In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

The research on intelligent fault diagnosis has yielded remarkable achievements based on
artificial intelligence-related technologies. In engineering scenarios, machines usually work …

Globally, there is a huge unmet need for effective treatments for neurodegenerative
diseases. The complexity of the molecular mechanisms underlying neuronal degeneration …

Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

With the rapid progress in recent years, techniques that generate and manipulate
multimedia content can now provide a very advanced level of realism. The boundary …

What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …

Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

While the quality of GAN image synthesis has improved tremendously in recent years, our
ability to control and condition the output is still limited. Focusing on StyleGAN, we introduce …

Acquiring images of the same anatomy with multiple different contrasts increases the
diversity of diagnostic information available in an MR exam. Yet, the scan time limitations …

In recent years, significant progress has been made in developing more accurate and
efficient machine learning algorithms for segmentation of medical and natural images. In this …