Iris and Periocular Recognition using Deep Learning 1st Edition

Iris and Periocular Recognition using Deep Learning 1st Edition by Ajay Kumar is an authoritative, contemporary guide for anyone advancing biometric systems with state-of-the-art deep learning. This clear, richly illustrated volume captures the fast-evolving science of iris and periocular recognition—bridging theory, practical implementation, and real-world deployment.

Discover how modern convolutional and transformer-based architectures are tailored to the unique challenges of ocular biometrics: variable illumination, occlusion, off-angle captures and mobile-camera noise. The book walks readers through dataset selection, preprocessing, feature extraction, network training, performance metrics and robust evaluation protocols, making complex concepts accessible to engineers, researchers, and security professionals.

What sets this edition apart is its pragmatic focus on applications—secure authentication, border control, surveillance, and healthcare ID systems—illustrated with case studies that resonate with teams across academia and industry worldwide. Whether you’re building solutions for high-throughput checkpoints in Europe, mobile authentication in Asia, or research labs in North America, the techniques and best practices presented here scale to diverse environments and regulatory contexts.

Readable yet rigorous, this book equips you with reproducible workflows, optimization tips, and a forward-looking view of multimodal biometric fusion. If you value precision, reliability, and cutting-edge performance in ocular recognition, add this essential resource to your library.

Order your copy today and elevate your biometric projects with practical deep-learning expertise from Ajay Kumar.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.