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Artificial Intelligence Based Smart and Secured Applications Third International Conference, ASCIS 2024, Rajkot, India, October 16–18, 2024, Revised Selected Papers, Part II

Aus der Reihe Communications in Computer and Information Science
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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.04.2025

Abbildungen

LIII, 446 p. 299 illus., 237 illus. in color.

Herausgeber

Sridaran Rajagopal + weitere

Verlag

Springer

Seitenzahl

446

Maße (L/B/H)

23,5/15,5/2,7 cm

Gewicht

750 g

Sprache

Englisch

ISBN

978-3-031-86292-2

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.04.2025

Abbildungen

LIII, 446 p. 299 illus., 237 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

446

Maße (L/B/H)

23,5/15,5/2,7 cm

Gewicht

750 g

Sprache

Englisch

ISBN

978-3-031-86292-2

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Artificial Intelligence Based Smart and Secured Applications
  • Produktbild: Artificial Intelligence Based Smart and Secured Applications

  • .- Artificial Intelligence & Machine Learning.



    .- Enhanced Locomotive Delay Prediction Using Machine Learning with Modified Z-Score and Lasso Regression.



    .- Hybrid Deep Learning Models for Real-Time Melanoma Classification Using Mobile Imaging.



    .- Geometrically Innovated Machine Learning for Optimized Prediction of Rice Blast Disease.



    .- An Optimized Hybrid Deep Learning Framework For Intrusion Detection System Integration.



    .- Efficient Palm Print Identification Using Various Machine Learning Approaches.



    .- Diabetes Prediction using Convolutional Neural Networks and Long Short Term Memory Techniques.



    .- Image Classification and Detection of Artificial Images using CNN Models.



    .- Mutual Information-Driven Ant Lion Optimizer for Enhanced Feature Selection in Colorectal Cancer Detection.



    .- Optimized Deep Belief Network for Colorectal Cancer Detection Using Hybrid PIO-DE Algorithm.



    .- Advanced Lung Image Enhancement Using Dynamic Dual-Histogram Gamma Correction.



    .- Anthology Of ML Based Data Science Applications.



    .- MACHINE LEARNING APPROCHES FOR THE PREDICTION OF DIABETES.



    .- MACHINE LEARNING APPROACHES FOR LUNG CANCER PREDICTION.



    .- Exploring Advanced Ensemble Learning Strategies in Machine Learning and Data Mining for Predictive Modeling of Marathon Running  Time.



    .- Performance comparative analysis of recurrent neural network for osteoporosis disease prediction.



    .- Image Splicing Detection: A Deep Learning based Approach.



    .- Artificial Intelligence-Driven Insights into the Indian Mutual Fund Industry: A Pre and Post-COVID Comparative Study.



    .- Evaluating the Evaluation of India’s Mutual Fund Industry: Ways to Enhance by AI.



    .- Transformative Influence: AI's Application in Improving Risk Prevention and Management in Banking Institutions.



    .- Exploratory Data Analysis for online Advertisement CTR prediction using Machine Learning.



    .- Fake News Classification using Feature based hybrid Deep Learning.



    .- Performance Evaluation of Deep Learning Models for the Classification of Lung Diseases in  X-Ray Images.



    .- Advanced Predictive Analytics for Early Detection of Chronic Kidney Disease using ML Models.



    .- Enhanced Prediction of Chronic Kidney Disease Using K-Nearest Neighbors with Various Pre-processing Techniques.



    .- Heart Disease Prediction using Logistic Regression with PCA-MFSA Feature Extraction Technique and Multidimensional Scaling (MDS) Pre-Processing Approach.



    .- Deep Learning Approaches for Diabetic Retinopathy- A Study.


    .- Detection of Optical problem in retinal Fundus images using AI Based deep learning method.



    .- Deep Learning-Based Risk Stratification for Chronic Kidney Disease Patients.



    .- Enhanced Feature Selection for Chronic Kidney Disease Detection: A Hybrid Integration of Simulated Annealing and Recursive Feature Elimination.



    .- A Survey on Artificial Intelligence Models for Endometrial Tumor Detection, Classification and Diagnosis.



    .- Implementation of Deep Learning Approaches for Defect Detection in Ceramic Tiles.