A REVIEW PAPER ON CNN APPROACHES FOR POISONOUS MUSHROOM IDENTIFICATION

Kelvin Dmello; B S Sumukha; Akash Devadiga; Sooraj; Charan S V

A REVIEW PAPER ON CNN APPROACHES FOR POISONOUS MUSHROOM IDENTIFICATION

December 2024

Vol-10, Issue-6

Paper ID: 25516

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Information Science and Engineering

Keywords

CNN ResNet-50 Mushroom Classification Toxic Mushroom Detection Image Processing TensorFlow Keras NumPy Pandas Matplotlib Scikit-learn and Pillow.

Abstract

Mushrooms are popular due to their high nutritional value, which includes amino acids, polysaccharides, and other essential nutrients. However, eating poisonous mushrooms can cause serious health problems like nausea, vomiting, mental disorders, acute anemia, and even death. Every year, approximately 8,000 people suffer from mushroom poisoning, with 70 fatalities. With thousands of mushroom species, only about 900 are edible, making it difficult for those without specialized knowledge to distinguish between them. While many people believe that poisonous mushrooms are brightly colored, some dangerous species do not exhibit this characteristic. allowing for further advancements in mushroom toxicity detection and classification. To reduce the risks associated with eating toxic mushrooms, this study proposes using deep learning techniques to classify mushrooms as edible or poisonous based on image features such as color, shape, and texture. A dataset containing 5,127 edible and 3,163 poisonous mushroom images will be used for training, validation, and testing, with a 70% training, 15% validation, and 15% testing ratio. The ResNet50 algorithm, a deep learning architecture known for its performance in image classification, will be used. TensorFlow and Keras will be used to implement deep learning, NumPy and Pandas to manipulate data, Matplotlib to visualize, Scikit-learn to evaluate models, and Pillow to preprocess images. The model aims to provide accurate predictions while taking into account the benefits and side effects of various mushrooms. This solution, by automating the identification of toxic and edible mushrooms, will help reduce the risks associated with foraging. while also contributing to public safety.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Kelvin Dmello	Alva’s Institute of Engineering and Technology, Karnataka
2	B S Sumukha	Alva’s Institute of Engineering and Technology, Karnataka
3	Akash Devadiga	Alva’s Institute of Engineering and Technology, Karnataka
4	Sooraj	Alva’s Institute of Engineering and Technology, Karnataka
5	Charan S V	Alva’s Institute of Engineering and Technology, Karnataka

How to Cite

Use the following formats to cite this article in your research.

APA Style

Dmello, Kelvin, Sumukha, B S, Devadiga, Akash, Sooraj, & V, Charan S (2024). A REVIEW PAPER ON CNN APPROACHES FOR POISONOUS MUSHROOM IDENTIFICATION. International Journal of Advance Research and Innovative Ideas In Education, 10(6), 1807-1812.

MLA Style

Dmello, Kelvin, et al. "A REVIEW PAPER ON CNN APPROACHES FOR POISONOUS MUSHROOM IDENTIFICATION." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 6, 2024, pp. 1807-1812.

IEEE Style

Kelvin Dmello, B S Sumukha, Akash Devadiga, Sooraj, and Charan S V, "A REVIEW PAPER ON CNN APPROACHES FOR POISONOUS MUSHROOM IDENTIFICATION," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 6, pp. 1807-1812, 2024.

Vancouver Style

Dmello Kelvin, Sumukha B S, Devadiga Akash, Sooraj, V Charan S. A REVIEW PAPER ON CNN APPROACHES FOR POISONOUS MUSHROOM IDENTIFICATION. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(6):1807-1812.

Harvard Style

Dmello, Kelvin, Sumukha, B S, Devadiga, Akash, Sooraj, & V, Charan S (2024) 'A REVIEW PAPER ON CNN APPROACHES FOR POISONOUS MUSHROOM IDENTIFICATION', International Journal of Advance Research and Innovative Ideas In Education, 10(6), pp. 1807-1812.

Chicago Style

Dmello, Kelvin, et al. "A REVIEW PAPER ON CNN APPROACHES FOR POISONOUS MUSHROOM IDENTIFICATION." International Journal of Advance Research and Innovative Ideas In Education 10, no. 6 (2024): 1807-1812.

Turabian Style

Dmello, Kelvin, et al. "A REVIEW PAPER ON CNN APPROACHES FOR POISONOUS MUSHROOM IDENTIFICATION." International Journal of Advance Research and Innovative Ideas In Education 10, no. 6 (2024): 1807-1812.