Buch, Englisch, Band 676, 731 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1262 g
NICE-DT 2023
Buch, Englisch, Band 676, 731 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1262 g
Reihe: Lecture Notes in Networks and Systems
ISBN: 978-981-99-1698-6
Verlag: Springer Nature Singapore
The book presents selected papers from NIELIT's International Conference on Communication, Electronics and Digital Technology (NICE-DT 2023) held during February 10–11, 2023, in New Delhi, India. The book covers state-of-the-art research insights on artificial intelligence, machine learning, big data, data analytics, cyber security and forensic, network and mobile security, advance computing, cloud computing, quantum computing, VLSI and semiconductors, electronics system, Internet of Things, robotics and automations, blockchain and software technology, digital technologies for future, assistive technology for divyangjan (people with disabilities) and Strategy for Digital Skilling for building a global Future Ready workforce.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
- Mathematik | Informatik EDV | Informatik Angewandte Informatik
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
Weitere Infos & Material
Quality of Service (QoS)-driven Edge Computing and Smart Hospitals: A Vision, Architectural Elements and Future Directions.- Real Time Face Mask Detector with Multi-class Classification using Deep Neural Networks.- Data Correlation Analysis to Curb Road Accidents.- Speech Recognition via Machine Learning in Recording Studio.- Clustering-Based Filter Pruning Approach for Efficient ConvNets.- SMS and E-mail Spam Classification using Natural Language Processing and Machine Learning.- Detecting Malware in Windows Environment Using Machine Learning.- Fake News Detection using LSTM Based Deep Learning Approach and Word Embedding Feature Extraction.- Safe Distance Monitoring for COVID-19 Using YOLOv3 Object Recognition Paradigm.- Machine Learning Based Depth of Anesthesia Estimation using Spectral and Statistical Features of EEG.