Sökning: "Classification Model"

Visar resultat 6 - 10 av 542 avhandlingar innehållade orden Classification Model.

1. 6. Classification of Remotely Sensed Data Utilising the Autocorrelation between Spatio-Temporal Neighbours

   Författare :Ann-Marie Flygare; Sweden Umeå Umeå University Department of Mathematical Statistics; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Image classification; strong mixing; spatio-temporal model; autocorrelation model; autocorrelation estimator; robustness aspects; strong consistency; asymptotic normality; evaluation; Statistik; Statistics;

   Sammanfattning : The subject of this thesis is methods for classifying land using satellite images, and adherent parameter estimation. A satellite image consists of a set of pixels where measurements of spectral intensities are observed. Based on these spectral intensities, each pixel is assigned a class. LÄS MER

3. 7. Architecting model driven system integration in production engineering

   Författare :Yujiang Li; Lars Mattsson; Gunilla Franzén Sivard; Torsten J. A. Kjellberg; Mikael Hedlind; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; System architecture; system integration; information model; ISO 10303; application context; implementation context; implementation model.; Production Engineering; Industriell produktion;

   Sammanfattning : System integration is a key enabler to maximize information value in an engineering context. The valuable information is normally represented by information models which play a decisive role in the implementation of system integration. LÄS MER

4. 8. Decision Algebra : A General Approach to Learning and Using Classifiers

   Författare :Antonina Danylenko; Welf Löwe; Jonas Lundberg; Uwe Assmann; Linnéuniversitetet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; classification; decision model; classifier; Decision Algebra; decision function; Computer Science; Datavetenskap;

   Sammanfattning : Processing decision information is a vital part of Computer Science fields in which pattern recognition problems arise. Decision information can be generalized as alternative decisions (or classes), attributes and attribute values, which are the basis for classification. LÄS MER

5. 9. Machine Learning Methods Using Class-specific Subspace Kernel Representations for Large-Scale Applications

   Författare :Yinan Yu; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; class-specific kernels; large-scale framework; subspace model; classification; kernel approximation; RKHS;

   Sammanfattning : Kernel techniques became popular due to and along with the rising success of Support Vector Machines (SVM). During the last two decades, the kernel idea itself has been extracted from SVM and is now widely studied as an independent subject. LÄS MER

7. 10. Bringing predictability into a geometallurgical program : An iron ore case study

   Författare :Viktor Lishchuk; Bertil Pålsson; Cecilia Lund; Pertti Lamberg; Jennifer Broadhurst; Luleå tekniska universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Additivity; Apatite iron ore; AIO; Block model; Change of support; Classification; Data integration; DT; Feed quality; Geometallurgical program; Geometallurgy; Iron ore; Iron recovery; Leveäniemi; Liberation; Machine learning; Magnetic separation; Malmberget; Mineralogical approach; Mineralogy; Prediction; Proxies; Proxies approach; Sampling; Simulation; Synthetic ore body; Traditional approach; WLIMS; Mineral Processing; Mineralteknik;

   Sammanfattning : The risks of starting, operating and closing mining projects have become higher than ever. In order to stay ahead of the competition, mining companies have to manage various risks: technical, environmental, legal, regulatory, political, cyber, financial and social. Some of these can be mitigated with the help of geometallurgy. LÄS MER