QAT(quantize aware training) for classification with MQBench
-
Updated
Nov 18, 2021 - Python
QAT(quantize aware training) for classification with MQBench
🔪 Elimination based Lightweight Neural Net with Pretrained Weights
Efficient way to detect if a face has a mask on. Used EfficientNet-B0 model architecture.
American Sign Language Alphabet Detection in Real Time using OpenCV-Mediapipe with EfficientNetB0 in PyTorch
Development of a depth estimation model based on a UNET architecture - connection of Bi-directional Feature Pyramid Network (BIFPN) and EfficientNet.
Add a description, image, and links to the efficientnetb0 topic page so that developers can more easily learn about it.
To associate your repository with the efficientnetb0 topic, visit your repo's landing page and select "manage topics."