Computer Vision and Machine Learning in Agriculture, Volume 2

Computer Vision and Machine Learning in Agriculture, Volume 2

Bansal, Jagdish Chand; Uddin, Mohammad Shorif

Springer Verlag, Singapore

03/2022

260

Dura

Inglês

9789811699900

15 a 20 dias

582

Descrição não disponível.
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 networksand 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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Precision Agriculture;Machine Learning and Deep Learning Tools and Techniques;Disease Detection;Plant Recognition;Production Yield, Product Quality and Defect Assessment;Applications of Agricultural Robots and Drones;Computer Vision