J. Barbedo

发表

Expert Systems Applied to Plant Disease Diagnosis: Survey and Critical View

J. G. A. Barbedo, J. Barbedo, 2016, IEEE Latin America Transactions.

Perspectives on the use of unmanned aerial systems to monitor cattle

Luciano Vieira Koenigkan, J. Barbedo, L. V. Koenigkan, 2018, Outlook on Agriculture.

An Automatic Method to Detect and Measure Leaf Disease Symptoms Using Digital Image Processing.

Jayme Garcia Arnal Barbedo, J. Barbedo, 2014, Plant disease.

A novel algorithm for semi-automatic segmentation of plant leaf disease symptoms using digital image processing

J. G. A. Barbedo, J. Barbedo, 2016, Tropical Plant Pathology.

A new automatic method for disease symptom segmentation in digital photographs of plant leaves

Jayme Garcia Arnal Barbedo, J. Barbedo, 2017, European Journal of Plant Pathology.

Deoxynivalenol screening in wheat kernels using hyperspectral imaging

J. Barbedo, C. S. Tibola, M. I. P. Lima, 2017 .

The use of infrared images to detect ticks in cattle and proposal of an algorithm for quantifying the infestation.

Jayme Garcia Arnal Barbedo, J. Barbedo, F. Cardoso, 2017, Veterinary parasitology.

A special issue on phytopathometry — visual assessment, remote sensing, and artificial intelligence in the twenty-first century

J. Barbedo, Anne-Katrin Mahlein, C. Bock, 2022, Tropical Plant Pathology.

Cattle Detection Using Oblique UAV Images

Luciano Vieira Koenigkan, J. Barbedo, Patrícia Menezes Santos, 2020, Drones.

A Review on the Use of Computer Vision and Artificial Intelligence for Fish Recognition, Monitoring, and Management

J. Barbedo, 2022, Fishes.

Using digital image processing for counting whiteflies on soybean leaves

Jayme Garcia Arnal Barbedo, J. Barbedo, 2014 .

From visual estimates to fully automated sensor-based measurements of plant disease severity: status and challenges for improving accuracy

Emerson M. Del Ponte, David Bohnenkamp, Clive H. Bock, 2020 .

A phytopathometry glossary for the twenty-first century: towards consistency and precision in intra- and inter-disciplinary dialogues

J. Barbedo, Anne-Katrin Mahlein, P. Esker, 2021, Tropical Plant Pathology.

A special issue on phytopathometry — visual assessment, remote sensing, and artificial intelligence in the twenty-first century

J. Barbedo, Anne-Katrin Mahlein, C. Bock, 2022, Tropical Plant Pathology.

Detecting and Classifying Pests in Crops Using Proximal Images and Machine Learning: A Review

Jayme Garcia Arnal Barbedo, J. Barbedo, 2020, AI.

A New Strategy for Objective Estimation of the Quality of Audio Signals

J.G.A. Barbedo, A. Lopez, J. Barbedo, 2004, IEEE Latin America Transactions.

Strategies to Increase the Applicability of Methods for Objective Assessment of Audio Quality

Jayme Garcia Arnal Barbedo, Amauri Lopes, J. Barbedo, 2004 .

A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses

Jayme Garcia Arnal Barbedo, J. Barbedo, 2019, Drones.

Detection of nutrition deficiencies in plants using proximal images and machine learning: A review

Jayme Garcia Arnal Barbedo, J. Barbedo, 2019, Comput. Electron. Agric..

Improving a Multiple Pitch Estimation Method With AR Models

Jayme G. A. Barbedo, Amauri Lopes, Tiago Fernandes Tavares, 2011, Semantic Audio.

Estimating Frequency, Amplitude and Phase of Two Sinusoids with Very Close Frequencies

Jayme Garcia Arnal Barbedo, Amauri Lopes, J. Barbedo, 2009 .

Data Fusion in Agriculture: Resolving Ambiguities and Closing Data Gaps

J. Barbedo, 2022, Sensors.

Detection of sprout damage in wheat kernels using NIR hyperspectral imaging

Jayme Garcia Arnal Barbedo, J. Barbedo, C. S. Tibola, 2018, Biosystems Engineering.

A review on the main challenges in automatic plant disease identification based on visible range images

Jayme Garcia Arnal Barbedo, J. Barbedo, 2016 .

Using Brainwave Patterns Recorded from Plant Pathology Experts to Increase the Reliability of AI-Based Plant Disease Recognition System

J. Barbedo, Omri Keren, Yaar Shalom, 2023, SSRN Electronic Journal.

Impact of dataset size and variety on the effectiveness of deep learning and transfer learning for plant disease classification

Jayme G. A. Barbedo, J. Barbedo, 2018, Comput. Electron. Agric..

COMPUTER-AIDED DISEASE DIAGNOSIS IN AQUACULTURE: CURRENT STATE AND PERSPECTIVES FOR THE FUTURE

Jayme Garcia Arnal Barbedo, J. Barbedo, 2014 .

