Comprehensive Guide: Explores the challenges and solutions for face recognition in adverse conditions, including low light, motion blur, and facial occlusions.
Advanced Techniques: Covers state-of-the-art algorithms and techniques for robust face recognition, such as deep learning, image enhancement, and feature extraction.
Real-World Applications: Provides practical insights into the use of face recognition in security, surveillance, and other real-world scenarios.
Case Studies and Examples: Includes case studies and examples to illustrate the effectiveness of different face recognition methods in adverse conditions.
* Authoritative Reference: Written by leading experts in the field, providing a comprehensive and authoritative resource for researchers, practitioners, and students.