Mushroom Image Classification with CNN

This study presents a Convolutional Neural Network (CNN) approach for mushroom image classification. Leveraging deep learning, the model demonstrates high accuracy in distinguishing various mushroom species. Through extensive training on diverse datasets, the CNN effectively captures intricate features, enabling robust classification. The proposed method not only enhances mushroom species identification but also contributes to the broader field of image recognition. This research underscores the potential of CNNs in automating the identification process for mushrooms, facilitating both scientific research and practical applications in fields such as agriculture and mycology.

Keyword: Mushroom dataset, deep learning algorithms