This review article provides a comprehensive examination of the state-of-the-art in maize
disease detection leveraging Convolutional Neural Networks (CNNs). Beginning with the …

Accurate categorization and timely control of leaf diseases are crucial for citrus growth. We
proposed the Multi-Models Fusion Network (MMFN) for citrus leaf diseases detection based …

Significant accomplishments in many agricultural applications during the past decade attest
to the fast progress and use of deep learning and machine learning methods in agricultural …

Maize (Zea mays L.) has been shown to be sensitive to temperature deviations, influencing
its yield potential. The development of new maize hybrids resilient to unfavourable weather …

Robotically selective broccoli harvesting requires precise lightweight detection models to
efficiently detect broccoli heads. Therefore, this study introduces a lightweight and high …

IoT techniques have transformative potential across domains, particularly in precision
agriculture, where they enable farmers to optimize crop production while minimizing …

This paper introduces a novel deep learning model for grape disease detection that
integrates multimodal data and parallel heterogeneous activation functions, significantly …

Lemon, as an important cash crop with rich nutritional value, holds significant cultivation
importance and market demand worldwide. However, lemon diseases seriously impact the …

Early diagnosis of plant diseases is essential in reducing economic losses for farmers and
increasing production efficiency. Therefore, Computer-Aided Diagnosis (CAD) systems …

This paper developed a radish disease detection system based on a hybrid attention
mechanism, significantly enhancing the precision and real-time performance in identifying …