mlsanityData to 7 Oct 2026

Carrot Cure: A CNN based Application to Detect Carrot Disease

arXiv 2304.03511 ↗First posted 7 Apr 2023cs.CV cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Carrot is a famous nutritional vegetable and developed all over the world. Different diseases of Carrot has become a massive issue in the carrot production circle which leads to a tremendous effect on the economic growth in the agricultural sector. An automatic carrot disease detection system can help to identify malicious carrots and can provide a guide to cure carrot disease in an earlier stage, resulting in a less economical loss in the carrot production system. The proposed research study has developed a web application Carrot Cure based on Convolutional Neural Network (CNN), which can identify a defective carrot and provide a proper curative solution. Images of carrots affected by cavity spot and leaf bright as well as healthy images were collected. Further, this research work has employed Convolutional Neural Network to include birth neural purposes and a Fully Convolutional Neural Network model (FCNN) for infection order. Different avenues regarding different convolutional models with colorful layers are explored and the proposed Convolutional model has achieved the perfection of 99.8%, which will be useful for the drovers to distinguish carrot illness and boost their advantage.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 2 of its 29 references that are in the map. First posted on arXiv 7 Apr 2023.

Builds on

2 of 29 references.

References · 2

  1. 2016Using Deep Learning for Image-Based Plant Disease Detectioncited by 216
  2. 2017Fruit recognition from images using deep learningcited by 35

Built on by

Not cited yet.