Abstract Generative Adversarial Networks (GANs) have been extremely successful in
various application domains such as computer vision, medicine, and natural language …

Text‐to‐image synthesis refers to computational methods which translate human written
textual descriptions, in the form of keywords or sentences, into images with similar semantic …

Accurate Computer-Assisted Diagnosis, relying on large-scale annotated pathological
images, can alleviate the risk of overlooking the diagnosis. Unfortunately, in medical …

A number of machine learning methods have been recently proposed to circumvent the high
computational cost of the gradient-based topology optimization solvers. By and large, these …

Story visualization (SV) is a challenging text-to-image generation task for the difficulty of not
only rendering visual details from the text descriptions but also encoding a longterm context …

The task of text-to-image synthesis is a new challenge in the field of image synthesis. In the
earlier research, the task of text-to-image synthesis is mainly to achieve the alignment of …

Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …

Due to the trending need of building autonomous robotic perception system, sensor fusion
has attracted a lot of attention amongst researchers and engineers to make best use of cross …

The advancements in artificial intelligence research, particularly in computer vision, have led
to the development of previously unimaginable applications, such as generating new …

In machine learning, a generative model is responsible for generating new samples of data
in terms of a probabilistic model. Generative adversarial network (GAN) has been widely …