Hash Code

Hashing techniques map high-dimensional data into compact binary codes, enabling efficient similarity search and data compression. Current research focuses on improving hashing's accuracy and efficiency through deep learning architectures, particularly exploring federated learning for privacy-preserving applications and incorporating semantic information for better generalization. These advancements are crucial for various applications, including large-scale image and audio retrieval, recommendation systems, and even privacy-preserving benchmarks for sensitive AI evaluations, highlighting the growing importance of robust and efficient hashing methods.