Vishal M. Patel – författare

Compressed sensing or compressive sensing is a new concept in signal processing where one measures a small number of non-adaptive linear combinations of the signal.  These measurements are usually much smaller than the number of samples that define the signal.  From these small numbers of measurements, the signal is then reconstructed by non-linear procedure.  Compressed sensing has recently emerged as a powerful tool for efficiently processing data in non-traditional ways.  In this book, we highlight some of the key mathematical insights underlying sparse representation and compressed sensing and illustrate the role of these theories in classical vision, imaging and biometrics problems.

This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding, offering valuable insights from an international selection of experts in the field.

This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding, offering valuable insights from an international selection of experts in the field.

The book presents novel research in the areas of social identity and security when using mobile platforms.

The book presents novel research in the areas of social identity and security when using mobile platforms.

This book provides an overview of different deep learning-based methods for face recognition and related problems.

This book provides an overview of different deep learning-based methods for face recognition and related problems.

This book constitutes the proceedings of the First International Workshop on Emerging LLM/LMM Applications in Medical Imaging, ELAMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025. The 14 full papers were carefully reviewed and selected from 24 submissions. The conference covers all aspects of Healthcare, LLM, LMM, Medical Imaging, AI, Machine learning, and Multimodal.