Can knowledge distillation be used in conjunction with fine tuning?

Mar 20, 2023 ... With fine-tuning, you freeze the weights for all the pretrained layers except for one. Then, through edge training, the weights for the single ... Nov 7, 2020 ... This study aimed at evaluating the layer depths and degree of fine-tuning on transfer learning with a deep convolutional neural network (CNN)-based COVID-19 ... Feb 13, 2025 ... Fine-tuning is a form of transfer learning where the pre-trained model is adjusted to better fit the new data. There are several steps involved ... Fine-tuning is a deep learning technique that refers to taking a pre-trained model and further training it on a new dataset or task. Aug 16, 2024 ... The very last classification layer (on "top", as most diagrams of machine learning models go from bottom to top) is not very useful. Instead ... Course Q&A Deep Learning Specialization Convolutional Neural Networks · Marios_Constantinou July 24, 2022, 12:39pm 1. I have a ResNet50 model with 190 ... In this work, the focus was on fine-tuning and evaluation of state-of-the-art deep convolutional neural network for image-based plant disease classification. Deep neural networks have been highly successful across a multitude of domains, from computer vision [1, 2] and natural language processing [3, 4], to game ... only fine-tune the last layer of the deep neural network: here, the last layer of the source model is kept but serves as an initialization of the target Machine ... Apr 18, 2025 ... Hello I am trying to fine tune the " High Resolution Land Cover Classification - USA " deep learning model for a region of interest in ...