HSSNet: A End-to-End Network for Detecting Tiny Targets of Apple Leaf Diseases in Complex Backgrounds [PDF]
Plants, 2023 Apple leaf diseases are one of the most important factors that reduce apple quality and yield. The object detection technology based on deep learning can detect diseases in a timely manner and help automate disease control, thereby reducing economic ...
Xing Gao +5 more
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Apple Leaf Diseases Recognition Based on An Improved Convolutional Neural Network [PDF]
Sensors, 2020 Scab, frogeye spot, and cedar rust are three common types of apple leaf diseases, and the rapid diagnosis and accurate identification of them play an important role in the development of apple production. In this work, an improved model based on VGG16 is
Qian Yan +5 more
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Apple-Net: A Model Based on Improved YOLOv5 to Detect the Apple Leaf Diseases [PDF]
Plants, 2022 Effective identification of apple leaf diseases can reduce pesticide spraying and improve apple fruit yield, which is significant to agriculture. However, the existing apple leaf disease detection models lack consideration of disease diversity and ...
Ruilin Zhu +3 more
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A High-Precision Detection Method of Apple Leaf Diseases Using Improved Faster R-CNN
Agriculture, 2023 Apple leaf diseases seriously affect the sustainable production of apple fruit. Early infection monitoring of apple leaves and timely disease control measures are the key to ensuring the regular growth of apple fruits and achieving a high-efficiency ...
Xulu Gong, Shujuan Zhang
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AppleLeafNet: a lightweight and efficient deep learning framework for diagnosing apple leaf diseases [PDF]
Frontiers in Plant ScienceAccurately identifying apple diseases is essential to control their spread and support the industry. Timely and precise detection is crucial for managing the spread of diseases, thereby improving the production and quality of apples.
Muhammad Umair Ali +5 more
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Real-Time Detection of Apple Leaf Diseases in Natural Scenes Based on YOLOv5
Agriculture, 2023 Aiming at the problem of accurately locating and identifying multi-scale and differently shaped apple leaf diseases from a complex background in natural scenes, this study proposed an apple leaf disease detection method based on an improved YOLOv5s model.
Huishan Li, Lei Shi, Siwen Fang, Fei Yin
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A method of detecting apple leaf diseases based on improved convolutional neural network. [PDF]
PLoS ONE, 2022 Apple tree diseases have perplexed orchard farmers for several years. At present, numerous studies have investigated deep learning for fruit and vegetable crop disease detection.
Jie Di, Qing Li
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IEEE Access, 2019 Alternaria leaf spot, Brown spot, Mosaic, Grey spot, and Rust are five common types of apple leaf diseases that severely affect apple yield. However, the existing research lacks an accurate and fast detector of apple diseases for ensuring the healthy ...
Peng Jiang +4 more
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Identification of Apple Leaf Diseases by Improved Deep Convolutional Neural Networks With an Attention Mechanism [PDF]
Frontiers in Plant Science, 2021 The accurate identification of apple leaf diseases is of great significance for controlling the spread of diseases and ensuring the healthy and stable development of the apple industry.
Peng Wang +17 more
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A systematic review of deep learning techniques for apple leaf diseases classification and detection [PDF]
PeerJ Computer ScienceAgriculture sustains populations and provides livelihoods, contributing to socioeconomic growth. Apples are one of the most popular fruits and contains various antioxidants that reduce the risk of chronic diseases. Additionally, they are low in calories,
Assad Souleyman Doutoum, Bulent Tugrul
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