Distillation is a process that involves separating a substance into its constituent parts based on their boiling points or volatility.
In unsupervised domain adaptive (UDA) semantic segmentation, the distillation based methods are currently dominant in performance. However, the distillatio... Li, Junjie,Wang, Zilei,Gao, Yuan,... 被引量: 0发表: 2022年 C3Net: Cross-Modal Feature Recalibrated, Cross-Scale Semantic Aggregated and...
fish behavior images are collected in a land-based factory,and a dataset is constructed and extended through flip,rotation,and color jitter augmentation techniques.The proposed method is also compared with other state-of-the-art methods.The experimental results show that the proposed model is more ...
embedding-based methods:将视觉特征映射到语义空间中 generative methods:根据语义生成视觉特征,这就和将图片输入到CNN网络最后得到视觉特征的过程类似,也就是说将问题转化为了常规的分类问题。 Currently, the generative ZSL usually based on variational autoencoders (VAEs) , generative adversarial nets (GANs), ...
(representing certainty) for one class and logits approaching 0 for all others—they do not provide as much information. Response-based methods thus often use a hightemperaturesetting for model outputs, which increases the entropy of model predictions. This ensures a more variable probability ...
Knowledge Distillation (KD) based methods adopt the one-way Knowledge Transfer (KT) scheme in which training a lower-capacity student network is guided by a pre-trained high-capacity teacher network. Recently, Deep Mutual Learning (DML) presented a two-way KT strategy, showing that the student...
Other distillation methods This is the last update for distillation of MultiLayerBasedModel. Other distillation methods will be added in succession. WhenKnowledge Distillationis mature enough, I will integrate them into a framework. March, 2020 ...
A distillation method for the quantitative determination of malonaldehyde in rancid foods An improved distillation method is described for the quantitative determination of malonaldehyde in foods containing oxidized fats. The procedure is compared with other methods in current use for the determination of...
In addition, FedKD can save up to 94.63% and 94.89% of communication cost on MIND and ADR, respectively, which is more communication-efficient than other compared federated learning-based methods. This is because FedKD can learn useful knowledge from the sophisticated local mentor models to ...
However, the latter is not convenient when one wants to use feature-map-based distillation methods. For a solution, this paper proposes a versatile and powerful training algorithm named FEature-level Ensemble for knowledge Distillation (FEED), which aims to transfer the ensemble knowledge using ...