Abstract Machine learning applications in agriculture will be covered to help increase
efficiencies at farm level. Artificial neural networks (ANNs) will be introduced for their ability …

This book is as an extension of the previous two volumes on “Computer Vision and Machine
Learning in Agriculture”. This volume 3 discusses solutions to the problems of agricultural …

In crop production, precision agriculture applications seek to deploy different devices and
systems to enhance yield and to reduce ecological impacts by optimizing inputs and timing …

Recently, agriculture has gained much attention regarding automation by artificial
intelligence techniques and robotic systems. Particularly, with the advancements in machine …

The agricultural sector is crucial for sustaining human civilization by providing food, fiber,
and raw materials. Technological advancements have revolutionized agriculture, with …

The advent of cutting-edge techniques such as Computer Vision (CV) and Artificial
Intelligence (AI) have sparked a revolution in the agricultural industry, with applications …

The exponential growth in the world population has led to an ever-increasing demand for
food supplies. This has led to the realization that conventional and traditional methods alone …

Convolutional neural networks (CNNs) are deep learning algorithms that are particularly
useful for analyzing and interpreting images. This chapter introduces fundamental concepts …

Machine learning has emerged with big data technologies and high-performance computing
to create new opportunities for data intensive science in the multi-disciplinary agri …

This study examines the transformative role of deep learning algorithms in agricultural
monitoring and management. Deep learning has shown remarkable progress in predicting …