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Tianyu Bai, Song Fu and Qing Yang
With the wider adoption of edge computing services, intelligent edge devices, and high-speed V2X communication, compute-intensive tasks for autonomous vehicles, such as object detection using camera, LiDAR, and/or radar data, can be partially offloaded t...
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Zonglei Lyu and Jia Luo
Airport apron carries a lot of preparations for flight operation, and the advancement of its various tasks is of great significance to the flight operation. In order to build a more intelligent and easy-to-deploy airport apron operation analysis guarante...
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Shou-Cih Chen and Chung-Cheng Chiu
The edge detection algorithm is the cornerstone of image processing; a good edge detection result can further extract the required information through rich texture information and achieve object detection, segmentation, and identification. To obtain a ri...
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Ruicheng Gao, Zhancai Dong, Yuqi Wang, Zhuowen Cui, Muyang Ye, Bowen Dong, Yuchun Lu, Xuaner Wang, Yihong Song and Shuo Yan
In this study, a deep-learning-based intelligent detection model was designed and implemented to rapidly detect cotton pests and diseases. The model integrates cutting-edge Transformer technology and knowledge graphs, effectively enhancing pest and disea...
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Yuhuan Wu and Yonghong Wu
Salient object detection (SOD) aims to identify the most visually striking objects in a scene, simulating the function of the biological visual attention system. The attention mechanism in deep learning is commonly used as an enhancement strategy which e...
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Dingnan Song, Ran Liu, Zhiwei Zhang, Dingding Yang and Tianzhen Wang
Tidal stream turbines (TSTs) harness the kinetic energy of tides to generate electricity by rotating the rotor. Biofouling will lead to an imbalance between the blades, resulting in imbalanced torque and voltage across the windings, ultimately polluting ...
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Jiansen Zhao, Fengchuan Song, Guobao Gong and Shengzheng Wang
Accurate and real-time monitoring of the shoreline through cameras is an invaluable guarantee for the safety of near-shore navigation and berthing of unmanned surface vehicles; existing shoreline detection methods cannot meet both these requirements. The...
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Yao-Liang Chung
Against the backdrop of rising road traffic accident rates, measures to prevent road traffic accidents have always been a pressing issue in Taiwan. Road traffic accidents are mostly caused by speeding and roadway obstacles, especially in the form of rock...
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Shenghan Zhou, Tianhuai Wang, Linchao Yang, Zhao He and Siting Cao
This paper aims to build a Self-supervised Fault Detection Model for UAVs combined with an Auto-Encoder. With the development of data science, it is imperative to detect UAV faults and improve their safety. Many factors affect the fault of a UAV, such as...
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Peigen Li, Haiting Xia, Bin Zhou, Feng Yan and Rongxin Guo
In recent years, deep learning-based detection methods have been applied to pavement crack detection. In practical applications, surface cracks are divided into inner and edge regions for pavements with rough surfaces and complex environments. This creat...
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Eduardo Assunção, Pedro D. Gaspar, Khadijeh Alibabaei, Maria P. Simões, Hugo Proença, Vasco N. G. J. Soares and João M. L. P. Caldeira
Within the scope of precision agriculture, many applications have been developed to support decision making and yield enhancement. Fruit detection has attracted considerable attention from researchers, and it can be used offline. In contrast, some applic...
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Jarina Raihan A, Pg Emeroylariffion Abas and Liyanage C. De Silva
Underwater images are extremely sensitive to distortion occurring in an aquatic underwater environment, with absorption, scattering, polarization, diffraction and low natural light penetration representing common problems caused by sea water. Because of ...
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Emanuele Torti, Caterina Toma, Stela Vujosevic, Paolo Nucci, Stefano De Cillà and Francesco Leporati
Cysts detection in the retina is of crucial importance for the correct evaluation of microvascular impairment in patients with macular edema on images acquired by optical coherence tomography angiography. We describe a fully automatic method for cysts de...
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Halil Murat Ünver, Yunus Kökver, Elvan Duman and Osman Ayhan Erdem
Accurate and efficient localization of the optic disk (OD) in retinal images is an essential process for the diagnosis of retinal diseases, such as diabetic retinopathy, papilledema, and glaucoma, in automatic retinal analysis systems. This paper present...
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Febri Liantoni, Rifki Indra Perwira, Daniel Silli Bataona
Pág. 328 - 336
Leaf bone structure has a characteristic that can be used as a reference in digital image processing. One form of digital image processing is image edge detection. Edge detection is the process of extracting edge information from an image. In this resear...
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Claudia I. Gonzalez, Patricia Melin and Oscar Castillo
This paper presents a new general type-2 fuzzy logic method for edge detection applied to color format images. The proposed algorithm combines the methodology based on the image gradients and general type-2 fuzzy logic theory to provide a powerful edge d...
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Febri Liantoni,Luky Agus Hermanto
Pág. 75 - 79
Abstract? Leaves recognition can use an image edge detection method. In this research, the classification of mango gadung and manalagi will be performed. In the preprocess stage edge detection method using adaptive ant colony optimization method. The use...
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Sepehr Honarparvar, Sara Saeedi, Steve Liang and Jeremy Squires
Emerging deep learning (DL) approaches with edge computing have enabled the automation of rich information extraction, such as complex events from camera feeds. Due to the low speed and accuracy of object detection, some objects are missed and not detect...
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Guojie Chen and Min Lin
Lossless coding is a compression method in the Versatile Video Coding (VVC) standard, which can compress video without distortion. Lossless coding has great application prospects in fields with high requirements for video quality. Since the current VVC s...
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Yiheng Zhou, Kainan Ma, Qian Sun, Zhaoyuxuan Wang and Ming Liu
Over the past several decades, deep neural networks have been extensively applied to medical image segmentation tasks, achieving significant success. However, the effectiveness of traditional deep segmentation networks is substantially limited by the sma...
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