Search Results - "deep encoder-decoder structure"

Automatic segmentation of white matter hyperintensities and correlation analysis for cerebral small vessel disease by Xu, Bin, Zhang, Xiaofeng, Tian, Congyu, Yan, Wei, Wang, Yuanqing, Zhang, Doudou, Liao, Xiangyun, Cai, Xiaodong

“…Cerebral white matter hyperintensity can lead to cerebral small vessel disease, MRI images in the brain are used to assess the degree of pathological changes…”
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Joint Sequence Learning and Cross-Modality Convolution for 3D Biomedical Segmentation by Kuan-Lun Tseng, Yen-Liang Lin, Hsu, Winston, Chung-Yang Huang

“…Deep learning models such as convolutional neural network have been widely used in 3D biomedical segmentation and achieve state-of-the-art performance…”
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Convolutional autoencoder based on latent subspace projection for anomaly detection by Yu, Qien, Li, Chen, Zhu, Ye, Kurita, Takio

“…Image anomaly detection (AD) is widely researched on many occasions in computer vision tasks. High-dimensional data, such as image data, with noise and complex…”
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CrossTransUnet: A new computationally inexpensive tumor segmentation model for brain MRI by Anaya-Isaza, Andres, Mera-Jimenez, Leonel, Fernandez-Quilez, Alvaro

“…Brain tumors are usually fatal diseases with low life expectancies due to the organs they affect, even if the tumors are benign. Diagnosis and treatment of…”
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Time-domain Separation Priority Pipeline-based Cascaded Multi-task Learning for Monaural Noisy and Reverberant Speech Separation by Dang, Shaoxiang, Matsumoto, Tetsuya, Takeuchi, Yoshinori, Kudo, Hiroaki

“…Monaural speech separation is a crucial task in speech processing, focused on isolating single-channel audio with multiple speakers into individual streams…”
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High-Resolution Recurrent Gated Fusion Network for 3D Pancreas Segmentation by Li, Weijia, Wu, Xing, Hu, Yangjinan, Wang, Lulu, He, Zhongshi, Du, Jinglong

“… Current mainstream pancreas segmentation methods are based on the deep encoder-decoder structure, which recover high-resolution representations from encoded low-resolution representations to generate…”
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Road Segmentation Using CNN with GRU by Lyu, Yecheng, Huang, Xinming

“… The existing deep neural network based segmentation algorithms usually take a very deep encoder-decoder structure to fuse pixels, which requires heavy computations, large memory and long processing time…”
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Joint Sequence Learning and Cross-Modality Convolution for 3D Biomedical Segmentation by Kuan-Lun Tseng, Yen-Liang, Lin, Hsu, Winston, Chung-Yang, Huang

“… To better leverage the multi- modalities, we propose a deep encoder-decoder structure with cross-modality convolution layers to incorporate different modalities of MRI data…”
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