International Journal of Neural Systems 
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This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.Human Gait Activity Recognition Using Multimodal Sensors
Int J Neural Syst. 2023 Sep 30:2350058. doi: 10.1142/S0129065723500582. Online ahead of print.ABSTRACTHuman activity recognition is an application of machine learning with the aim of identifying activities from the gathered activity raw data acquired by different sensors. In medicine, human gait is commonly analyzed by doctors to detect abnormalities and determine possible treatments for the patient. Monitoring the patient's activity is paramount in evaluating the treatment's evolution. This type of classification is still not enough precise, which may lead to unfavorable reactions and responses. A novel methodology that r...
Source: International Journal of Neural Systems - October 2, 2023 Category: Neurology Authors: Diego Teran-Pineda Karl Thurnhofer-Hemsi Enrique Dom ínguez Source Type: research
Unsupervised Domain Adaptive Dose Prediction Via Cross-Attention Transformer and Target-Specific Knowledge Preservation
Int J Neural Syst. 2023 Sep 29:2350057. doi: 10.1142/S0129065723500570. Online ahead of print.ABSTRACTRadiotherapy is one of the leading treatments for cancer. To accelerate the implementation of radiotherapy in clinic, various deep learning-based methods have been developed for automatic dose prediction. However, the effectiveness of these methods heavily relies on the availability of a substantial amount of data with labels, i.e. the dose distribution maps, which cost dosimetrists considerable time and effort to acquire. For cancers of low-incidence, such as cervical cancer, it is often a luxury to collect an adequate am...
Source: International Journal of Neural Systems - September 29, 2023 Category: Neurology Authors: Jiaqi Cui Jianghong Xiao Yun Hou Xi Wu Jiliu Zhou Xingchen Peng Yan Wang Source Type: research
Unsupervised Domain Adaptive Dose Prediction Via Cross-Attention Transformer and Target-Specific Knowledge Preservation
Int J Neural Syst. 2023 Sep 29:2350057. doi: 10.1142/S0129065723500570. Online ahead of print.ABSTRACTRadiotherapy is one of the leading treatments for cancer. To accelerate the implementation of radiotherapy in clinic, various deep learning-based methods have been developed for automatic dose prediction. However, the effectiveness of these methods heavily relies on the availability of a substantial amount of data with labels, i.e. the dose distribution maps, which cost dosimetrists considerable time and effort to acquire. For cancers of low-incidence, such as cervical cancer, it is often a luxury to collect an adequate am...
Source: International Journal of Neural Systems - September 29, 2023 Category: Neurology Authors: Jiaqi Cui Jianghong Xiao Yun Hou Xi Wu Jiliu Zhou Xingchen Peng Yan Wang Source Type: research
Unsupervised Domain Adaptive Dose Prediction Via Cross-Attention Transformer and Target-Specific Knowledge Preservation
Int J Neural Syst. 2023 Sep 29:2350057. doi: 10.1142/S0129065723500570. Online ahead of print.ABSTRACTRadiotherapy is one of the leading treatments for cancer. To accelerate the implementation of radiotherapy in clinic, various deep learning-based methods have been developed for automatic dose prediction. However, the effectiveness of these methods heavily relies on the availability of a substantial amount of data with labels, i.e. the dose distribution maps, which cost dosimetrists considerable time and effort to acquire. For cancers of low-incidence, such as cervical cancer, it is often a luxury to collect an adequate am...
Source: International Journal of Neural Systems - September 29, 2023 Category: Neurology Authors: Jiaqi Cui Jianghong Xiao Yun Hou Xi Wu Jiliu Zhou Xingchen Peng Yan Wang Source Type: research
Enhancing Robustness of Medical Image Segmentation Model with Neural Memory Ordinary Differential Equation
Int J Neural Syst. 2023 Sep 23:2350060. doi: 10.1142/S0129065723500600. Online ahead of print.ABSTRACTDeep neural networks (DNNs) have emerged as a prominent model in medical image segmentation, achieving remarkable advancements in clinical practice. Despite the promising results reported in the literature, the effectiveness of DNNs necessitates substantial quantities of high-quality annotated training data. During experiments, we observe a significant decline in the performance of DNNs on the test set when there exists disruption in the labels of the training dataset, revealing inherent limitations in the robustness of DN...
