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Pengfei Zhao and Ze Liu
The three-dimensional (3D) reconstruction of Electromagnetic Tomography (EMT) is an important task for many applications, such as the non-destructive testing of inner defects in rail systems. Additionally, image reconstruction algorithms utilizing deep l...
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Jiayao Liang and Mengxiao Yin
With the rapid advancement of deep learning, 3D human pose estimation has largely freed itself from reliance on manually annotated methods. The effective utilization of joint features has become significant. Utilizing 2D human joint information to predic...
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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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Qingqing Hong, Xinyi Zhong, Weitong Chen, Zhenghua Zhang and Bin Li
Hyperspectral images (HSIs) are pivotal in various fields due to their rich spectral?spatial information. While convolutional neural networks (CNNs) have notably enhanced HSI classification, they often generate redundant spatial features. To address this...
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Juan Jiang, Hong Liu, Xin Yu, Jin Zhang, Bing Xiong and Lidan Kuang
Precisely segmenting the hippocampus from the brain is crucial for diagnosing neurodegenerative illnesses such as Alzheimer?s disease, depression, etc. In this research, we propose an enhanced hippocampus segmentation algorithm based on 3D U-Net that can...
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Ziyi Li, Yang Li, Yanping Wang, Guangda Xie, Hongquan Qu and Zhuoyang Lyu
With the rapid development of deep learning, more and more complex models are applied to 3D point cloud object detection to improve accuracy. In general, the more complex the model, the better the performance and the greater the computational resource co...
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Hayat Ullah and Arslan Munir
The recognition of human activities using vision-based techniques has become a crucial research field in video analytics. Over the last decade, there have been numerous advancements in deep learning algorithms aimed at accurately detecting complex human ...
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Zhichao Peng, Wenhua He, Yongwei Li, Yegang Du and Jianwu Dang
Speech emotion recognition is a critical component for achieving natural human?robot interaction. The modulation-filtered cochleagram is a feature based on auditory modulation perception, which contains multi-dimensional spectral?temporal modulation repr...
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Jun Wu, Xinyi Sun, Lei Qu, Xilan Tian and Guangyu Yang
Recently, deep learning tools have made significant progress in hyperspectral image (HSI) classification. Most of existing methods implement a patch-based classification manner which may cause training test information leakage or waste labeled informatio...
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