Automatic counting of fish larvae using computer vision based on neural networks
Fish larvae counting is a technique applied in aquaculture to determine the efficiency of the induction stage and to know the number of fertilized larvae. For this reason, the research aims to improve the count of larvae under 3 fundamental pillars: precision, error and time. For this, we carried ou...
Guardado en:
| Autores principales: | , , , , |
|---|---|
| Formato: | Artículo |
| Lenguaje: | inglés |
| Publicado: |
Universidad Nacional de Trujillo
2022
|
| Materias: | |
| Acceso en línea: | Enlace permanente (DOI o Handle) |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1881508979714031616 |
|---|---|
| author | Guelac Gomez, Jhordani Sánchez Calle, Jeison Elí Valles-Coral, Miguel Angel Nakagawa, Nixon Chichipe, Ariel |
| author_browse | Chichipe, Ariel Guelac Gomez, Jhordani Nakagawa, Nixon Sánchez Calle, Jeison Elí Valles-Coral, Miguel Angel |
| author_facet | Guelac Gomez, Jhordani Sánchez Calle, Jeison Elí Valles-Coral, Miguel Angel Nakagawa, Nixon Chichipe, Ariel |
| author_sort | Guelac Gomez, Jhordani |
| collection | Producción científica |
| description | Fish larvae counting is a technique applied in aquaculture to determine the efficiency of the induction stage and to know the number of fertilized larvae. For this reason, the research aims to improve the count of larvae under 3 fundamental pillars: precision, error and time. For this, we carried out an experimental investigation under a completely randomized design with two counting systems: traditional and artificial vision; each one with 10 repetitions, with 2000 larvae; Later, we carried out the count by means of artificial vision using a camera that captured images of a fish tank with moving fish. The results show that the proposed method is feasible for counting larvae, with 92.65% accuracy, 7.41% error and an average time of 61 seconds per repetition in relation to the traditional counting system: accuracy 64.44%, error 35.61% and time 2009.3 s. The developed system can be replicated in the aquaculture sector due to its effectiveness and cost. |
| format | Article |
| id | oai:cris.upeu.edu.pe:20.500.15037/3110 |
| institution | UPeU |
| language | English |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Universidad Nacional de Trujillo |
| publisherStr | Universidad Nacional de Trujillo |
| record_format | dspace |
| spelling | oai:cris.upeu.edu.pe:20.500.15037/31102026-10-30T17:09:43ZAutomatic counting of fish larvae using computer vision based on neural networksConteo automático de larvas de peces utilizando visión por computadora basado en redes neuronalesGuelac Gomez, JhordaniSánchez Calle, Jeison ElíValles-Coral, Miguel AngelNakagawa, NixonChichipe, Arielacuiculturaautomatizacióncontador automáticopeces ornamentalesvisión por computadoraaquacultureautomationautomatic counterornamental fishcomputer visionFish larvae counting is a technique applied in aquaculture to determine the efficiency of the induction stage and to know the number of fertilized larvae. For this reason, the research aims to improve the count of larvae under 3 fundamental pillars: precision, error and time. For this, we carried out an experimental investigation under a completely randomized design with two counting systems: traditional and artificial vision; each one with 10 repetitions, with 2000 larvae; Later, we carried out the count by means of artificial vision using a camera that captured images of a fish tank with moving fish. The results show that the proposed method is feasible for counting larvae, with 92.65% accuracy, 7.41% error and an average time of 61 seconds per repetition in relation to the traditional counting system: accuracy 64.44%, error 35.61% and time 2009.3 s. The developed system can be replicated in the aquaculture sector due to its effectiveness and cost.Article10.17268/sci.agropecu.2022.0142-s2.0-85135856172https://hdl.handle.net/20.500.15037/3110enScientia AgropecuariaScientia Agropecuaria2077-9917Universidad Nacional de Trujillo2022-06-292026-06-27T02:35:54Z2026-06-27T02:35:54Z |
| spellingShingle | acuicultura automatización contador automático peces ornamentales visión por computadora aquaculture automation automatic counter ornamental fish computer vision Guelac Gomez, Jhordani Sánchez Calle, Jeison Elí Valles-Coral, Miguel Angel Nakagawa, Nixon Chichipe, Ariel Automatic counting of fish larvae using computer vision based on neural networks |
| title | Automatic counting of fish larvae using computer vision based on neural networks |
| title_full | Automatic counting of fish larvae using computer vision based on neural networks |
| title_fullStr | Automatic counting of fish larvae using computer vision based on neural networks |
| title_full_unstemmed | Automatic counting of fish larvae using computer vision based on neural networks |
| title_short | Automatic counting of fish larvae using computer vision based on neural networks |
| title_sort | automatic counting of fish larvae using computer vision based on neural networks |
| topic | acuicultura automatización contador automático peces ornamentales visión por computadora aquaculture automation automatic counter ornamental fish computer vision |
| topic_facet | acuicultura automatización contador automático peces ornamentales visión por computadora aquaculture automation automatic counter ornamental fish computer vision |
| url | https://hdl.handle.net/20.500.15037/3110 |
| work_keys_str_mv | AT guelacgomezjhordani automaticcountingoffishlarvaeusingcomputervisionbasedonneuralnetworks AT sanchezcallejeisoneli automaticcountingoffishlarvaeusingcomputervisionbasedonneuralnetworks AT vallescoralmiguelangel automaticcountingoffishlarvaeusingcomputervisionbasedonneuralnetworks AT nakagawanixon automaticcountingoffishlarvaeusingcomputervisionbasedonneuralnetworks AT chichipeariel automaticcountingoffishlarvaeusingcomputervisionbasedonneuralnetworks AT guelacgomezjhordani conteoautomaticodelarvasdepecesutilizandovisionporcomputadorabasadoenredesneuronales AT sanchezcallejeisoneli conteoautomaticodelarvasdepecesutilizandovisionporcomputadorabasadoenredesneuronales AT vallescoralmiguelangel conteoautomaticodelarvasdepecesutilizandovisionporcomputadorabasadoenredesneuronales AT nakagawanixon conteoautomaticodelarvasdepecesutilizandovisionporcomputadorabasadoenredesneuronales AT chichipeariel conteoautomaticodelarvasdepecesutilizandovisionporcomputadorabasadoenredesneuronales |