IEEE

Compression-Based Complexity Analysis of Thalamic EEG Using Multiscale Preprocessing Techniques

Abstract: Quantifying the complexity of biomedical signals offers critical insight into underlying physiological and pathological dynamics. This study systematically evaluates compression-based ...
GitHub

kajeethkumar/1D-CNN-FAO

This repository contains the implementation of a 1D CNN optimized using the Fractional Adam Optimizer (FAO) for ECG arrhythmia classification on the MIT-BIH Arrhythmia dataset. MIT-BIH Arrhythmia ...
IEEE

Efficient Image Compression Techniques Leveraging Wavelet Transform and Quantization

Abstract: Image compression is a continuously evolving field, driven by the need for optimizing storage and transmission while maintaining image fidelity. This work explores a hybrid compression ...
Tech Times

Compile Once, Run Offline: New AI Method Matches 32B Models With a 23MB File

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...
GitHub

FlowLet: Conditional 3D Brain MRI Synthesis using Wavelet Flow Matching

Official PyTorch implementation of "FlowLet: Conditional 3D Brain MRI Synthesis using Wavelet Flow Matching" (accepted at Medical Image Analysis, Elsevier). flowlet/ Core library ├── wavelets/ ...
Frontiers

MsGCN: a multi-stream graph convolutional network for multiband PLV graph fusion in EEG-based biometric identification

2.2 EEG preprocessing The EEG recordings were segmented using a sliding-window strategy. To avoid potential data leakage caused by overlapping windows, the train/test split was performed before window ...