Ruimin Dan,Honghui Zhang,Jianchao Bai
Ruimin Dan
This study proposes a novel adaptive DBS control strategy for epilepsy treatment based on deep reinforcement learning. By establishing a random disturbance model of the cortical-thalamus loop, the neural modulation problem is successfully t...
Visually-Inspired Multimodal Iterative Attentional Network for High-Precision EEG-Eye-Movement Emotion Recognition [0.03%]
视觉启发的多模态迭代注意力网络在高精度脑电-眼动情绪识别中的应用
Wei Meng,Fazheng Hou,Kun Chen et al.
Wei Meng et al.
Advancements in artificial intelligence have propelled affective computing toward unprecedented accuracy and real-world impact. By leveraging the unique strengths of brain signals and ocular dynamics, we introduce a novel multimodal framewo...
An Enhanced Random Convolutional Kernel Transform for Diverse and Robust Feature Extraction from High-Density Surface Electromyograms for Cross-day Gesture Recognition [0.03%]
一种增强的随机卷积核变换方法，用于跨天手势识别的高密度表面肌电图的多样和鲁棒特征提取
Yonglin Wu,Xinyu Jiang,Jionghui Liu et al.
Yonglin Wu et al.
High-density surface electromyogram (HD-sEMG) has become a powerful signal source for hand gesture recognition. However, existing approaches suffer from limited feature diversity in hand-crafted methods and high data dependency in deep lear...
A Unified Hypergraph-Mamba Framework for Adaptive Electroencephalogram Modeling in Multi-view Seizure Prediction [0.03%]
一种用于多视图癫痫预测的自适应脑电建模统一超图-曼巴框架
Dengdi Sun,Yanqing Liu,Changxu Dong et al.
Dengdi Sun et al.
Seizure prediction from Electroencephalogram (EEG) signals is a critical task for proactive intervention in epilepsy management. Existing models often struggle to capture high-order inter-channel dependencies dynamically and adapt to the sp...
Evolutionary Channel Pruning for Style-Based Generative Adversarial Networks [0.03%]
基于风格的生成对抗网络的进化通道剪枝法
Yixia Zhang,Ferrante Neri,Xilu Wang et al.
Yixia Zhang et al.
Generative Adversarial Networks (GANs) have demonstrated remarkable success in high-quality image synthesis, with StyleGAN and its successor, StyleGAN2, achieving state-of-the-art performance in terms of realism and control over generated f...
A Multivariate Cloud Workload Prediction Method Integrating Convolutional Nonlinear Spiking Neural Model with Bidirectional Long Short-Term Memory [0.03%]
一种基于卷积非线性脉冲神经模型和双向长短时记忆的多元云工作负载预测方法
Minglong He,Nan Zhou,Hong Peng et al.
Minglong He et al.
Multivariate workload prediction in cloud computing environments is a critical research problem. Effectively capturing inter-variable correlations and temporal patterns in multivariate time series is key to addressing this challenge. To add...
A Prompt-Guided Generative Language Model for Unifying Visual Neural Decoding Across Multiple Subjects and Tasks [0.03%]
一种统一多被试和任务的视觉神经解码的提示引导生成式语言模型
Wei Huang,Hengjiang Li,Fan Qin et al.
Wei Huang et al.
Visual neural decoding not only aids in elucidating the neural mechanisms underlying the processing of visual information but also facilitates the advancement of brain-computer interface technologies. However, most current decoding studies ...
Driver Emotion Recognition Using Multimodal Signals by Combining Conformer and Autoformer [0.03%]
基于 conformer 和 autoformer 的多模态驾驶员情感识别方法
Weiguang Wang,Jian Lian,Chuanjie Xu
Weiguang Wang
This study aims to develop a multimodal driver emotion recognition system that accurately identifies a driver's emotional state during the driving process by integrating facial expressions, ElectroCardioGram (ECG) and ElectroEncephaloGram (...
Objective Assessment of Disorders of Consciousness Based on EEG Temporal and Spectral Features [0.03%]
基于EEG时间及频谱特征的意识障碍客观评定方法研究
Wanqing Dong,Yi Yang,Tong Wu et al.
Wanqing Dong et al.
Most existing studies analyzed the resting-state electroencephalogram (EEG) of DOC patients, and recent research demonstrated that the passive auditory paradigm was helpful for bedside detection of DOC and better captured sensory and cognit...
A Compound-Eye-Inspired Multi-Scale Neural Architecture with Integrated Attention Mechanisms [0.03%]
一种灵感来源于复眼的多尺度神经网络架构及其集成了注意力机制
Ferrante Neri,Mengchen Yang,Yu Xue
Ferrante Neri
In the context of neural system structure modeling and complex visual tasks, the effective integration of multi-scale features and contextual information is critical for enhancing model performance. This paper proposes a biologically inspir...