A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks
Breast cancer is currently the second most common cause of cancer-related death in
women. Presently, the clinical benchmark in cancer diagnosis is tissue biopsy examination …
women. Presently, the clinical benchmark in cancer diagnosis is tissue biopsy examination …
[PDF][PDF] 大数据下的机器学习算法综述
何清, 李宁, 罗文娟, 史忠植 - 模式识别与人工智能, 2014 - researchgate.net
摘要随着产业界数据量的爆炸式增长, 大数据概念受到越来越多的关注. 由于大数据的海量,
复杂多样, 变化快的特性, 对于大数据环境下的应用问题, 传统的在小数据上的机器学习算法很多 …
复杂多样, 变化快的特性, 对于大数据环境下的应用问题, 传统的在小数据上的机器学习算法很多 …
A new image classification method using CNN transfer learning and web data augmentation
D Han, Q Liu, W Fan - Expert Systems with Applications, 2018 - Elsevier
Abstract Since Convolutional Neural Network (CNN) won the image classification
competition 202 (ILSVRC12), a lot of attention has been paid to deep layer CNN study. The …
competition 202 (ILSVRC12), a lot of attention has been paid to deep layer CNN study. The …
A survey on transfer learning
A major assumption in many machine learning and data mining algorithms is that the
training and future data must be in the same feature space and have the same distribution …
training and future data must be in the same feature space and have the same distribution …
Multi-source transfer learning guided ensemble LSTM for building multi-load forecasting
C Peng, Y Tao, Z Chen, Y Zhang, X Sun - Expert Systems with Applications, 2022 - Elsevier
Generally, it is difficult to establish an accurate building load forecasting model by using
insufficient energy data. Although the transfer of knowledge from similar buildings can …
insufficient energy data. Although the transfer of knowledge from similar buildings can …
Transfer learning for cross-company software defect prediction
CONTEXT: Software defect prediction studies usually built models using within-company
data, but very few focused on the prediction models trained with cross-company data. It is …
data, but very few focused on the prediction models trained with cross-company data. It is …
Transfer learning
SJ Pan - Learning, 2020 - api.taylorfrancis.com
Supervised machine learning techniques have already been widely studied and applied to
various real-world applications. However, most existing supervised algorithms work well …
various real-world applications. However, most existing supervised algorithms work well …
[PDF][PDF] Co-training for cross-lingual sentiment classification
X Wan - Proceedings of the Joint Conference of the 47th Annual …, 2009 - aclanthology.org
The lack of Chinese sentiment corpora limits the research progress on Chinese sentiment
classification. However, there are many freely available English sentiment corpora on the …
classification. However, there are many freely available English sentiment corpora on the …
Link prediction and recommendation across heterogeneous social networks
Link prediction and recommendation is a fundamental problem in social network analysis.
The key challenge of link prediction comes from the sparsity of networks due to the strong …
The key challenge of link prediction comes from the sparsity of networks due to the strong …
[PDF][PDF] Cross-language text classification using structural correspondence learning
P Prettenhofer, B Stein - Proceedings of the 48th annual meeting …, 2010 - aclanthology.org
We present a new approach to crosslanguage text classification that builds on structural
correspondence learning, a recently proposed theory for domain adaptation. The approach …
correspondence learning, a recently proposed theory for domain adaptation. The approach …