Ensemble of multi-task deep convolutional neural networks using transfer learning for fruit freshness classification

Automatic classification of fruit freshness plays an important role in the agriculture industry. In this work, we propose an ensemble model that combines the bottleneck features of two multi-task deep convolutional neural networks with different architectures (ResNet-50 and ResNet-101). In our proposed multi-tasking framework, there are two classification branches: a binary classifier to distinguish between fresh and rotten fruits, and a...