Trained as containing

Spanish translation: se enseña a detectar anomalías

GLOSSARY ENTRY (DERIVED FROM QUESTION BELOW)
English term or phrase:are trained as containing anomalies
Spanish translation:se enseña a detectar anomalías
Entered by: Beatriz Ramírez de Haro

22:56 Apr 20, 2020
English to Spanish translations [PRO]
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English term or phrase: Trained as containing
Hola a todos...

¿Me ayudan con esto?

Me confunde la idea en este contexto... No el "trained" en sí mismo...

https://www.cognex.com/blogs/deep-learning/deep-learning-for...

Deep learning-based classification works by separating different classes based on a collection of labelled images and identifies products based on these packaging discrepancies

Gracias :)

Débo
Débora Corones
Local time: 18:22
ver dentro
Explanation:
Hola Débora:
Coincido con Lydia en que el contexto donde aparece el término debe ir en el cuerpo de la pregunta. Esa es la condición indispensable, y aparte de eso siempre viene bien facilitar el enlace como referencia general.

Esta es mi interpretación de la frase:

- "Si se enseña al sistema que alguna de las clases contiene anomalías, el sistema puede aprender a clasificarlas como aceptables o inaceptables."

- "Si se enseña al sistema que algunas de las clases contienen anomalías, el sistema puede aprender a clasificarlas como aceptables o inaceptables."

- "Si en cualquiera de las clases se enseña al sistema a detectar anomalías, el sistema puede aprender a clasificarlas como aceptables o inaceptables


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Note added at 21 hrs (2020-04-21 20:52:51 GMT)
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Esta es la expresión en su contexto:
Deep learning-based classification works by separating different classes based on a collection of labelled images and identifies products based on these packaging discrepancies. If any of the classes are trained as containing anomalies, then the system can learn to classify them as acceptable or unacceptable.
Selected response from:

Beatriz Ramírez de Haro
Spain
Local time: 22:22
Grading comment
Selected automatically based on peer agreement.
4 KudoZ points were awarded for this answer



Summary of answers provided
3 +4ver dentro
Beatriz Ramírez de Haro
3 -2ensenhar (la computadora) a ver imagenes con defectos
Tomasso


Discussion entries: 4





  

Answers


1 hr   confidence: Answerer confidence 3/5Answerer confidence 3/5 peer agreement (net): -2
trained as containing
ensenhar (la computadora) a ver imagenes con defectos


Explanation:
The computer is trained to recognize images containing defects, that is anomalies, things not expected. Learning in the program takes time and many examples.
Se toma fotos de los productos, incluyendo los con defectos, o variaciones. Literalmente, hay que** entrenar conteniendo defectos***.
vease a ;https://towardsdatascience.com/train-image-recognition-ai-wi...
En la http dice; concept of Machine Learning was introduced and it ushered in an era in which instead of telling computers what to look out for in recognizing scenes and objects in images and videos, we can instead design algorithms that will make computers to learn how to recognize scenes and objects in images by itself, just like a child learns to understand his/her environment by exploring. Machine learning opened the way for computers to learn to recognize almost any scene or object we want them too.

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Note added at 21 hrs (2020-04-21 20:14:28 GMT)
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http://xinleic.xyz/papers/iccv13.pdf
""We propose NEIL (Never Ending Image Learner), a computer program that runs 24 hours per day and 7 days per
week to automatically extract visual knowledge from Internet data. NEIL uses a semi-supervised learning algorithm that jointly discovers common sense relationships
(e.g., “Corolla is a kind of/looks similar to Car”,“Wheel
is a part of Car”) and labels instances of the given visual
categories. It is an attempt to develop the world’s largest
visual structured knowledge base with minimum human labeling effort. As of 10th October 2013, NEIL has been continuously running for 2.5 months on 200 core cluster (more
than 350K CPU hours) and has an ontology of 1152 object
categories, 1034 scene categories and 87 attributes. During
this period, NEIL has discovered more than 1700 relationships and has labeled more than 400K visual instances.


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Note added at 21 hrs (2020-04-21 20:16:54 GMT)
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Quote op cite "Las computadoras ya consiguen identificar y etiquetar los objetos utilizando la visión artificial de la máquina, pero los investigadores esperan que NEIL aprenda las relaciones entre los diferentes elementos sin ***que hayan sido previamente enseñados.***

Example sentence(s):
  • El programa fue entrenado reconocer productos y su caja, aun si tiene defectos.
  • El progama entrenado completo con variaciones con defectos, puede aparta las cajas defectuosas para revision por humanos, o por otra revision automatica segun programacion.
Tomasso
United States
Local time: 15:22
Native speaker of: Native in EnglishEnglish

Peer comments on this answer (and responses from the answerer)
disagree  Juan Jacob: ¿Ensenhar, imagenes? No.
1 hr

disagree  Lydia De Jorge: This makes no sense. Sorry!
5 hrs
Login to enter a peer comment (or grade)

11 hrs   confidence: Answerer confidence 3/5Answerer confidence 3/5 peer agreement (net): +4
trained as containing
ver dentro


Explanation:
Hola Débora:
Coincido con Lydia en que el contexto donde aparece el término debe ir en el cuerpo de la pregunta. Esa es la condición indispensable, y aparte de eso siempre viene bien facilitar el enlace como referencia general.

Esta es mi interpretación de la frase:

- "Si se enseña al sistema que alguna de las clases contiene anomalías, el sistema puede aprender a clasificarlas como aceptables o inaceptables."

- "Si se enseña al sistema que algunas de las clases contienen anomalías, el sistema puede aprender a clasificarlas como aceptables o inaceptables."

- "Si en cualquiera de las clases se enseña al sistema a detectar anomalías, el sistema puede aprender a clasificarlas como aceptables o inaceptables


--------------------------------------------------
Note added at 21 hrs (2020-04-21 20:52:51 GMT)
--------------------------------------------------

Esta es la expresión en su contexto:
Deep learning-based classification works by separating different classes based on a collection of labelled images and identifies products based on these packaging discrepancies. If any of the classes are trained as containing anomalies, then the system can learn to classify them as acceptable or unacceptable.

Beatriz Ramírez de Haro
Spain
Local time: 22:22
Specializes in field
Native speaker of: Native in SpanishSpanish
PRO pts in category: 1758
Grading comment
Selected automatically based on peer agreement.

Peer comments on this answer (and responses from the answerer)
agree  Marta Moreno Lobera: Esta es la idea.
2 hrs
  -> Muchas gracias Marta - Bea

agree  Mónica Algazi
3 hrs
  -> Muchas gracias Mónica - Bea

agree  Andrea Cerdán Cabrera (X)
3 hrs
  -> Muchas gracias Andrea - Bea

agree  Lydia De Jorge
10 hrs
  -> Muchas gracias Lydia - Bea
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