Deep Learning Technologies for the Sustainable Development Goals [E-Book] : Issues and Solutions in the Post-COVID Era / edited by Virender Kadyan, T. P. Singh, Chidiebere Ugwu.
This book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenge...
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Personal Name(s): | Kadyan, Virender, editor |
Singh, T. P., editor / Ugwu, Chidiebere, editor | |
Edition: |
1st edition 2023. |
Imprint: |
Singapore :
Springer,
2023
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Physical Description: |
XII, 246 pages 83 illustrations, 63 illustrations in color (online resource) |
Note: |
englisch |
ISBN: |
9789811957239 |
DOI: |
10.1007/978-981-19-5723-9 |
Series Title: |
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Advanced Technologies and Societal Change
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Subject (LOC): |
- How Deep Learning can help in Regulating the Subscription Economy to Ensure Sustainable Consumption and Production Patterns (12th goal of SDGs)
- Deep Technologies using Big Data in: Energy and Waste Management
- QoS aware service provisioning and resource distribution in 4G/5G heterogeneous networks
- Leveraging Fog Computing for Healthcare
- Intelligent self-tuning control design for wastewater treatment plant based on PID and Model Predictive methods
- Impact of Deep learning models for technology sustainability in tourism using Big data analytics
- Study of UAV Management Using Cloud Based Systems
- Contemporary Role of Blockchain in Industry 4.0
- SDGs Laid Down by UN 2030 Document
- Healthcare 4P: Systematic Review of Applications of Decentralized Trust using Blockchain Technology
- Implementation of An IOT Based Water And Disaster Management System By Using Hybrid Classification Approach
- Knowledge Representation to Expound Deep
- Learning Black Box
- Ann : Concept And Application In Brain Tumor Segmentation
- Automation Of Brain Tumor Segmentation Using Deep Learning
- Transportation Management using IoT Deep Learning to Predict various Traffic States.