Deep Learning Applications in Agriculture: A Short Review

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2020

Autores

Santos, L (Autor) Outra; Filipe Neves Santos (Autor) FEUP; Oliveira, PM (Autor) Outra; Shinde, P (Autor) Outra

Ata de Conferência Internacional

Título: FOURTH IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, ROBOT 2019, VOL 1

Páginas: 139-151

4th Iberian Robotics Conference (Robot) - Advances in Robotics

Porto, PORTUGAL, NOV 20-22, 2019

Indexação

ISI Web of Knowledge - 62 Citações

Scopus - 93 Citações

Outras Informações

ID Authenticus: P-00R-CG4

DOI: 10.1007/978-3-030-35990-4_12

Abstract (EN): Deep learning (DL) incorporates a modern technique for image processing and big data analysis with large potential. Deep learning is a recent tool in the agricultural domain, being already successfully applied to other domains. This article performs a survey of different deep learning techniques applied to various agricultural problems, such as disease detection/identification, fruit/plants classification and fruit counting among other domains. The paper analyses the specific employed models, the source of the data, the performance of each study, the employed hardware and the possibility of real-time application to study eventual integration with autonomous robotic platforms. The conclusions indicate that deep learning provides high accuracy results, surpassing, with occasional exceptions, alternative traditional image processing techniques in terms of accuracy.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 13