1D Convolutional Neural Network

One-dimensional convolutional neural networks (1D CNNs) are a powerful deep learning technique used for analyzing sequential data, primarily focusing on extracting relevant features from time-series or other 1D signals. Current research emphasizes their application in diverse fields, including signal processing (e.g., speech recognition, biosignal analysis), and various classification tasks (e.g., medical diagnosis, exoplanet detection). The effectiveness and relative efficiency of 1D CNNs, often combined with other architectures like GRUs or GNNs, demonstrates their significant impact across numerous scientific and engineering domains.