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BMCBI
2006
169views more  BMCBI 2006»
15 years 6 months ago
Machine learning techniques in disease forecasting: a case study on rice blast prediction
Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
CONNECTION
2006
172views more  CONNECTION 2006»
15 years 6 months ago
Temporal sequence detection with spiking neurons: towards recognizing robot language instructions
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...
Christo Panchev, Stefan Wermter
IJCV
2008
192views more  IJCV 2008»
15 years 6 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
JMLR
2008
159views more  JMLR 2008»
15 years 6 months ago
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
Andreas Krause, Ajit Paul Singh, Carlos Guestrin
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CSDA
2007
264views more  CSDA 2007»
15 years 6 months ago
Model-based methods to identify multiple cluster structures in a data set
Model-based clustering exploits finite mixture models for detecting group in a data set. It provides a sound statistical framework which can address some important issues, such as...
Giuliano Galimberti, Gabriele Soffritti