eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
IEEE

Supervised Convolutional Encoder-Decoder With Gated Linear Units for Detecting Fetal R-Peaks

Abstract: Noninvasive fetal electrocardiography (ECG) is prevalently used for monitoring fetal heartbeats during pregnancy due to its affordability, ease of use, and constant monitoring capability. A ...
IEEE

Convolutional Encoder-Decoder Based Salient Object Detection

Abstract: Saliency detection has achieved outstanding performance by utilizing deep encoder-decoder networks. Many of the existing saliency approaches, however, are unable to effectively process ...
GitHub

Few-Shot EEG Visual Decoding via Wavelet-Based Prototypical Networks

Key insight: model trained on simple data generalizes to complex data without fine-tuning. Support set: S = {(x_1, y_1), ..., (x_n, y_n)} where n = N * K Query set: Q ...
Scientific Research Publishing

Liang, J., Chen, J. H., Zhang, X. Q. et al. (2019). Anomaly Detection Based on One-Hot Encoding and Convolutional Neural Network. Journal of Tsinghua University (Science and ...

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.