Volume 1. Introduction to Computer Vision and Machine Learning Applications in Agriculture
Robots and Drones in Agriculture: A Survey
Detection of Rotten Fruits and Vegetables using Deep Learning
Deep Learning-Based Essential Paddy Pests Filtration Technique: A Better Economic Damage Management Process
Deep CNN-Based Mango Insect Classification
Implementation of a Deep Convolutional Neural Network for the Detection of Tomato Leaf Diseases
A Multi-Plant Disease Diagnosis Method using Convolutional Neural Network
A Deep Learning-Based Approach for Potato Diseases Classification
An In-Depth Analysis of Different Segmentation Techniques in Automated Local Fruit Disease Recognition
Machine Vision Based Fruit and Vegetable Disease Recognition: A Review
An Efficient Bag-of-Features for Diseased Plant Identification.

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 Cauliflower Disease Classification
An Intelligent System for Crop Disease Identification and Dispersion Forecasting in Sri Lanka
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.