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Computer Vision and Machine Learning in Agriculture, Volume 2

Computer Vision and Machine Learning in Agriculture, Volume 2

Hardcover

Series: Algorithms for Intelligent Systems

Technology & EngineeringAgriculture

ISBN10: 9811699909
ISBN13: 9789811699900
Publisher: Springer Nature
Published: Mar 14 2022
Pages: 260
Weight: 1.24
Height: 0.69 Width: 6.14 Depth: 9.21
Language: English
Harvesting robots for smart agriculture.- Drone-based weed detection architectures using deep learning algorithms and real-time analytics.- A deep learning-based detection system of multi-class crops and orchards using a UAV.- Real-life agricultural data retrieval for large scale annotation flow optimization.- Design and analysis of IoT-based modern agriculture monitoring system for real time data collection.- Estimation of wheat yield based on precipitation and evapotranspiration using soft computing methods.- Coconut maturity recognition using convolutional neural network.- Agri food products quality assessment methods.- Medicinal plant recognition from leaf images using deep learning.- ESMO based plant leaf disease identification: A machine learning approach.- Deep learning-based cuali flower disease classification.- An Intelligent System for Crop Disease Identification and Dispersion Forecasting in SriLanka.- Apple leaves diseases detection using deep convolutional neural networks and transfer learning.- A deep learning paradigm for detection and segmentation of plant leaves diseases.- Early-stage prediction of plant leaf diseases using deep learning models.

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Uddin, Mohammad Shorif

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