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E-raamat: Agriculture-Centric Computation: First International Conference, ICA 2023, Chandigarh, India, May 11-13, 2023, Revised Selected Papers

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Agriculture-Centric Computation: First International Conference, ICA 2023, Chandigarh, India, May 11-13, 2023, Revised Selected PapersSuurem pilt
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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.
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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