https://www.selleckchem.com/pr....oducts/alkbh5-inhibi
Compared to the ResNet-50 model, the small shallow custom-built model had higher training (99.7%) and validation (99.1%) accuracies. When tested with new tick image data, the shallow custom-built model yielded higher mean prediction accuracy (80%), greater confidence of true detection (88.7%) and lower mean response time (3.64 s). These results demonstrate that, with limited data size for model training, a simple shallow custom-built CNN model has great prospects for use in the classification of common hard ticks present in a
Like
Comment
Share
