Image recognition of Legacy blueberries in a Chilean smart farm through deep learning

Agriculture is one of the most important pillars of development in Chile. However, it is expected that around the year 2030 there is going to be a gradual decrease in the number of farmers. Therefore, it is necessary to replace this workforce with technology and mechanization. One way to do this is...

Πλήρης περιγραφή

Αποθηκεύτηκε σε:
Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Quiroza, Ignacio A. (autor)
Άλλοι συγγραφείς: Alférez, Germán H. (coautor)
Μορφή: Ηλ. βιβλίο
Γλώσσα:Αγγλικά
Θέματα:
Διαθέσιμο Online:https://repositoriobiblio.unach.cl/handle/123456789/1424
Ετικέτες: Προσθήκη ετικέτας
Δεν υπάρχουν, Καταχωρήστε ετικέτα πρώτοι!

MARC

LEADER 00000nam a22000005a 4500
001 125-2020
003 CL-ChUAC
005 20250113144507.0
006 m o d |
007 cr cn|||||||||
008 210609s2020 ne |||||s|||| 000 ||eng d
022 |a 0168-1699 
040 |a CL-ChUAC  |b spa  |c CL-ChUAC 
041 |a eng  |b eng  |f eng 
100 1 |a Quiroza, Ignacio A.  |e autor 
245 1 0 |a Image recognition of Legacy blueberries in a Chilean smart farm through deep learning  |c A. Quiroza, Ignacio ; H. Alférez, Germán 
336 |2 rdacontent   |a text  |b txt 
337 |2 rdamedia  |a unmediated  |b n 
338 |2 rdacarrier   |a volume  |b nc 
520 3 |a Agriculture is one of the most important pillars of development in Chile. However, it is expected that around the year 2030 there is going to be a gradual decrease in the number of farmers. Therefore, it is necessary to replace this workforce with technology and mechanization. One way to do this is through smart farms to leverage agricultural production. The contribution of this research work is a novel approach for deep-learning image recognition of Legacy blueberries in the rooting stage that can be used in smart farms in Chile. Legacy blueberry is a variety of Southern Highbush blueberry. This species constitutes 80% of the blueberry crops in Chile. Specifically, we propose an image recognition approach based on a convolutional neural network (CNN) to detect the presence of trays with living blueberry plants, the presence of trays without living plants, and the absence of trays. The average results of the evaluation of the predictive model are as follows: accuracy: 86%, precision: 86%, recall: 88%, and F1 score: 86%. 
650 4 |a Convolutional neural networks 
650 4 |a Smart farms 
650 4 |a Image recognition 
650 4 |a Legacy blueberry 
700 1 |a Alférez, Germán H.  |e coautor 
773 0 |d Ámsterdam, Países Bajos  |g Volume 168, January 2020, 105044  |t Computers and Electronics in Agriculture [artículo de revista]  
856 4 1 |u https://repositoriobiblio.unach.cl/handle/123456789/1424 
942 |2 ddc  |c AREV 
999 |c 2366425  |d 2366425