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Frédéric Leroux, Mickaël Germain, Étienne Clabaut, Yacine Bouroubi and Tony St-Pierre
Digital twins are increasingly gaining popularity as a method for simulating intricate natural and urban environments, with the precise segmentation of 3D objects playing an important role. This study focuses on developing a methodology for extracting bu...
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Yee Sye Lee, Ali Rashidi, Amin Talei and Daniel Kong
In recent years, mixed reality (MR) technology has gained popularity in construction management due to its real-time visualisation capability to facilitate on-site decision-making tasks. The semantic segmentation of building components provides an attrac...
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Fadi Shaar, Arif Yilmaz, Ahmet Ercan Topcu and Yehia Ibrahim Alzoubi
Recognizing aircraft automatically by using satellite images has different applications in both the civil and military sectors. However, due to the complexity and variety of the foreground and background of the analyzed images, it remains challenging to ...
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Abderrazzaq Kharroubi, Zouhair Ballouch, Rafika Hajji, Anass Yarroudh and Roland Billen
Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations o...
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You Sheng Toh and Carol Anne Hargreaves
Extensive medical research has revealed evidence of a strong association between hippocampus atrophy and age-related diseases such as Alzheimer?s disease (AD). Therefore; segmentation of the hippocampus is an important task that can help clinicians and r...
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Lingfeng Huang, Jieyu Zhao and Yu Chen
3D mesh as a complex data structure can provide effective shape representation for 3D objects, but due to the irregularity and disorder of the mesh data, it is difficult for convolutional neural networks to be directly applied to 3D mesh data processing....
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Yongzhe Sun, Linxiao Miao, Ziming Zhao, Tong Pan, Xueying Wang, Yixin Guo, Dawei Xin, Qingshan Chen and Rongsheng Zhu
The investigation of plant phenotypes through 3D modeling has emerged as a significant field in the study of automated plant phenotype acquisition. In 3D model construction, conventional image preprocessing methods exhibit low efficiency and inherent ine...
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Chang Gwon Dang, Seung Soo Lee, Mahboob Alam, Sang Min Lee, Mi Na Park, Ha-Seung Seong, Min Ki Baek, Van Thuan Pham, Jae Gu Lee and Seungkyu Han
Accurate weight measurement is critical for monitoring the growth and well-being of cattle. However, the traditional weighing process, which involves physically placing cattle on scales, is labor-intensive and stressful for the animals. Therefore, the de...
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Qianmu Xiao and Liang Zhao
Acquiring relevant, high-quality, and heterogeneous medical images is essential in various types of automated analysis, used for a variety of downstream data augmentation tasks. However, a large number of real image samples are expensive to obtain, espec...
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Tanweer Rashid, Sharmin Sultana, Mallar Chakravarty and Michel Albert Audette
This paper presents a multi-material dual ?contouring? method used to convert a digital 3D voxel-based atlas of basal ganglia to a deformable discrete multi-surface model that supports surgical navigation for an intraoperative MRI-compatible surgical rob...
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