𝔖 Bobbio Scriptorium
✦   LIBER   ✦

An evaluation of radar as a crop classifier

✍ Scribed by T.F. Bush; F.T. Ulaby

Publisher
Elsevier Science
Year
1978
Tongue
English
Weight
974 KB
Volume
7
Category
Article
ISSN
0034-4257

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Evaluation of saltgrass as a fodder crop
Evaluation of saltgrass as a fodder crop for livestock
✍ Amnon Bustan; Dov Pasternak; Irina Pirogova; Muhamet Durikov; Tonny T Devries; S πŸ“‚ Article πŸ“… 2005 πŸ› John Wiley and Sons 🌐 English βš– 141 KB

## Abstract Farmland salinization due to unsustainable agricultural practices has become a worldwide problem. Salt‐resistant forage crops, introduced at the primary stages of land reclamation, can provide fodder for livestock, thus adding economic benefit to the process. Saltgrass (__Distichlis spi

An Agroecological Modeling Approach to E
An Agroecological Modeling Approach to Explain ERS SAR Radar Backscatter of Agricultural Crops
✍ B.A.M. Bouman; D.W.G. van Kraalingen; W. Stol; H.J.C. van Leeuwen πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 349 KB

An agroecological approach is presented to simulate and by the launch in July 1991 of the ERS-1 satellite that carries, among others, an imaging C-band SAR (Syn-time series of ERS SAR radar backscatter of agricultural crops from integrated crop growth (SUCROS), water thetic Aperture Radar). The inte

An initial comparison of a fuzzy neural
An initial comparison of a fuzzy neural classifier and a decision tree based classifier
✍ Jurgen Martens; Geert Wets; Jan Vanthienen; Christophe Mues πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 210 KB

At the present time a large number of AI methods have been developed in the field of pattern classification. In this paper, we will compare the performance of a well-known algorithm in machine learning (C4.5) with a recently proposed algorithm in the fuzzy set community (NEFCLASS). We will compare t

Classifier performance as a function of
Classifier performance as a function of distributional complexity
✍ Sanju N. Attoor; Edward R. Dougherty πŸ“‚ Article πŸ“… 2004 πŸ› Elsevier Science 🌐 English βš– 283 KB

When choosing a classiΓΏcation rule, it is important to take into account the amount of sample data available. This paper examines the performances of classiΓΏers of di ering complexities in relation to the complexity of feature-label distributions in the case of small samples. We deΓΏne the distributi