Results 21 to 30 of about 14,848 (289)
Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance [PDF]
, 2020 Models for natural language understanding (NLU) tasks often rely on the idiosyncratic biases of the dataset, which make them brittle against test cases outside the training distribution.
Gurevych, Iryna +2 more
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A Lightweight Graph Neural Network Algorithm for Action Recognition Based on Self-Distillation
Algorithms, 2023 Recognizing human actions can help in numerous ways, such as health monitoring, intelligent surveillance, virtual reality and human–computer interaction. A quick and accurate detection algorithm is required for daily real-time detection. This paper first
Miao Feng, Jean Meunier
doaj +1 more source
, 2022 Knowledge distillation is the procedure of transferring "knowledge" from a large model (the teacher) to a more compact one (the student), often being used in the context of model compression. When both models have the same architecture, this procedure is called self-distillation.
Pham, Minh +3 more
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Bayesian Optimization Meets Self-Distillation
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 Bayesian optimization (BO) has contributed greatly to improving model performance by suggesting promising hyperparameter configurations iteratively based on observations from multiple training trials. However, only partial knowledge (i.e., the measured performances of trained models and their hyperparameter configurations) from previous trials is ...
Lee, HyunJae +5 more
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Point Cloud Instance Segmentation with Inaccurate Bounding-Box Annotations
Sensors, 2023 Most existing point cloud instance segmentation methods require accurate and dense point-level annotations, which are extremely laborious to collect.
Yinyin Peng, Hui Feng, Tao Chen, Bo Hu
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Self-distillation for Surgical Action Recognition
, 2023 Surgical scene understanding is a key prerequisite for contextaware decision support in the operating room. While deep learning-based approaches have already reached or even surpassed human performance in various fields, the task of surgical action recognition remains a major challenge.
Yamlahi, Amine +11 more
openaire +2 more sources
Self-Distillation for Unsupervised 3D Domain Adaptation [PDF]
, 2023 Point cloud classification is a popular task in 3D vision. However, previous works, usually assume that point clouds at test time are obtained with the same procedure or sensor as those at training time.
Adriano Cardace +4 more
core +1 more source
Frontiers in Earth Science, 2023 Salt structures are crucial targets in oil and gas seismic exploitation so that one fast, automatic and accurate method is necessary for accelerating salt structure identification in the exploitation process.
Keran Li +6 more
doaj +1 more source
Cervical Cell Image Classification-Based Knowledge Distillation
Biomimetics, 2022 Current deep-learning-based cervical cell classification methods suffer from parameter redundancy and poor model generalization performance, which creates challenges for the intelligent classification of cervical cytology smear images.
Wenjian Gao +5 more
doaj +1 more source
Frontiers in Ecology and Evolution, 2022 Masked image modeling (MIM) is a learning method in which the unmasked components of the input are utilized to learn and predict the masked signal, enabling learning from large amounts of unannotated data.
Xuying Wang +4 more
doaj +1 more source