Earticle

초록

영어

Early diagnosis of crop diseases as- sists the farmers to increase their output and save on their earnings. In this research, the Corn Leaf Disease Dataset with four classes is used, namely, Cercospora leaf spot, Common rust, Northern Leaf Blight, and Healthy. An image transformer (ViT) model is used, and image patches are treated as sequences, which enables them to cap- ture fine and global details. Application of transfer learning on a trained ViT enhances the accuracy and lowers the training time. Accuracy, precision, recall and F1-score measurements indicate that ViT is similar in performance to CNN models, and it is therefore useful in the detection of plant diseases.

목차

Abstract
I. INTRODUCTION
II. ARTICLE REVIEW
III. RELATED WORK
IV. METHODOLOGY
V. RESULTS AND DISCUSSION
6.1 TRAINING RESULTS
6.2 TRAINING EVALUATION METRICS
6.3 TESTING RESULTS
VI. CONCLUSION
REFERENCES

저자

• Maria Tariq [ Department of Computer Science Lahore Garrison University Lahore, Pakistan ]
• Sundas Munir [ Department of Computer Science Lahore Garrison University Lahore, Pakistan ]
• Khushbu Khalid Butt [ Department of Computer Science Lahore Garrison University Lahore, Pakistan ]
• Tahir Alyas [ Department of Computer Science Lahore Garrison University Lahore, Pakistan ]
• Muhammad Shoukat Aslam [ Department of Computer Science LIST Lahore, Pakistan ]
• Muhammad Adnan Khan [ Department of Software Gachon University Seongnam-si, Republic of Korea. ] Corresponding Author

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