Source: International Journal of Neural Systems - September 25, 2023 Category: Neurology Authors: Junjie Hu Chengrong Yu Zhang Yi Haixian Zhang Source Type: research
Effect of Action Units, Viewpoint and Immersion on Emotion Recognition Using Dynamic Virtual Faces
This study investigates the unique contributions of different factors in the communication and perception of emotions conveyed by VHs. Specifically, it examines the effects of the use of action units (AUs) in virtual faces, the positioning of the VH (frontal or mid-profile), and the level of immersion in the VR environment (desktop screen versus immersive VR). Thirty-six healthy subjects participated in each condition. Dynamic virtual faces (DVFs), VHs with facial animations, were used to represent the six basic emotions and the neutral expression. The results highlight the important role of the accurate implementation of ...
Source: International Journal of Neural Systems - September 25, 2023 Category: Neurology Authors: Miguel A Vicente-Querol Antonio Fern ández-Caballero Pascual Gonz ález Luz M Gonz ález-Gualda Patricia Fern ández-Sotos Jos é P Molina Arturo S Garc ía Source Type: research
Enhancing Robustness of Medical Image Segmentation Model with Neural Memory Ordinary Differential Equation
Int J Neural Syst. 2023 Sep 23:2350060. doi: 10.1142/S0129065723500600. Online ahead of print.ABSTRACTDeep neural networks (DNNs) have emerged as a prominent model in medical image segmentation, achieving remarkable advancements in clinical practice. Despite the promising results reported in the literature, the effectiveness of DNNs necessitates substantial quantities of high-quality annotated training data. During experiments, we observe a significant decline in the performance of DNNs on the test set when there exists disruption in the labels of the training dataset, revealing inherent limitations in the robustness of DN...
Source: International Journal of Neural Systems - September 25, 2023 Category: Neurology Authors: Junjie Hu Chengrong Yu Zhang Yi Haixian Zhang Source Type: research
Effect of Action Units, Viewpoint and Immersion on Emotion Recognition Using Dynamic Virtual Faces
This study investigates the unique contributions of different factors in the communication and perception of emotions conveyed by VHs. Specifically, it examines the effects of the use of action units (AUs) in virtual faces, the positioning of the VH (frontal or mid-profile), and the level of immersion in the VR environment (desktop screen versus immersive VR). Thirty-six healthy subjects participated in each condition. Dynamic virtual faces (DVFs), VHs with facial animations, were used to represent the six basic emotions and the neutral expression. The results highlight the important role of the accurate implementation of ...
Source: International Journal of Neural Systems - September 25, 2023 Category: Neurology Authors: Miguel A Vicente-Querol Antonio Fern ández-Caballero Pascual Gonz ález Luz M Gonz ález-Gualda Patricia Fern ández-Sotos Jos é P Molina Arturo S Garc ía Source Type: research
Enhancing Robustness of Medical Image Segmentation Model with Neural Memory Ordinary Differential Equation
Int J Neural Syst. 2023 Sep 23:2350060. doi: 10.1142/S0129065723500600. Online ahead of print.ABSTRACTDeep neural networks (DNNs) have emerged as a prominent model in medical image segmentation, achieving remarkable advancements in clinical practice. Despite the promising results reported in the literature, the effectiveness of DNNs necessitates substantial quantities of high-quality annotated training data. During experiments, we observe a significant decline in the performance of DNNs on the test set when there exists disruption in the labels of the training dataset, revealing inherent limitations in the robustness of DN...
Source: International Journal of Neural Systems - September 25, 2023 Category: Neurology Authors: Junjie Hu Chengrong Yu Zhang Yi Haixian Zhang Source Type: research
Effect of Action Units, Viewpoint and Immersion on Emotion Recognition Using Dynamic Virtual Faces
This study investigates the unique contributions of different factors in the communication and perception of emotions conveyed by VHs. Specifically, it examines the effects of the use of action units (AUs) in virtual faces, the positioning of the VH (frontal or mid-profile), and the level of immersion in the VR environment (desktop screen versus immersive VR). Thirty-six healthy subjects participated in each condition. Dynamic virtual faces (DVFs), VHs with facial animations, were used to represent the six basic emotions and the neutral expression. The results highlight the important role of the accurate implementation of ...
