An apple leaf disease detection dataset is collected, containing 2,748 images of diseased apple leaves under a complex environment, such as from different shooting angles, during different spans of the day, and under different weather conditions. Moreover, various data augmentati...
The existing plant leaf disease detection techniques can detect only one disease from a leaf. However, a single leaf may contain symptoms of multiple diseases. This study has proposed a hybrid deep learning-based framework for the real-time detection of multiple diseases from a single guava leaf...
Based on this, a new apple leaf disease detection model that uses deep-CNNs is proposed by introducing the GoogLeNet Inception structure and Rainbow concatenation. Finally, under the hold-out testing dataset, using a dataset of 26,377 images of diseased apple leaves, the proposed INAR-SSD (...
This paper specifically delves into the domain of plant disease detection, showcasing its application in a pear orchard through the use of deep learning models. For this purpose, a dataset was collected from a pear orchard, named diaMOS Plant, containing annotations for four distinct classes. A...
First, we proposed a multi-stage system which could not only do the plant species classification but also do the disease classification at the same time. Besides, this approach could also reduce the dependence of the...
We tested the performance of ECA-ConvNeXt on the rice leaf disease identification dataset. Experimental results show that the proposed model achieved an accuracy of 94.82%, a precision of 94.47%, a recall rate of 94.31%, and an F1- Score of 94.3...
D. Singh, N. Jain, P. Jain, P. Kayal, S. Kumawat, N. Batra, PlantDoc: a dataset for visual plant disease detection, inProceedings of the 7th ACM IKDD CoDS and 25th COMAD(2020), pp. 249–253 Google Scholar Dataset.https://www.kaggle.com/datasets/smaranjitghose/corn-or-maize-leaf...
Plant leaf diseases can be detected based on the disease symptoms. Here, dataset of disease affected leaves is considered for experimentation. This dataset contains the plant leaves suffered from the AlternariaAlternata,Cercospora Leaf Spot, Anthracnose andBacterial Blight along with some healthy leaf ...
To address this issue, we propose a new model called YOLOv8_Rice, specifically designed for rice leaf disease detection based on the YOLOv8n object detection model. Firstly, we conducted experimental research to investigate the influence of various common attention mechanisms on the performance of ...
The present study and previous plant disease detection algorithms are also compared. 3. We create and present an original dataset of images of diseased tea leaves obtained from the prominent tea gardens of Sylhet, Bangladesh. This brand-new dataset might be used for training and testing the YOLO...