Detection of mulberry ripeness stages using deep learning models

Keyphrases

• Advanced Development 33%
• AlexNet 66%
• Automated Sorting 66%
• Black mulberry 33%
• Challenging Tasks 33%
• Classification Accuracy 66%
• Classifier Transfer 33%
• Computer Vision 33%
• Computer Vision-based 33%
• Convolutional Neural Network 33%
• Convolutional Neural Network Model 66%
• Deep Learning Model 100%
• DenseNet 33%
• Fruit Image 33%
• Fruit Ripening 33%
• Genotype 66%
• Horticultural Products 33%
• Human Error 33%
• InceptionV3 33%
• Machine Learning 33%
• Manual Sorting 33%
• Microbial Contamination 33%
• Mulberry 100%
• Mulberry Fruit 66%
• Overall Accuracy 66%
• Postharvest Management 33%
• Precise Classification 33%
• Processed Products 33%
• Quality Degradation 33%
• ResNet18 100%
• ResNet50 33%
• Ripeness 66%
• Ripeness Classification 33%
• Ripeness Stage 100%
• Ripening Stage 66%
• Sorting System 33%
• Training Costs 33%
• Transfer Learning 66%
• Vision Application 33%
• White mulberry 33%

Agricultural and Biological Sciences

• Alexnet 50%
• Computer Vision 50%
• Genotyping 25%
• Microbial Contamination 25%
• Morus Alba 25%
• Morus Nigra 25%
• Mulberries 100%
• Neural Network 75%
• Postharvest 25%
• Ripening 50%

Chemical Engineering

• Deep Learning 100%
• Learning System 33%
• Neural Network 100%