论文标题
使用卷积神经网络基于脑电图的情绪感测
EEG Based Emotion Sensing using convolutional neural networks
论文作者
论文摘要
深度学习影响了各个领域，尤其是在生物医学应用中。深度学习算法与结构化和非结构化数据都很好地运行。尤其是，卷积神经网络与诸如脑电图数据之类的基于信号的数据很好地运行。这些类型的数据可能会或可能不会遵循其数据中的模式。 CNN等算法有助于具有工程和对数据的简单解释。与属于较大数据集的数据相比，与其他算法相比，这些算法也更好。
Deep Learning has impacted various fields especially in bio-medical applications. Deep learning algorithms work well with both structured and unstructured data. Especially, convolutional neural network work well with signal-based data like EEG data. These types of data may or may not follow a pattern in their data. Algorithms like CNN help feature engineering and simplistic interpretation of the data. These algorithms are also better in comparison to other algorithms when generalised to a data belonging to larger data set.