Digital image processing techniques for detecting, quantifying and classifying plant diseases.

Jayme Garcia Arnal Barbedo, J. Barbedo, 2013 .

3D Plant Modeling: Localization, Mapping and Segmentation for Plant Phenotyping Using a Single Hand-held Camera

Jayme G. A. Barbedo, Luciano Vieira Koenigkan, Thiago Teixeira Santos, 2014, ECCV Workshops.

Factors influencing the use of deep learning for plant disease recognition

Jayme Garcia Arnal Barbedo, J. Barbedo, 2018, Biosystems Engineering.

A review on the combination of deep learning techniques with proximal hyperspectral images in agriculture

J. Barbedo, 2023, Comput. Electron. Agric..

Deep learning applied to plant pathology: the problem of data representativeness

J. Barbedo, 2021, Tropical Plant Pathology.

Detecting Fusarium head blight in wheat kernels using hyperspectral imaging

Jayme Garcia Arnal Barbedo, José Maurício Cunha Fernandes, Casiane Salete Tibola, 2015 .

Identifying multiple plant diseases using digital image processing

Luciano Vieira Koenigkan, Jayme Garcia Arnal Barbedo, Thiago Teixeira Santos, 2016 .

Influence of image quality on the identification of psyllids using convolutional neural networks

Jayme Garcia Arnal Barbedo, Guilherme B. Castro, J. Barbedo, 2019, Biosystems Engineering.

Deep learning architectures for semantic segmentation and automatic estimation of severity of foliar symptoms caused by diseases or pests

Flora Maria de Melo Villar, J. Barbedo, E. D. Del Ponte, 2021, Biosystems Engineering.

Statistical Analysis of features used in Automatic Audio Genre Classification DOI: 10.14209/jcis.2006.9

J. G. A. barbedo, A. Lopes, J. Barbedo, 2015 .

Automatic object counting in Neubauer chambers.

J. G. A. Barbedo, J. Barbedo, 2013 .

Survey on automatic transcription of music

T. Tavares, R. Attux, J. Barbedo, 2013, Journal of the Brazilian Computer Society.

A Study on the Detection of Cattle in UAV Images Using Deep Learning

Luciano Vieira Koenigkan, Jayme Garcia Arnal Barbedo, Thiago Teixeira Santos, 2019, Sensors.

Counting Cattle in UAV Images—Dealing with Clustered Animals and Animal/Background Contrast Changes

Luciano Vieira Koenigkan, Jayme Garcia Arnal Barbedo, Patrícia Menezes Santos, 2020, Sensors.

A Review on Methods for Automatic Counting of Objects in Digital Images

Jayme Garcia Arnal Barbedo, J. Barbedo, 2012 .

Counting Clustered Soybean Seeds

Jayme G. A. Barbedo, J. Barbedo, 2012, 2012 12th International Conference on Computational Science and Its Applications.

A novel algorithm for semi-automatic segmentation of plant leaf disease symptoms using digital image processing

J. Barbedo, 2016, Tropical Plant Pathology.

Farmers' perception of barriers that difficult the implementation of agriculture 4.0

J. Barbedo, F. G. Amaral, Filipe Molinar Machado, 2023, Agricultural Systems.

Automatic Genre Classification of Musical Signals

Jayme G. A. Barbedo, Amauri Lopes, J. Barbedo, 2007, EURASIP J. Adv. Signal Process..

Deep learning applied to plant pathology: the problem of data representativeness

J. Barbedo, 2021, Tropical Plant Pathology.

Deep Learning for Soybean Monitoring and Management

J. Barbedo, 2023, Seeds.

Unsupervised training of detection threshold for polyphonic musical note tracking based on event periodicity

Romis de Faissol Attux, Jayme G. A. Barbedo, Amauri Lopes, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

System for quantitative diagnosis of COVID-19 associated Pneumonia based on Superpixels with deep learning and chest CT

Everton Castelão Tetila, J. Barbedo, H. Pistori, 2023, OBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANA.

Method for Automatic Counting Root Nodules Using Digital Images

Jayme G. A. Barbedo, J. Barbedo, 2012, 2012 12th International Conference on Computational Science and Its Applications.

A Study on the Use of Semi-Automatic Systems for Counting Objects in Digital Images

J. Barbedo, 2013 .

Automatic Classification of Soybean Diseases Based on Digital Images of Leaf Symptoms

J. Barbedo, C. Godoy, 2015 .

Using hyperspectral images and the Fusarium Index for estimating deoxynivalenol concentration in wheat kernels.

J. Barbedo, C. S. Tibola, 2015 .

A Study on CNN-Based Detection of Psyllids in Sticky Traps Using Multiple Image Data Sources

Jayme Garcia Arnal Barbedo, Guilherme Barros Castro, J. Barbedo, 2020, AI.

Proposal for a framework to manage the barriers that hinder the development of agriculture 4.0 in the agricultural production chain

J. Barbedo, Sabrina Letícia Couto da Silva, F. D. Silveira, 2023, Comput. Electron. Agric..