Computer Vision and Machine Learning in Agriculture, Volume 2

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.

• Format: Hardcover
• Language: English
• ISBN: 9811699909
• ISBN13: 9789811699900
• Release Date: March 2022
• Publisher: Springer
• Length: 260 Pages
• Weight: 1.24 lbs.
• Dimensions: 0.7" x 6.1" x 9.2"