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Data driven approach towards disruptive technologies : proceedings of MIDAS 2020 / / T. P. Singh [and four others] editors
Data driven approach towards disruptive technologies : proceedings of MIDAS 2020 / / T. P. Singh [and four others] editors
Pubbl/distr/stampa Singapore : , : Springer, , [2021]
Descrizione fisica 1 online resource (586 pages)
Disciplina 006.3
Collana Studies in Autonomic, Data-driven and Industrial Computing
Soggetto topico Artificial intelligence
Artificial intelligence - Mathematics
Intel·ligència artificial
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 981-15-9873-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910484814703321
Singapore : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data Driven Approach Towards Disruptive Technologies : Proceedings of MIDAS 2020 / / edited by T P Singh, Ravi Tomar, Tanupriya Choudhury, Thinagaran Perumal, Hussain Falih Mahdi
Data Driven Approach Towards Disruptive Technologies : Proceedings of MIDAS 2020 / / edited by T P Singh, Ravi Tomar, Tanupriya Choudhury, Thinagaran Perumal, Hussain Falih Mahdi
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (586 pages)
Disciplina 006.3
Collana Studies in Autonomic, Data-driven and Industrial Computing
Soggetto topico Computational intelligence
Data protection
Machine learning
Artificial intelligence
Computational Intelligence
Data and Information Security
Machine Learning
Artificial Intelligence
ISBN 981-15-9873-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1. Design and Fabrication of Hybrid Land-Air Vehicle -- Chapter 2. Pixel Value Differencing of Image Steganography in Substitution Technique : A Survey -- Chapter 3. Newspaper Text Recognition Printed in Gurumukhi Script: SVM vs. MLP -- Chapter 4. Bound Constructive Fraud and Implementing Dual Accessibility Approach on Biometric Credit/Debit Cards -- Chapter 5. Automatic dimension detection of fish images -- Chapter 6. Privacy-Preserving of Cloud Storage Security -- Chapter 7. Mitigating Security Challenges in Smart Home Management Through Smart Lock -- Chapter 7. Quality efficiency of VoIP application using Hybrid Co-ordination Function -- Chapter 8. A Review of Algorithms for Secure Data Transmission in IoT Devices -- Chapter 9. The new phase of manufacturing: industry 4.0 -- Chapter 10. Summarization and Analysis of text using Network Theory.
Record Nr. UNINA-9910863274503321
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Deep Learning Technologies for the Sustainable Development Goals [[electronic resource] ] : Issues and Solutions in the Post-COVID Era / / edited by Virender Kadyan, T. P. Singh, Chidiebere Ugwu
Deep Learning Technologies for the Sustainable Development Goals [[electronic resource] ] : Issues and Solutions in the Post-COVID Era / / edited by Virender Kadyan, T. P. Singh, Chidiebere Ugwu
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (254 pages)
Disciplina 006.31
Collana Advanced Technologies and Societal Change
Soggetto topico Computational intelligence
Blockchains (Databases)
Sustainability
Quantitative research
Artificial intelligence
Internet of things
Computational Intelligence
Blockchain
Data Analysis and Big Data
Artificial Intelligence
Internet of Things
ISBN 981-19-5723-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNISA-996546845303316
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Deep Learning Technologies for the Sustainable Development Goals : Issues and Solutions in the Post-COVID Era / / edited by Virender Kadyan, T. P. Singh, Chidiebere Ugwu
Deep Learning Technologies for the Sustainable Development Goals : Issues and Solutions in the Post-COVID Era / / edited by Virender Kadyan, T. P. Singh, Chidiebere Ugwu
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (254 pages)
Disciplina 006.31
Collana Advanced Technologies and Societal Change
Soggetto topico Computational intelligence
Blockchains (Databases)
Sustainability
Quantitative research
Artificial intelligence
Internet of things
Computational Intelligence
Blockchain
Data Analysis and Big Data
Artificial Intelligence
Internet of Things
ISBN 9789811957239
9811957231
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNINA-9910647778103321
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Geo-intelligence for sustainable development / / T.P. Singh, Dharmaveer Singh, R.B. Singh, editors
Geo-intelligence for sustainable development / / T.P. Singh, Dharmaveer Singh, R.B. Singh, editors
Pubbl/distr/stampa Singapore : , : Springer, , [2021]
Descrizione fisica 1 online resource (237 pages)
Disciplina 338.9270285
Collana Advances in geographical and environmental sciences
Soggetto topico Sustainable development - Data processing
ISBN 981-16-4768-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910502975903321
Singapore : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui