In the context of big data, the exploration of the application effect of machine learning in
intelligent encryption for real-time image text digital information aims to improve the privacy …

Balancing privacy and predictive utility remains a central challenge for machine learning in
healthcare. In this paper, we develop Syfer, a neural obfuscation method to protect against …

As machine and deep learning spread across diverse aspects of our society, the concerns
about the privacy of the data are getting stronger, particularly in scenarios where sensitive …

Image recognition is one of the core research directions in the field of computer vision
research, which can be divided into general image recognition and fine‐grained image …

Improving people's secrecy and data security is the goal of investigating the real-world use
of machine learning for intelligent encryption of real-time picture text digital information in the …

Language models have become ubiquitous in natural language processing, leveraging
large amounts of unlabeled data and fine-tuning for downstream tasks. However, concerns …

While AI has the potential to transform patient care, the development of equitable clinical AI
models and their translation to hospitals remains difficult. From a computational perspective …

Deep learning is widely used in artificial intelligence fields such as computer vision, natural
language recognition, and intelligent robots. With the development of deep learning …

Recently, with personal information being increasingly used in several applications, its
leakage and resulting damage have become a relevant concern. In video data, only people …

Privacy preservation is always a potential concern while storing or transmitting images with
sensitive information within them. A review of existing privacy preservation techniques …