Automation that actually understands your homelab.

Abstract: Anomaly detection in system software traditionally relies on single-modal algorithms that analyze either discrete log events or continuous performance metrics in isolation, potentially ...

Abstract: In hyperspectral anomaly detection (HAD), anomalous pixels typically exhibit a sparsely distributed spatial pattern. Existing deep models often generate backgrounds by reconstructing ...

face-mask-detection/ ├── dataset/ │ ├── with_mask/ # Training images with masks │ └── without_mask/ # Training images without masks ├── model/ │ ├── mask_detector.h5 # Trained model (generated) │ └── ...

GitHub is adopting AI-based scanning for its Code Security tool to expand vulnerability detections beyond the CodeQL static analysis and cover more languages and frameworks. The developer ...

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit ...