A Robust Deep Learning Framework: Ensemble of YOLOv8 and EfficientNet

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Kaur Harjeet; Prashar Deepak; Kumar Vipul

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Information Technology Management Year:2025 | Volume:17 | Issue:2 Special Issue Page(s): 32-44

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

A Robust Deep Learning Framework: Ensemble of YOLOv8 and EfficientNet

Author(s)

Kaur Harjeet | Prashar Deepak | Kumar Vipul | Issue Writer Certificate

Keywords

Deep learning

EfficientNet

Yolov8

Image classification

Object Detection

loss

Abstract

This research work aims to present a robust Deep learning framework by devising a Deep learning-based ensemble method of Yolov8 and EfficientNet. The suggested model is evaluated on the dataset collected from Kaggle, comprising 10,000 high-definition images of stems, leaves, and cut fruits of banana and papaya. These images are captured under different lighting conditions and thus expanded to 80,000 images. Authors have proposed an ensemble model comprising Yolov8 and EfficientNet as base Deep learning models to enhance prediction and classification performance. Here, authors combine the merits of both models, i.e., speed of Yolov8 and the accuracy of EfficientNet, by putting a majority voting method in place. The final forecast is determined by majority voting, and EfficientNet is given higher significance in the situation of a tie owing to its enhanced accuracy. The proposed model presents a robust solution for agricultural disease management and demonstrates significant improvements in the detection of diseases in papaya and banana, opening avenues for its widespread employment in real life.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans