IEEE

Weak–Strong Graph Contrastive Learning Neural Network for Hyperspectral Image Classification

Abstract: Deep learning methods have shown promising results in various hyperspectral image (HSI) analysis tasks. Despite these advancements, existing models still struggle to accurately identify fine ...
GitHub

Language-agnostic AST analysis and dependency visualization for modern development workflows

CodeGraph is a powerful open source tool that brings advanced computer science principles to everyday development through Abstract Syntax Tree (AST) analysis, dependency graph visualization, and ...
IEEE

Graph-Aware Hybrid Encoding for Hyperspectral Image Classification

Abstract: Hyperspectral image (HSI) classification faces critical challenges in effectively modeling the intricate spectral–spatial structures and non-Euclidean relationships. Traditional methods ...
GitHub

JavaScript captcha solver (Node.js): Bypass reCAPTCHA, Cloudflare, GeeTest and more

Use the JavaScript captcha solver to automatically bypass any captcha - including reCAPTCHA v2, Invisible, v3, Enterprise, Cloudflare Turnstile, GeeTest sliders, Amazon WAF, FunCaptcha, and both image ...
wpi.edu

Joseph D. Fehribach publishes new book: Kirchhoff Graphs, Vector Dependencies and Implications

Kirchhoff graphs are a new type of graph, one whose edges are vectors. They depict the dependencies in sets of vectors, and in this regard, they are akin to matroids. Indeed every binary matroid is ...
Frontiers

RS-STGCN: Regional-Synergy Spatio-Temporal Graph Convolutional Network for emotion recognition

Decoding emotional states from electroencephalography (EEG) signals is a fundamental goal in affective neuroscience. This endeavor requires accurately modeling the complex spatio-temporal dynamics of ...