Porting vision models to Keras 3 for easily accessibility. Contains MobileViT v1, MobileViT v2, fastvit

FastViT base model for use with Autodistill.

Reproducible deep-learning image-classification pipeline for industrial soft sensing. Originally built for sludge-cake quality monitoring at DC Water Blue Plains AWWTP. Six architectures (FastViT, EfficientNet, MobileNet, EfficientFormerV2, DeepTEN-ResNet, sparse-AE CNN) compared with multi-seed statistics on Modal cloud GPUs.

WYT-Net: Lightweight Wavelet-YOLO-Transformer hybrid for real-time deepfake detection on edge devices. Uses DWT frequency-domain features + SimAM attention + FastViT blocks — achieving 94.44% accuracy with only 2.57M parameters. Runs at 8.1ms on Jetson Nano (INT8).