Mauro Francisco
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Mauro Francisco has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Fernando Ribeiro
School of Technology, Polytechnic Institute of Castelo Branco, 6000-081 Castelo Branco, Portugal
1 shared publication - José Metrôlho
School of Technology, Polytechnic Institute of Castelo Branco, 6000-081 Castelo Branco, Portugal
1 shared publication - Rogério Dionísio
R&D Unit in Digital Services, Applications and Content, Polytechnic Institute of Castelo Branco, 6000-767 Castelo Branco, Portugal
1 shared publication
Latest Publications
- Open Access
- 9 April 2023
- Published by MDPI AG in Applied Sciences
- Vol. 13 (8) , 4720
Algorithms and Models for Automatic Detection and Classification of Diseases and Pests in Agricultural Crops: A Systematic Review
Plant diseases and pests significantly influence food production and the productivity and economic profitability of agricultural crops. This has led to great interest in developing technological solutions to enable timely and accurate detection. This systematic review aimed to find studies on the automation of processes to detect, identify and classify diseases and pests in agricultural crops. The goal is to characterize the class of algorithms, models and their characteristics and understand the efficiency of the various approaches and their applicability. The literature search was conducted in two citation databases. The initial search returned 278 studies and, after removing duplicates and applying the inclusion and exclusion criteria, 48 articles were included in the review. As a result, seven research questions were answered that allowed a characterization of the most studied crops, diseases and pests, the datasets used, the algorithms, their inputs and the levels of accuracy that have been achieved in automatic identification and classification of diseases and pests. Some trends that have been most noticed are also highlighted.
- 9 April 2023
- Published by MDPI AG in Applied Sciences
- Vol. 13 (8) , 4720
Open AccessAlgorithms and Models for Automatic Detection and Classification of Diseases and Pests in Agricultural Crops: A Systematic Review
Plant diseases and pests significantly influence food production and the productivity and economic profitability of agricultural crops. This has led to great interest in developing technological solutions to enable timely and accurate detection. This systematic review aimed to find studies on the automation of processes to detect, identify and classify diseases and pests in agricultural crops. The goal is to characterize the class of algorithms, models and their characteristics and understand the efficiency of the various approaches and their applicability. The literature search was conducted in two citation databases. The initial search returned 278 studies and, after removing duplicates and applying the inclusion and exclusion criteria, 48 articles were included in the review. As a result, seven research questions were answered that allowed a characterization of the most studied crops, diseases and pests, the datasets used, the algorithms, their inputs and the levels of accuracy that have been achieved in automatic identification and classification of diseases and pests. Some trends that have been most noticed are also highlighted.