Multimodality Imaging: Deep learning applications. Volume 1

Multimodality Imaging, Volume 1: Deep le

📁 Multimodality Imaging, Volume 1: Deep learning applications

✍ Mainak Biswas, Jasjit S. Suri 📂 Library 📅 2022 🏛 IOP Publishing 🌐 English

This research and reference text explores the finer details of deep learning models. It provides a brief outline on popular models including convolution neural networks, deep belief networks, autoencoders and residual neural networks. The text discusses some of the deep learning-based applications i

Multimodality Imaging: Deep learning app

📁 Multimodality Imaging: Deep learning applications. Volume 1

✍ Jasjit S. Suri; Mainak Biswas 📂 Library 📅 2022 🌐 English

This research and reference text explores the finer details of deep learning models. It provides a brief outline on popular models including convolution neural networks, deep belief networks, autoencoders and residual neural networks.

Deep learning for image processing appli

📁 Deep learning for image processing applications

✍ Estrela, Vania Vieira; Hemanth, D. Jude (eds.) 📂 Library 📅 2017 🏛 IOS Press 🌐 English

Deep Learning Applications in Image Anal

📁 Deep Learning Applications in Image Analysis

✍ Sanjiban Sekhar Roy, Ching-Hsien Hsu, Venkateshwara Kagita 📂 Library 📅 2023 🏛 Springer 🌐 English

This book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry

Multimodal Scene Understanding: Algorith

📁 Multimodal Scene Understanding: Algorithms, Applications and Deep Learning

✍ Michael Ying Yang (editor), Bodo Rosenhahn (editor), Vittorio Murino (editor) 📂 Library 📅 2019 🏛 Academic Press 🌐 English

Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and de

Deep Learning Applications, Volume 4

📁 Deep Learning Applications, Volume 4

✍ M. Arif Wani, Vasile Palade 📂 Library 📅 2023 🏛 Springer 🌐 English

This book presents a compilation of extended versions of selected papers from 20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2021). It focuses on deep learning networks and their applications in domains such as healthcare, security and threat detection,

Multimodality Imaging: Deep learning applications. Volume 1

✦ Synopsis