AINeutralarXiv – CS AI · 10h ago5/10
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Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis
Researchers have developed an improved deep learning model combining LSTM and CNN layers to classify cognitive workload states from fNIRS brain imaging data. The integrated approach increases classification accuracy from 97.40% to 97.92% by capturing both spatial features and temporal dependencies in neural activity patterns.