The magic happens using the TinyML model I built, where I trained it on two weeks of data by exporting every timestamped ...
New papers on Apple's machine learning blog detail how AI can be used for faster, cheaper, and more effective QE testing, as ...
Anomaly-NIDS-Project/ ├── data/ # Raw and processed dataset (ignored in Git) ├── models/ # Saved models and training checkpoints ├── scripts/ # Python scripts for training, evaluation, detection │ ├── ...
Abstract: Infrared-visible image fusion methods aim at generating fused images with good visual quality and also facilitate the performance of high-level tasks. Indeed, existing semantic-driven ...
Abstract: In this paper, we propose a novel Transformer based approach, namely Cross-modal Contrastive Masked AutoEncoder (C2MAE), to Self-Supervised Learning (SSL) on compressed videos. A unified ...
This project explores autoencoders, a class of neural networks used for unsupervised learning. Specifically, we focus on using autoencoders to remove noise from images and restore corrupted images. We ...