A vision encoder is a necessary component for allowing many leading LLMs to be able to work with images uploaded by users.

Subsequently, we detail the architecture ... MRI images, this image generation-based approach offers more universality and effectively addresses issues of data sparsity and label imbalance. By ...

But current AMD classification ... ensemble-based architecture was shown in Figure 5. All experiments were conducted in Pytorch and the hardware was composed of 64 hyper-thread processors, 8 × RTX ...

Abstract: Unlike other deep learning (DL) models, Transformer has the ability to extract long-range dependency features from hyperspectral image (HSI) data. Masked autoencoder (MAE), which is based on ...

In particular, we present a diffusion-model-based architecture that leverages text conditioning during training while being class-aware, to best preserve the crucial details of the ships during the ...

They have been used in various applications such as image classification, object detection, semantic segmentation, and image generation. Overall, the Vision Transformer model is a novel and powerful ...