Knowledge Distillation (KD) aims to transfer knowledge in a teacher-student framework, by providing the predictions of the teacher network to the student network in the training stage to help the student network generalize better. It can use either a teacher with high capacity or {an} ensemble ...
Thus in this paper, we propose an online knowledge distillation method that transfers not only the knowledge of the class probabilities but also that of the feature map using the adversarial training framework. We train multiple networks simultaneously by employing discriminators to distinguish the ...
Fast and Accurate Single Image Super-Resolution via Information Distillation Network 本文主旨为了再生成深度网络的同时降低计算复杂性和减少内存消耗,因此本文提出了一个信息蒸馏网络,降低复杂性和内存消耗。总体网络框架分为三个部分①特征提取模块②增强模块(蒸馏模块)③特征融合与生成图片...能保留浅特征提取信息,而...
EnsembleDistill [formal2022distillation] DistilBERT ✓ ✓ 36.9 Co-SelfDistill [formal2022distillation] coConbase ✓ ✓ 37.5 Co-EnsembleDistill [formal2022distillation] coConbase ✓ ✓ 38.0 FecTek coConbase ✓ 38.2 FecTek-Distill-MinLM coConbase ✓ ✓ 38.7 Table 2: Ablation study on...
Granularity-aware distillation and structure modeling region proposal network for fine-grained image classification Fine-grained visual classification (FGVC) aims to identify objects belonging to multiple sub-categories of the same super-category. The key to solving fine... X Ke,Y Cai,B Chen,... ...
threat intelligence; document-level relation extraction; knowledge distillation; knowledge graph1. Introduction Today, the Internet of Things (IoT) impacts almost every aspect of societal needs [1]. With the rapid development of network and information technology, new cyber threats (e.g., session ...
Model compression with two-stage multi-teacher knowledge distillation for web question answering system. In Proceedings of the 13th International Conference on Web Search and Data Mining, Houston, TX, USA, 3–7 February 2020; pp. 690–698. [Google Scholar] Liscio, E.; Araque, O.; Gatti, L...
public dataset PolyU-DB showed that the proposed method can reduce the EER of the recognition result to 0.422%. In the future, we will try to use some model distillation methods to reduce the computational complexity of the proposed method so that low-cost embedded devices can also run the ...
For instance, Mendoza et al. [39] used a self-distillation method to build a self-supervised monocular depth estimation model. To strengthen the consistency between predictions, they studied consistency enforcement strategy and employ auxiliary strategies to filter out unreliable predictions....