Source: International Journal of Neural Systems - September 25, 2023 Category: Neurology Authors: Miguel A Vicente-Querol Antonio Fern ández-Caballero Pascual Gonz ález Luz M Gonz ález-Gualda Patricia Fern ández-Sotos Jos é P Molina Arturo S Garc ía Source Type: research
Enhancing Robustness of Medical Image Segmentation Model with Neural Memory Ordinary Differential Equation
Int J Neural Syst. 2023 Sep 23:2350060. doi: 10.1142/S0129065723500600. Online ahead of print.ABSTRACTDeep neural networks (DNNs) have emerged as a prominent model in medical image segmentation, achieving remarkable advancements in clinical practice. Despite the promising results reported in the literature, the effectiveness of DNNs necessitates substantial quantities of high-quality annotated training data. During experiments, we observe a significant decline in the performance of DNNs on the test set when there exists disruption in the labels of the training dataset, revealing inherent limitations in the robustness of DN...
Source: International Journal of Neural Systems - September 25, 2023 Category: Neurology Authors: Junjie Hu Chengrong Yu Zhang Yi Haixian Zhang Source Type: research
Effect of Action Units, Viewpoint and Immersion on Emotion Recognition Using Dynamic Virtual Faces
This study investigates the unique contributions of different factors in the communication and perception of emotions conveyed by VHs. Specifically, it examines the effects of the use of action units (AUs) in virtual faces, the positioning of the VH (frontal or mid-profile), and the level of immersion in the VR environment (desktop screen versus immersive VR). Thirty-six healthy subjects participated in each condition. Dynamic virtual faces (DVFs), VHs with facial animations, were used to represent the six basic emotions and the neutral expression. The results highlight the important role of the accurate implementation of ...
Source: International Journal of Neural Systems - September 25, 2023 Category: Neurology Authors: Miguel A Vicente-Querol Antonio Fern ández-Caballero Pascual Gonz ález Luz M Gonz ález-Gualda Patricia Fern ández-Sotos Jos é P Molina Arturo S Garc ía Source Type: research
Epileptic Seizure Prediction Using Attention Augmented Convolutional Network
In this study, a novel epileptic seizure prediction method is proposed based on multi-head attention (MHA) augmented convolutional neural network (CNN) to address the issue of CNN's limit of capturing global information of input signals. First, data enhancement is performed on original EEG recordings to balance the pre-ictal and inter-ictal EEG data, and the EEG recordings are sliced into 6-second-long EEG segments. Subsequently, EEG time-frequency distribution is obtained using Stockwell transform (ST), and the attention augmented convolutional network is employed for feature extraction and classification. Finally, post-p...
Source: International Journal of Neural Systems - September 7, 2023 Category: Neurology Authors: Dongsheng Liu Xingchen Dong Dong Bian Weidong Zhou Source Type: research
Epileptic Seizure Prediction Using Attention Augmented Convolutional Network
In this study, a novel epileptic seizure prediction method is proposed based on multi-head attention (MHA) augmented convolutional neural network (CNN) to address the issue of CNN's limit of capturing global information of input signals. First, data enhancement is performed on original EEG recordings to balance the pre-ictal and inter-ictal EEG data, and the EEG recordings are sliced into 6-second-long EEG segments. Subsequently, EEG time-frequency distribution is obtained using Stockwell transform (ST), and the attention augmented convolutional network is employed for feature extraction and classification. Finally, post-p...
Source: International Journal of Neural Systems - September 7, 2023 Category: Neurology Authors: Dongsheng Liu Xingchen Dong Dong Bian Weidong Zhou Source Type: research
Epileptic Seizure Prediction Using Attention Augmented Convolutional Network
In this study, a novel epileptic seizure prediction method is proposed based on multi-head attention (MHA) augmented convolutional neural network (CNN) to address the issue of CNN's limit of capturing global information of input signals. First, data enhancement is performed on original EEG recordings to balance the pre-ictal and inter-ictal EEG data, and the EEG recordings are sliced into 6-second-long EEG segments. Subsequently, EEG time-frequency distribution is obtained using Stockwell transform (ST), and the attention augmented convolutional network is employed for feature extraction and classification. Finally, post-p...
Source: International Journal of Neural Systems - September 7, 2023 Category: Neurology Authors: Dongsheng Liu Xingchen Dong Dong Bian Weidong Zhou Source Type: research
