Development and Comparative Analysis of Temporal Convolutional Network for Time Series Data Classification - Alekhya, Dasari; Haritha, Donavalli (Journal of Neonatal Surgery, 2025)
The paper describes the development and assessment of a Temporal Convolutional Network model used for the classification of time-series data, with focus on biomedical signal datasets. The proposed TCN uses dilated convolutions to effectively reflect temporal dependencies. Two implementation variants are compared in terms of their performance: one with softmax activation that is ideal for multi-class, and the other with sigmoid activation, used in case of binary classification. The basis of comparison is the accuracy and loss computed for training and validation datasets. The findings reveal that TCN models can accurately solve complicated classification tasks that are based on time series. The models offer a competitive alternative to conventional deep learning.