Results 271 to 280 of about 5,782,720 (331)

A Novel Approach to Estimate the Transition Temperature via Dynamic Nanoindentation

Advanced Engineering Materials, EarlyView.
A new dynamic nanoindentation‐based method was developed that uses the stiffness ratio as an indicator of the elastic–plastic deformation contributions at different temperatures. The approach successfully identified transition temperatures in ferritic steel and distinguished them from continuously ductile austenitic steel.
Stefan Zeiler, Nikolaus Kostwein, Ronald Schnitzer, Christian Mitterer, Verena Maier‐Kiener   +4 more
wiley   +1 more source

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Supervised Classification

Satellite Remote Sensing of Natural Resources, 2022
D. Verbyla
semanticscholar   +2 more sources

A survey of multi-label classification based on supervised and semi-supervised learning

International Journal of Machine Learning and Cybernetics, 2022
Xilong Zhang, Meng Han
exaly   +2 more sources

Big Self-Supervised Models Advance Medical Image Classification

IEEE International Conference on Computer Vision, 2021
Self-supervised pretraining followed by supervised fine-tuning has seen success in image recognition, especially when labeled examples are scarce, but has received limited attention in medical image analysis.
Shekoofeh Azizi, Basil Mustafa, Fiona Ryan, Zach Beaver, J. Freyberg, Jonathan Deaton, Aaron Loh, A. Karthikesalingam, Simon Kornblith, Ting Chen, Vivek Natarajan, Mohammad Norouzi   +11 more
semanticscholar   +1 more source

Embedding Regularizer Learning for Multi-View Semi-Supervised Classification

IEEE Transactions on Image Processing, 2021
Classification remains challenging when confronted with the existence of multi-view data with limited labels. In this paper, we propose an embedding regularizer learning scheme for multi-view semi-supervised classification (ERL-MVSC).
Aiping Huang, Zheng Wang, Yannan Zheng, Tiesong Zhao, Chia-Wen Lin   +4 more
semanticscholar   +1 more source

Learning Deep Sparse Regularizers With Applications to Multi-View Clustering and Semi-Supervised Classification

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Sparsity-constrained optimization problems are common in machine learning, such as sparse coding, low-rank minimization and compressive sensing. However, most of previous studies focused on constructing various hand-crafted sparse regularizers, while ...
Shiping Wang, Zhaoliang Chen, Shi-De Du, Zhou-Chen Lin   +3 more
semanticscholar   +1 more source

Progressive Supervision for Node Classification

2021
Graph Convolution Networks (GCNs) are a powerful approach for the task of node classification, in which GCNs are trained by minimizing the loss over the final-layer predictions. However, a limitation of this training scheme is that it enforces every node to be classified from the fixed and unified size of receptive fields, which may not be optimal.
Yiwei Wang 0001, Wei Wang 0059, Yuxuan Liang 0002, Yujun Cai, Bryan Hooi   +4 more
openaire   +2 more sources

Self-supervised Vision Transformers for Land-cover Segmentation and Classification

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022
Transformer models have recently approached or even surpassed the performance of ConvNets on computer vision tasks like classification and segmentation.
Linus Scheibenreif, Joelle Hanna, Michael Mommert, Damian Borth   +3 more
semanticscholar   +1 more source

SCL-MLNet: Boosting Few-Shot Remote Sensing Scene Classification via Self-Supervised Contrastive Learning

IEEE Transactions on Geoscience and Remote Sensing, 2022
Few-shot classification aims at recognizing novel categories from low data regimes based on prior knowledge. However, the existing methods for few-shot scene classification have limitations on using few annotated data and do not fully consider the intra ...
Xiaomin Li, D. Shi, Xiaolei Diao, Hao Xu
semanticscholar   +1 more source

Hyperspectral Image Classification With Contrastive Self-Supervised Learning Under Limited Labeled Samples

IEEE Geoscience and Remote Sensing Letters, 2022
Hyperspectral image (HSI) classification is an active research topic in remote sensing. Supervised learning-based methods have been widely used in HSI classification tasks due to their powerful feature extraction capabilities for cases of sufficiently ...
Lin Zhao, Wen-Qiang Luo, Qi-Ming Liao, Si-Yuan Chen, Jian-Hui Wu   +4 more
semanticscholar   +1 more source