Combining Convolutional Neural Networks for Fungi Classification
Deep learning approaches have shown exceptional efficacy in challenges related to the categorization of images. Nevertheless, the practical use of these methods in classifying fungi faces difficulties due to the distinctive features of fungal morphology and the scarcity of annotated training data. H...
Saved in:
| Main Authors: | Anuruk Prommakhot, Jakkree Srinonchat |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10505294/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hybrid CNN and Transformer-Based Sequential Learning Techniques for Plant Disease Classification
by: Anuruk Prommakhot, et al.
Published: (2025-01-01) -
Image Classification of Indonesian Snacks using Convolutional Neural Network
by: Kunti Eliyen, et al.
Published: (2025-05-01) -
Analysis of MSTAR Object Classification Features Extracted by a Deep Convolutional Neural Network
by: I. F. Kupryashkin
Published: (2025-05-01) -
Impact of the Radar Image Resolution of Military Objects on the Accuracy of their Classification by a Deep Convolutional Neural Network
by: I. F. Kupryashkin
Published: (2022-02-01) -
EFFICIENCY AND ACCURACY OF CONVOLUTIONAL AND FOURIER TRANSFORM LAYERS IN NEURAL NETWORKS FOR MEDICAL IMAGE CLASSIFICATION
by: Fauzi Nafi'udin, et al.
Published: (2024-10-01)