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

Continuing progress in machine learning (ML) has led to significant advancements in
agricultural tasks. Due to its strong ability to extract high-dimensional features from fruit …

Deep learning-based visual object detection is a fundamental aspect of computer vision.
These models not only locate and classify multiple objects within an image, but they also …

In the complex environment of an orchard, changes in illumination, leaf occlusion, and fruit
overlap make it challenging for mobile picking robots to detect and locate oil-seed camellia …

Instance segmentation, an important image processing operation for automation in
agriculture, is used to precisely delineate individual objects of interest within images, which …

Abstract" Digital" agriculture is rapidly affecting the value of agricultural output. Robotic
picking of the ripe agricultural product enables accurate and rapid picking, making …

Precise detection and low-cost deployment are the technological basis of intelligent fruit
picking. This study proposes a lightweight improved YOLOv5s model to detect pitaya fruits in …

This paper presents a comprehensive review of emerging technologies for the internet of
things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and …

An intelligent transportation system (ITS) plays an important role in public transport
management, security and other issues. Traffic flow detection is an important part of the ITS …

Deep learning achieved high success of fruit-on-plant detection such as on apple. Most of
studies on apple detection identified all target fruits as one class regardless of fruit condition …