AIPollen

For the development of pollen identification model, We employed ResNet34 as the pretrained model. After 203 epochs, the model achieved an impressive accuracy rate of 97.01% on the test set and 99.89% on the training sets, indicating its ability to correctly classify the majority of pollen images.

AIpollen platform offers a streamlined and intuitive interface, allowing users to easily classify pollen images. Users simply need to upload a pollen image by SEM or TEM with PNG, JPG, or TIFF format. Once uploaded, the image is processed by our pollen classification model hosted on the server.