Lim, J.Z., Mountstephens, J. and Teo, J. (2022) Eye-Tracking Feature Extraction for Biometric Machine Learning. Frontiers in Neurorobotics, 15, Article ID 796895.

A gradual fine-tuning strategy was employed, progressively unfreezing the last 6 layers of ESM-2 encoder and applying discriminative learning rates with the AdamW optimizer. The model was trained ...

KEYWORDS: Auto-Encoder, Stacked Voting, Classification, Cancer Diagnosis, Gene Expression, Prediction JOURNAL NAME: Journal of Biosciences and Medicines, Vol.13 No.3, March 14, 2025 ABSTRACT: Gene ...

Imaging mass spectrometry (IMS) is a technique for simultaneously acquiring the expression and distribution of molecules on the surface of a sample, and it plays a crucial role in spatial omics ...

An advanced generalized autoencoder for dimensionality reduction and feature extraction AutoencoderZ is an advanced Autoencoder model designed for dimensionality reduction of various data types, such ...

In the last decade, auxiliary information has been widely used to address data sparsity. Due to the advantages of feature extraction and the no-label requirement, autoencoder-based methods ...

Method overview: The proposed method involves three steps: Unsupervised training of a generative feature extractor Diffusion Autoencoder (DAE). Supervised training of a binary classifier to detect a ...

Lignocellulosic biomass is an abundant feedstock for producing sustainable fuels and chemicals. However, a key challenge in most biomass utilization strategies is the recovery of products from a ...

Feature Extraction Challenges While essential for optimizing machine learning models, feature extraction faces numerous challenges. For example, some techniques require domain-specific knowledge, ...