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Identificació de la wolframita a partir de pixels mitjançant Machine Learning

Authors: Abril Soler, Toni;

Identificació de la wolframita a partir de pixels mitjançant Machine Learning

Abstract

Cada vegada més, es persegueix aconseguir millores d’eficiència i l’abaratiment de qualsevol tasca a realitzar dins d’una empresa, amb l’objectiu de ser més competitiu al mercat i sobretot, anar per davant a la teva competència. El cas és, que en la mineria del Wolframi, actualment, s’ha de processar tot el material que s’extreu de la mina quan la llei de la wolframita és ridícula. Això suposa una enorme despesa de temps i diners, que es gasten processant tones i tones de material per acabar obtenint quantitats ínfimes de wolframita. I si es poguessin saltar uns quants passos del processament gracies a la Intel·ligència Artificial? En el present Treball Final de Grau es dissenya i s’analitza l’eficiència d’un detector de wolframita en una mostra donada, a parir de les característiques subministrades pels píxels d’un seguit d’imatges digitals i aplicant tècniques de Machine Learning. On s’han realitzat un seguit de proves utilitzant diferents algoritmes i així valorar amb quin o quins d’ells s’obté millor resultat.

Country
Spain
Keywords

Àrees temàtiques de la UPC::Enginyeria civil::Enginyeria de mines::Processament de minerals, Image processing--Digital techniques, Imatges -- Processament -- Tècniques digitals, Minerals--Analysis, Tungstè, :Enginyeria civil::Enginyeria de mines::Processament de minerals [Àrees temàtiques de la UPC], Minerals -- Anàlisi, Tungsten--Analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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