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Advanced Computing 13th International Conference, IACC 2023, Kolhapur, India, December 15-16, 2023, Revised Selected Papers, Part II
Title
Advanced Computing [electronic resource] : 13th International Conference, IACC 2023, Kolhapur, India, December 15-16, 2023, Revised Selected Papers, Part II / edited by Deepak Garg, Joel J. P. C. Rodrigues, Suneet Kumar Gupta, Xiaochun Cheng, Pushpender Sarao, Govind Singh Patel.
ISBN
9783031567032
Edition
1st ed. 2024.
Publication
Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Physical Description
1 online resource (XXVIII, 424 p.) 210 illus., 183 illus. in color.
Local Notes
Access is available to the Yale community.
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Access restricted by licensing agreement.
Summary
The two-volume set CCIS 2053 and 2054 constitutes the refereed post-conference proceedings of the 13th International Advanced Computing Conference, IACC 2023, held in Kolhapur, India, during December 15-16, 2023. The 66 full papers and 6 short papers presented in these proceedings were carefully reviewed and selected from 425 submissions. The papers are organized in the following topical sections: Volume I: The AI renaissance: a new era of human-machine collaboration; application of recurrent neural network in natural language processing, AI content detection and time series data analysis; unveiling the next frontier of AI advancement. Volume II: Agricultural resilience and disaster management for sustainable harvest; disease and abnormalities detection using ML and IOT; application of deep learning in healthcare; cancer detection using AI.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
April 10, 2024
Series
Communications in Computer and Information Science, 2054
Contents
Agricultural Resilience and Disaster Management for Sustainable Harvest
Plant Disease Recognition using Machine Learning and Deep Learning Classifiers
Securing Lives and Assets: IoT-Based Earthquake and Fire Detection for Real-Time Monitoring and Safety
An Early Detection of Fall Using Knowledge Distillation Ensemble Prediction Using Classification
Deep Learning Methods for Precise Sugarcane Disease Detection and Sustainable Crop Management
An Interactive Interface for Plant Disease Prediction and Remedy Recommendation
Tilapia Fish Freshness Detection using CNN Models
Chilli Leaf Disease Detection using Deep Learning
Damage Evaluation Following Natural Disasters Using Deep Learning
Total Electron Content Forecasting in Low Latitude Regions of India: Machine & Deep Learning Synergy
Disease and Abnormalities Detection using ML and IOT
Early Phase Detection of Diabetes Mellitus Using Machine Learning
Diabetes Risk Prediction through Fine-Tuned Gradient Boosting
Early Detection of Diabetes using ML-based Classification Algorithms
Prediction Of Abnormality Using IoT and Machine Learning
Detection of Cardiovascular Diseases using Machine Learning Approach
Mild Cognitive Impairment Diagnosis Using Neuropsychological Tests and Agile Machine Learning
Heart Disease Diagnosis using Machine Learning Classifiers
Comparative Evaluation of Feature Extraction Techniques in Chest X Ray Image with Different Classification Model
Application of Deep Learning in Healthcare
Transfer Learning Approach for Differentiating Parkinson's Syndromes using Voice Recordings
Detection of Brain Tumor Type Based on FANET Segmentation and Hybrid Squeeze Excitation Network with KNN
Mental Health Analysis using Rasa and Bert: Mindful
Kidney Failure Identification using Augment Intelligence and IOT Based on Integrated Healthcare System
Efficient Characterization of Cough Sounds Using Statistical Analysis
An Efficient Method for Heart Failure Diagnosis
Novel Machine Learning Algorithms for Predicting COVID-19 Clinical Outcomes with Gender Analysis
A Genetic Algorithm-Enhanced Deep Neural Network for Efficient and Optimized Brain Tumor Detection
Diabetes Prediction using Ensemble Learning
Cancer Detection Using AI
A Predictive Deep Learning Ensemble Based Approach for Advanced Cancer Classification
Predictive Deep Learning: An Analysis of Inception V3, VGG16, and VGG19 Models for Breast Cancer Detection
Innovation in the Field of Oncology: Early Lung Cancer Detection and Classification using AI
Colon Cancer Nuclei Classification with Convolutional Neural Networks
Genetic Algorithm-based Optimization of UNet for Breast Cancer Classification: A Lightweight and Efficient approach for IoT Devices
Classification of Colorectal Cancer Tissue Utilizing Machine Learning Algorithms
Prediction of Breast Cancer using Machine Learning Technique.
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