Advanced Computing (Record no. 87748)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 06819nam a22006735i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-56703-2 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730171704.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240325s2024 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783031567032 |
| -- | 978-3-031-56703-2 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 245 10 - TITLE STATEMENT | |
| Title | Advanced Computing |
| Sub Title | 13th International Conference, IACC 2023, Kolhapur, India, December 15-16, 2023, Revised Selected Papers, Part II / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XXVIII, 424 p. 210 illus., 183 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Communications in Computer and Information Science, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 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. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Data processing. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Digital techniques. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Garg, Deepak. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Rodrigues, Joel J. P. C. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Gupta, Suneet Kumar. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Cheng, Xiaochun. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Sarao, Pushpender. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Patel, Govind Singh. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-56703-2 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer Nature Switzerland : |
| -- | Imprint: Springer, |
| -- | 2024. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer networks . |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Application software. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Education |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Image processing |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer vision. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Engineering and Networks. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer and Information Systems Applications. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computers and Education. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Imaging, Vision, Pattern Recognition and Graphics. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 1865-0937 ; |
| 912 ## - | |
| -- | ZDB-2-SCS |
| 912 ## - | |
| -- | ZDB-2-SXCS |
No items available.