Hybrid Soft Computing for Multilevel Image and Data Segmentation by Sourav De
This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures.
This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.
-
Data-Driven Waste Revolution
-
Hesitant Fuzzy Set
-
Metaheuristics for Machine Learning
-
Intelligent Automation in Renewable Energy
-
Intelligent Computing in Carcinogenic Disease Detection
-
Neural Networks with Model Compression
-
Construct, Merge, Solve & Adapt
-
Advanced Spiking Neural P Systems
-
Decision Support for Product Development
-
Advanced Machine Learning with Evolutionary and Metaheuristic Techniques
-
Explainable AI in Health Informatics
-
Applied Deep Learning
| SKU | Unavailable |
| ISBN 13 | |
| ISBN 10 | |
| Title | Hybrid Soft Computing for Multilevel Image and Data Segmentation |
| Author | Sourav De |
| Series | |
| Condition | Unavailable |
| Binding Type | |
| Publisher | |
| Year published | |
| Number of pages | |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |
View All Editions
Filter
Applied Filters (0)
Sort by:
Loading editions...