LIMITED OFFER
Save 50% on book bundles
Immediately download your ebook while waiting for your print delivery. No promo code is needed.
Holiday book sale: Save up to 30% on print and eBooks. No promo code needed.
Save up to 30% on print and eBooks.
1st Edition - June 22, 2021
Editors: Arun Solanki, Anand Nayyar, Mohd Naved
Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative… Read more
LIMITED OFFER
Immediately download your ebook while waiting for your print delivery. No promo code is needed.
Biomedical Engineers and researchers in biomedical engineering, applied informatics, Artificial Intelligence, and data science. Students and researchers in data analytics, image processing, as well as computer scientists
1. Super-Resolution based GAN for Image Processing: Recent Advances and Future Trends
2. GAN models in Natural Language Processing and Image Translation
3. Generative Adversarial Networks and their variants
4. Comparative Analysis of Filtering Methods in Fuzzy C-Mean Environment for DICOM Image Segmentation
5. A Review on the Techniques for Generation of Images using GAN
6. A Review of Techniques to Detect the GAN Generated Fake Images
7. Synthesis of Respiratory Signals using Conditional Generative Adversarial Networks from Scalogram Representation
8. Visual Similarity-Based Fashion Recommendation System
9. Deep learning based vegetation index estimation
10. Image Generation using Generative Adversarial Networks
11. Generative Adversarial Networks for Histopathology Staining
12. ANALYSIS OF FALSE DATA DETECTION RATE IN GENERATIVE ADVERSARIAL NETWORKS USING RECURRENT NEURAL NETWORK
13. WGGAN: A Wavelet-Guided Generative Adversarial Network for Thermal Image Translation
14. GENERATIVE ADVERSARIAL NETWORK FOR VIDEO ANALYTICS
15. Multimodal reconstruction of retinal images over unpaired datasets using cyclical generative adversarial networks
16. Generative Adversarial Network for Video Anomaly Detection
AS
AN
MN
Dr. Mohd Naved is a machine learning consultant and researcher currently teaching in Amity University, Noida, India, for various degree programs in Analytics and Machine Learning. He is actively engaged in academic research on various topics in management as well as on 21st century technologies. He has published more than 30 research papers in reputed journals. He has 16 patents in AI/ML and actively engages in commercialization of innovative products developed at university level. His interview has been published in various national and international magazines. A former data scientist, he is an alumnus of Delhi University. He holds a PhD from Noida International University.