IEEE

Depression Detection Through EEG Signal Analysis: A Convolutional Autoencoder Deep Learning Model

Abstract: Depression is a debilitating and enervating mental health disorder that requires attention for necessitating accurate and efficient diagnostic techniques ...
IEEE

Multiscale Spectral–Spatial Unmixing Network With Boltzmann-Inspired Adaptive Temperature

Abstract: Hyperspectral unmixing aims to decompose mixed pixels into endmembers with corresponding abundances. However, while several existing convolutional autoencoder methods usually use fixed ...
GitHub

SVG-T2I: Scaling up Text-to-Image Latent Diffusion Model

Important Note: This repository implements SVG-T2I, a text-to-image diffusion framework that performs visual generation directly in Visual Foundation Model (VFM) representation space, rather than ...
GitHub

ohtlab/headpose-fsanet-pytorch

Note: My results are slightly worse than original author's results. For best results, please refer to official repository 1. Name Version python 3.7.6 numpy 1.18.5 ...
Scientific Research Publishing

A Hybrid CNN-LSTM Variational Autoencoder for Treatment Response Prediction in Synthetic Psychiatric Data ()

Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of conventional ...
Scientific Research Publishing

Justice, A.C., Covinsky, K.E. and Berlin, J.A. (1999) Assessing the Generalizability of Prognostic Information. Annals of Internal Medicine, 130, 515-524.

ABSTRACT: Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of ...