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Agriculture-Centric Computation First International Conference, ICA 2023, Chandigarh, India, May 11-13, 2023, Revised Selected Papers
Title
Agriculture-Centric Computation [electronic resource] : First International Conference, ICA 2023, Chandigarh, India, May 11-13, 2023, Revised Selected Papers / edited by Mukesh Kumar Saini, Neeraj Goel, Hanumant Singh Shekhawat, Jaime Lloret Mauri, Dhananjay Singh.
ISBN
9783031436055
Edition
1st ed. 2023.
Publication
Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Physical Description
XII, 254 p. 96 illus., 75 illus. in color.
Local Notes
Access is available to the Yale community.
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Access restricted by licensing agreement.
Summary
This book constitutes revised selected papers from the First International Conference on Agriculture-Centric Computation, ICA 2023, held in Chandigarh, India, in May 2023. The 18 papers were thoroughly reviewed and selected from the 52 submissions. They examine how computing disciplines such as big data analytics, artificial intelligence, machine learning, the Internet of Things (IoT), remote sensing, robotics, and drones can be applied to agriculture to address some of the biggest challenges facing the industry today, including climate change, food security, and environmental sustainability.
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Springer ENIN.
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Format
Books / Online
Language
English
Added to Catalog
October 03, 2023
Series
Communications in Computer and Information Science, 1866
Contents
Fine Tuned Single Shot Detector for Finding Disease Patches in Leaves
Empirical Analysis and Evaluation of Factors Influencing Adoption of AI-based Automation Solutions for Sustainable Agriculture
FusedNet Model for Varietal Classification of Rice Seeds
Fertilizer Recommendation using Ensemble Filter-based Feature Selection Approach
Privacy-Preserving Pest Detection Using Personalized Federated Learning
A review on applications of artificial intelligence for identifying soil nutrients
IRPD: In-Field Radish Plant Dataset
Fast Rotated Bounding Box Annotations for Object Detection
IndianPotatoWeeds: An Image Dataset of Potato Crop to Address Weed Issues in Precision Agriculture
Estimation Of Leaf Parameters in Punjab Region Through Multi-Spectral Drone Images using Deep Learning Models
Application of near-infrared (NIR) hyperspectral imaging system for protein content prediction in chickpea flour
Classification of crops based on band quality and redundancy from hyperspectral image
Automated Agriculture News Collection, Analysis, and Recommendation
Intelligent Chatbot Assistant in Agriculture Domain
Machine Learning Methods for Crop Yield Prediction
Real-time Plant Disease Detection: A Comparative Study
Fruit Segregation using Deep Learning
Investigation of the bulk and electronic properties of boron/nitrogen/indium doped armchair graphene nanoribbon for sensing plant VOC: A DFT study.
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