# Lightweight convolutional network

A computer vision model based on ConvNeXt-Tiny architecture, fine-tuned on specific datasets for image classification tasks

A self-supervised feature representation model based on ConvNeXt-V2, pre-trained using the Fully Convolutional Masked Autoencoder (FCMAE) framework, suitable for image feature extraction and fine-tuning tasks.

A self-supervised feature representation model based on ConvNeXt-V2, pre-trained using the Fully Convolutional Masked Autoencoder (FCMAE) framework.

A self-supervised feature representation model based on ConvNeXt-V2, pre-trained using the Fully Convolutional Masked Autoencoder (FCMAE) framework, suitable for image classification and feature extraction tasks.

This model is a fine-tuned version based on facebook/convnext-tiny-224, primarily used for image classification tasks, demonstrating excellent performance on the evaluation set.