technologynetworks

Single-Cell RNA-Seq Data Analysis With AI: Tools, Workflows, and Biological Interpretation

Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...
GitHub

niccolo246/baseline-to-future-ct

Code for the MICCAI paper "From Baseline to Future CT: Large-Scale Diffusion Pretraining for Single-Scan IPF Progression Prediction". The optional CT foundation encoder used for perceptual-feature ...
IEEE

Novel Temporal Autoencoder Model Based on STD for Industrial Soft Sensing

Abstract: Data-driven soft sensing is widely adopted for real-time quality variable detection due to rapid advancements in machine learning. Industrial process data typically exhibit high ...
GitHub

Deep learning-based network anomaly detection that learns the heartbeat of normal traffic and alerts when it breaks — powered by LSTM-Autoencoders on real network flow data.

NeuroShield.Net trains on normal network traffic and flags deviations in real time. It uses an LSTM-Autoencoder to model sequences of network flows, computes ...