Ying Zhuge,1,* Zhi-Feng Zheng,1,* Mu-Qing Xie,2 Lin Li,2 Fang Wang,1 Feng Gao2,3 1Department of Cardiology, Shanghai First People’s Hospital of Nanjing Medical University, 2Department of Pharmaceutics, School of Pharmacy, 3Shanghai Key Laboratory of Functional Materials Chemistry, East China University of Science and Technology, Shanghai, Peo

The task of Text-to-Image synthesis is a difficult challenge, especially Guitar Accessories when dealing with low-data regimes, where the number of training samples is limited.In order to address this challenge, the Self-Supervision Text-to-Image Generative Adversarial Networks (SS-TiGAN) has been proposed.The method employs a bi-level architecture

Software solutions to address computational challenges are ubiquitous in our daily lives.One specific application area where software is often used is in embedded systems, which, like other digital electronic devices, are vulnerable to side-channel analysis attacks.Although masking is the most common countermeasure and provides a solid theoretical