries with aerial vehicles using mobile for surveillance is the proposed title of this paper. The availability of drones has created several opportunities, particularly in the areas of agriculture, transportation, and security. This study is a follow-up to the creation of a drone controlled by Wi-Fi-based UAV and advanced imageprocessing. To provide simple and seamless control, a mobile application has been released. Drone-taken photos and videos can also be processed and studied right away. Increasing the degree of autonomous vehicle operations, improving the accuracy of picture identification/analysis algorithms, and ensuring continuous communication between the drone and the control software are perhaps the key objectives of this work. The imageprocessing component aims to take into account sophisticated improvements such as terrain analysis, object detection, and anomaly detection, which are crucial, particularly in the context of security surveillance. Ensuring steady and long-range connectivity while taking certain environmental elements into account can be critical. Enhancing the imageprocessing technique to run smoothly on the off-board drone's hardware constraints is also a crucial step. However, integrating hardware and software continues to be a major challenge in the implementation of a dependable, high-accuracy, real-time analog-to-digital conversion system. The purpose of this research is to develop novel ways for improving UAV systems by integrating tough control systems with complicated image analysis capabilities. Keeping the aforementioned limits in mind, the purpose of this work is to improve understanding of how to create more self-sufficient and adaptive drones that can contribute to a broader range of professions or do more specific activities with minimal human interaction.
In recent years, deep neural networks have achieved tremendous success in image classification in both academic and industrial settings. However, the high hardware requirements imposed by their intensive and complex c...
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The distribution of haze in UAV aerial haze images is usually inhomogeneous, and the traditional dehazing algorithms that may have some problems such as haze residue or excessive dehazing when processing them, this pa...
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Coastal flooding events have caused many issues to infrastructure including bridges and highways. How to assess the flooding level and infrastructure damages in a low-cost, rapid, and accurate approach is critical to ...
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ISBN:
(纸本)9781510660793;9781510660809
Coastal flooding events have caused many issues to infrastructure including bridges and highways. How to assess the flooding level and infrastructure damages in a low-cost, rapid, and accurate approach is critical to the infrastructure performance recovery. Due to the limited access to infrastructure during the post-flooding events, it is very challenging to evaluate infrastructure conditions closely. With the help of small unmanned aerial vehicles and onboard cameras, it provides the possibility to inspect the infrastructure conditions from images captured by drones remotely. With the additional help of imageprocessingalgorithms, it can help capture the infrastructure conditions and flooding levels from the imageries automatically with post-processing analysis. In this paper, we apply several different imageprocessingalgorithms to assess the infrastructure conditions by segmenting the flooding zone from the infrastructure. The performance of these algorithms in assessing infrastructure conditions is compared based on different factors with previously taken airborne imageries of infrastructure and flooding events. The performance of imageprocessing is summarized and future work of assessing the infrastructure post-flooding damages is discussed.
This paper discusses the frontier exploration and application prospect of image recognition technology based on deep learning. Firstly, the application and importance of deep learning in the field of image recognition...
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Remote sensing images are widely used in various fields, such as geographic information systems, environmental monitoring, and agricultural management. However, remote sensing images are often corrupted by various noi...
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image enhancement technology plays an important role in the practical application of detecting underwater tunnels. By improving image quality, it enhances the accuracy and reliability of detection results. However, in...
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The International Workshop on Artificial Intelligence for Signal, imageprocessing, and Multimedia (AI-SIPM) aims to provide a platform for researchers, practitioners, and industry professionals to exchange ideas, dis...
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ISBN:
(纸本)9798400706028
The International Workshop on Artificial Intelligence for Signal, imageprocessing, and Multimedia (AI-SIPM) aims to provide a platform for researchers, practitioners, and industry professionals to exchange ideas, discuss recent advancements, and explore future directions in the field of artificial intelligence (AI) applied to signal processing, imageprocessing, and multimedia technologies. This workshop will feature presentations of novel research findings, practical applications, and innovative solutions addressing various challenges and opportunities in AI-driven signal and imageprocessing, as well as multimedia analysis and understanding. Researchers and practitioners from academia, industry, and government agencies are invited to submit their original research contributions and participate in discussions that foster collaboration and knowledge sharing across different domains. Through this workshop, we aim to accelerate advancements in AI-driven technologies for signal processing, image analysis, and multimedia applications, contributing to the advancement of research and innovation in this rapidly evolving field.
In the post-harvest stages of agricultural products, labor shortages and poor-quality control lead to significant market losses. The automated industries for agricultural products that use machine learning are evolvin...
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