Atjaunināt sīkdatņu piekrišanu

E-grāmata: Advanced Network Technologies and Intelligent Computing: Third International Conference, ANTIC 2023, Varanasi, India, December 20-22, 2023, Proceedings, Part III

Edited by , Edited by , Edited by , Edited by , Edited by
  • Formāts - EPUB+DRM
  • Cena: 77,31 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

The 4-volume proceedings set CCIS 2090, 2091,2092 and 2093 constitute the refereed post-conference proceedings of the Third International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2023, held in Varanasi, India, during December 20-22, 2023.





The 87 full papers and 11 short papers included in this book were carefully reviewed and selected from 487 submissions. The conference papers are organized in topical sections on: 





Part I - Advanced Network Technologies.





Part II - Advanced Network Technologies; Intelligent Computing.





Part III- IV - Intelligent Computing.
.- Intelligent Computing.

.- Implementation and Performance Evaluation of Deep Learning Models for
Disease Classification and Severity Estimation of Coffee Leaves.

.- Flow-Optimized Channel-Attentive Excitation DenseNet Algorithm for
Multi-Disease Classification and Severity Estimation.

.- Image Captioning using Deep Learning.

.- Visualizing Optimal Classifiers in EEG-Based Sleepy Driver Prediction.

.- Revolutionizing Glaucoma Diagnosis with a Hybrid AI Algorithm.

.- Unravelling Crop Yield Secrets Through Identification of Significant
Factors Using Machine Learning.

.- Comparative Analysis of Short-Term Load Forecasting Using K-Nearest
Neighbor, Random Forest, and Gradient Boost Models.

.- Heuristics for Influence Maximization with Tiered Influence and Activation
thresholds.

.- Sentiment Analysis and Offensive Language Identification In Code-Mixed
Tamil-English Languages Using Transformer-based Models.

.- Performance evaluation of Deep Transfer Learning and Semantic Segmentation
models for crop and weed detection in the Sesame Production System.

.- Machine Learning Analysis on Hate Speech against Asians.

.- Deep Transfer Learning for Enhanced Blackgram Disease Detection: A
Transfer Learning - Driven Approach.

.- Sustainable Natural Gas Price Forecasting with DEEPAR.

.- Whale Optimized Deep Learning Technique for Accurate Skin Cancer
Identification.

.- Multi-Domain Feature Extraction Methods for Classification of Human
Emotions from Electroencephalography (EEG) Signals.

.- Enhancing Speech Quality using Spectral Subtraction and Time-Frequency
Filtering.

.- Analyzing the performance of BERT for the sentiment classification task in
Bengali text.

.- Students Performance Prediction using Decision Tree Regressor.

.- A Comprehensive Analysis on Features and Performance Evaluation Metrics in
Audio-Visual Voice Conversion.

.- Time Series Analytic Models for Forecasting Vehicular Registration Volume
in the Indian Context.

.- Impact of Clinical Features on Disease Diagnosis using Knowledge Graph
Embedding and Machine Learning: a Detailed Analysis.

.- Advancements in Alzheimer's Disease Diagnosis: The MRI-CNN Synergy for
Early Detection.

.- Drinking Addiction Predictive Model Using Body  Characteristics Machine
Learning Approach.

.- An Ensemble of Machine Learning Models Utilizing Deep Convolutional
Features for Medical Image Classification.