Subject
Creator
- Baichuan Zhang 1
- Bartlomiej P. Rajwa 1
- Jeffrey Dukes 1
- Michael Schuster 1
- Murat Dundar 1
- Nicholas G. Smith 1
- Qiang Kou 1
- Yicheng He 1
Type
- Dataset 2
Date
- 2015 2
subject: Life Sciences date: 2015
Total is 2 Results
Simplicity of K-means versus deepness of Deep Learning. A Case of Unsupervised Feature Learning with Limited Data
10.4231/R7N58J9Z
Baichuan Zhang, Bartlomiej P. Rajwa, Murat Dundar, Qiang Kou, Yicheng He
10/01/2015
We study a biodetection application as a case study to demonstrate that K-means-based unsupervised feature learning can be a simple yet effective alternative to deep learning techniques for small data sets with limited intra- as well as inter-class diversi...
bacterial colonies BARDOT Biomedical Engineering Computer Science deep learning Elastic light scattering Interdisciplinary Research K-Means Clustering Life Sciences Machine Learning representation learning
PRICLE community composition and soil moisture 2012-2013
10.4231/R7TQ5ZG3
Jeffrey Dukes, Michael Schuster, Nicholas G. Smith
12/01/2015
These data correspond to a paper entitled "Rainfall variability and nitrogen addition synergistically reduce plant diversity in a restored tallgrass prairie" by Smith, Schuster, and Dukes published in the Journal of Applied Ecology.
Agriculture Botany Climate environmental manipulation Forestry and Natural Resources Life Sciences plant community Plant Diversity Soil Water Content soils
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