A zero-shot learning framework for maize cob phenotyping

A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric ...
IEEE

Multi-Layer Feature Extraction Object Detection Based on Deep Forest

Abstract: With the emergence of various large-scale deep learning models, in remote sensing images, the object detection effect is also plagued by complex calculations, high costs, and high ...
Scientific Research Publishing

Arnal Barbedo, J.G. (2019) Plant Disease Identification from Individual Lesions and Spots Using Deep Learning. Biosystems Engineering, 180, 96-107.

ABSTRACT: Timely and accurate detection of plant diseases is essential for improving crop yields and ensuring food security, particularly in regions like Cameroon, where farmers often rely on visual ...
Scientific Research Publishing

YOLO-AgriNet: A Deep Learning-Based Model for Real-Time Plant Disease Detection in Precision Agriculture ()

1 Ambam Computer Science and Application Laboratory & Department of Computer Engineering, Higher Institute of Transport, Logistics and Commerce, University of Ebolowa, Ebolowa, Cameroon. 2 Institut ...
IEEE

A Deep Learning-Based Method for Object Workpiece Recognition and Grasp Detection

Abstract: Accurate and stable target detection is crucial for robotic grasping tasks under uneven lighting conditions. To address this, this paper proposes a target object detection network (YOLO-Net) ...
Frontiers

YOLO-ODD: an improved YOLOv8s model for onion foliar disease detection

Onion crops are affected by many diseases at different stages of growth, resulting in significant yield loss. The early detection of diseases helps in the timely incorporation of management practices, ...