Super-Resolution Reconstruction-Based Plant Image Classification Using Thermal and Visible-Light Images

Article Computer Science, Information Systems

Deep learning-based plant classification and crop disease classification by thermal camera

Ganbayar Batchuluun et al.

Summary: This study proposes a plant and crop disease classification method based on thermal images, utilizing convolutional neural network and explainable artificial intelligence technology. By establishing a new thermal plant image dataset for experiments, high classification accuracy was achieved.

JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES (2022)

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Article Mathematics

Deep Learning-Based Plant-Image Classification Using a Small Training Dataset

Ganbayar Batchuluun et al.

Summary: Previous research on plant image classification used various plant datasets, but faced difficulties due to small dataset sizes and limitations in constructing large-scale datasets. This study improved plant image classification performance by reducing training image numbers and then increasing them through augmentation methods.

MATHEMATICS (2022)

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Article Mathematics

Deep Learning-Based Plant Classification Using Nonaligned Thermal and Visible Light Images

Ganbayar Batchuluun et al.

Summary: This study focuses on overcoming the limitations of visible light cameras and thermal cameras in plant studies based on thermal images. By using thermal images and corresponding visible light images to extract features, the accuracy of multi-class classification is improved, and a new database is built.

MATHEMATICS (2022)

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Proceedings Paper Materials Science, Multidisciplinary

Automated plant leaf disease detection and classification using optimal MobileNet based convolutional neural networks

S. Ashwinkumar et al.

Summary: Agriculture is a major occupation in India, but plant diseases cause a 35% loss in crop productivity annually. Automated plant disease detection techniques help to identify disease symptoms early on plant leaves.

MATERIALS TODAY-PROCEEDINGS (2022)

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Article Agriculture, Multidisciplinary

T-CNN: Trilinear convolutional neural networks model for visual detection of plant diseases

Dongfang Wang et al.

Summary: This paper discusses the importance of detecting plant diseases and the application of convolutional neural networks in crop and disease recognition, proposing a new method that separates crop and disease identification and demonstrating its effectiveness. The results show high accuracy in crop and disease identification in controlled laboratory environments, and decent accuracy in real-world environments as well.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)

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Article Computer Science, Artificial Intelligence

Attention augmented residual network for tomato disease detection and classification

Getinet Yilma et al.

Summary: The study proposed an AAR network which improved tomato disease recognition and visualization effectiveness by enhancing salient feature learning and attention to detail.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES (2021)

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Article Chemistry, Analytical