Multi-modal expert system for automated durian ripeness classification using deep learning
Accurate classification of durian ripeness is essential for quality control and minimizing post-harvest losses. Manual inspection remains subjective and inconsistent, prompting the need for automated methods. We present a multi-modal approach that integrates Convolutional Neural Networks (CNNs) for...
Saved in:
| Main Authors: | Santi Sukkasem, Watchareewan Jitsakul, Phayung Meesad |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | Intelligent Systems with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667305325000894 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Real-Time Fire Risk Classification Using Sensor Data and Digital-Twin-Enabled Deep Learning
by: In-Seop Na, et al.
Published: (2025-01-01) -
Time Series Forecasting for Air Quality with Structured and Unstructured Data Using Artificial Neural Networks
by: Kenneth Chan, et al.
Published: (2025-03-01) -
The Role of Artificial Intelligence in Enhancing Cyber Security using Deep Learning Techniques: A Review
by: Abeer Alyoons, et al.
Published: (2024-06-01) -
A Deep Learning Approach to Evaluating SISO-OFDM Channel Equalization
by: Saja S Hanoon, et al.
Published: (2024-04-01) -
Pengenalan Ucapan Bahasa Indonesia Menggunakan MFCC dan Recurrent Neural Network
by: Panggih Tridarma, et al.
Published: (2020-11-01)