Deep Learning in Visual Computing and Signal Processing

著者名：Singh, Krishna Kant (EDT)/Sachan, Vibhav Kumar (EDT)/Singh, Akansha (EDT)/Padmanaban, Sanjeevikumar (EDT)

Apple Academic Press（2022/10/20発売）

• 言語：ENG
• ISBN：9781774638712
• eISBN：9781000564884

Description

An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications, this new volume covers the fundamentals and advanced topics in designing and deploying techniques using deep architectures and their application in visual computing and signal processing.

The volume first lays out the fundamentals of deep learning as well as deep learning architectures and frameworks. It goes on to discuss deep learning in neural networks and deep learning for object recognition and detection models. It looks at the various specific applications of deep learning in visual and signal processing, such as in biorobotics, for automated brain tumor segmentation in MRI images, in neural networks for use in seizure classification, for digital forensic investigation based on deep learning, and more.

Table of Contents

1. Deep Learning Architecture and Framework 

Ashish Tripathi, Shraddha Upadhaya, Arun Kumar Singh, Krishna Kant Singh, Arush Jain, Pushpa Choudhary, and Prem Chand Vashist 

2. Deep Learning in Neural Networks: An Overview 

Vidit Shukla and Shilpa Choudhary 

3. Deep Learning: Current Trends and Techniques 

Bharti Sharma, Arun Balodi, Utku Kose, and Akansha Singh 

4. TensorFlow: Machine Learning Using Heterogeneous Edge on Distributed Systems 

R. Ganesh Babu, A. Nedumaran, G. Manikandan, and R. Selvameena 

5. Introduction to Biorobotics: Part of Biomedical Signal Processing 

Kashish Srivastava and Shilpa Choudhary 

6. Deep Learning-Based Object Recognition and Detection Model 

Aman Jatain, Khushboo Tripathi, and Shalini Bhaskar Bajaj 

7. Deep Learning: A Pathway for Automated Brain Tumor Segmentation in MRI Images 

Roohi Sille, Piyush Chauhan, and Durgansh Sharma 

8. Recurrent Neural Networks and Their Application in Seizure Classification 

Kusumika Krori Dutta, Poornima Sridharan, and Sunny Arokia Swamy Bellary 

9. Brain Tumor Classification Using Convolutional Neural Network 

M. Jayashree, Poornima Sridharan, V. Megala, and R. K. Pongiannan 

10. A Proactive Improvement Toward Digital Forensic Investigation Based on Deep Learning 

Vidushi, Akash Rajak, Ajay Kumar Shrivastava, and Arun Kumar Tripathi