SycoNet can generate multiple plausible synthetic composite images based on a real image and a foreground mask, which is useful to construct pairs of synthetic composite images and real images for ...

Superpixels, which segment an image into a set of closely spaced regions, can be employed in real-world scenarios to deal with non-homogeneous haze. In our paper, an adaptive non-homogeneous image ...

Abstract: Self-supervised contrastive learning is a powerful pretraining framework for learning the invariant features from the different views of remote sensing images, therefore, the performance of ...

Yes, it can! This is one facet of adaptive optics, which astronomical observatories can use to compensate for distortions in astronomical images caused by our atmosphere. Let’s set the stage ...

AI-powered language learning apps leverage advanced algorithms, natural language processing, and adaptive technologies to create tailored learning experiences. These innovative tools cater to various ...

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments ...

Look closely at this image, stripped of its caption, and join the moderated conversation about what you and other students see. By The Learning Network Look closely at this image, stripped of ...

To address the above issues, we, in this study, propose an adaptive detection method based on the color distribution characteristics of endoscopic images. The main contributions are summarized in the ...