Pedro José de Melo Teixeira Pinto Integrated Member

BIO

Name: Pedro José de Melo Teixeira Pinto

Aggregation: Integrated Member

Scopus author ID: 56538928200

Orcid ID: 0000-0001-8257-0143

Ciência Vitae: 9011-BFDC-7EDC

Email: pmelo@utad.pt

Phone: 259350753

Publications

Boosting the performance of SOTA convolution-based networks with dimensionality reduction: An application on hyperspectral images of wine grape berries
Silva R., Gramaxo Freitas O., Melo-Pinto P., (2023) Boosting the performance of SOTA convolution-based networks with dimensionality reduction: An application on hyperspectral images of wine grape berries Intelligent Systems with Applications 19 (200252). doi: 10.1016/j.iswa.2023.200252.

Classification of Fish Species Using Multispectral Data from a Low-Cost Camera and Machine Learning
Monteiro F., Bexiga V., Chaves P., Godinho J., Henriques D., Melo-Pinto P., Nunes T., Piedade F., Pimenta N., Sustelo L., Fernandes A.M., (2023) Classification of Fish Species Using Multispectral Data from a Low-Cost Camera and Machine Learning Remote Sensing 15 (3952). ISSN: 20724292. doi: 10.3390/rs15163952.

Early yield prediction in different grapevine varieties using computer vision and machine learning
Palacios F., Diago M.P., Melo-Pinto P., Tardaguila J., (2023) Early yield prediction in different grapevine varieties using computer vision and machine learning Precision Agriculture 24 :407-435. ISSN: 15731618. doi: 10.1007/s11119-022-09950-y.

Multi-agent System for Multimodal Machine Learning Object Detection
Coelho E., Pimenta N., Peixoto H., Durães D., Melo-Pinto P., Alves V., Bandeira L., Machado J., Novais P., (2023) Multi-agent System for Multimodal Machine Learning Object Detection Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 14001 LNAI :673-681. ISSN: 16113349. doi: 10.1007/978-3-031-40725-3_57.

t-SNE: A study on reducing the dimensionality of hyperspectral data for the regression problem of estimating oenological parameters
Silva R., Melo-Pinto P., (2023) t-SNE: A study on reducing the dimensionality of hyperspectral data for the regression problem of estimating oenological parameters Artificial Intelligence in Agriculture 7 :58-68. ISSN: 25897217. doi: 10.1016/j.aiia.2023.02.003.

Customizable FPGA-Based Hardware Accelerator for Standard Convolution Processes Empowered with Quantization Applied to LiDAR Data
Silva J., Pereira P., Machado R., Névoa R., Melo-Pinto P., Fernandes D., (2022) Customizable FPGA-Based Hardware Accelerator for Standard Convolution Processes Empowered with Quantization Applied to LiDAR Data Sensors 22 (2184). doi: 10.3390/s22062184.

Deep learning and computer vision for assessing the number of actual berries in commercial vineyards
Palacios F., Melo-Pinto P., Diago M.P., Tardaguila J., (2022) Deep learning and computer vision for assessing the number of actual berries in commercial vineyards Biosystems Engineering 218 :175-188. doi: 10.1016/j.biosystemseng.2022.04.015.

Positron Emission Tomography Image Segmentation Based on Atanassov’s Intuitionistic Fuzzy Sets
Couto P., Bento T., Bustince H., Melo-Pinto P., (2022) Positron Emission Tomography Image Segmentation Based on Atanassov’s Intuitionistic Fuzzy Sets Applied Sciences (Switzerland) 12 (4865). ISSN: 20763417. doi: 10.3390/app12104865.

A review of different dimensionality reduction methods for the prediction of sugar content from hyperspectral images of wine grape berries
Silva R., Melo-Pinto P., (2021) A review of different dimensionality reduction methods for the prediction of sugar content from hyperspectral images of wine grape berries Applied Soft Computing 113 (107889). doi: 10.1016/j.asoc.2021.107889.

Application of hyperspectral imaging and deep learning for robust prediction of sugar and ph levels in wine grape berries
Gomes V., Mendes-Ferreira A., Melo-Pinto P., (2021) Application of hyperspectral imaging and deep learning for robust prediction of sugar and ph levels in wine grape berries Sensors 21 (3459). doi: 10.3390/s21103459.

Determination of sugar, ph, and anthocyanin contents in port wine grape berries through hyperspectral imaging: An extensive comparison of linear and non-linear predictive methods
Gomes V., Rendall R., Reis M.S., Mendes-Ferreira A., Melo-Pinto P., (2021) Determination of sugar, ph, and anthocyanin contents in port wine grape berries through hyperspectral imaging: An extensive comparison of linear and non-linear predictive methods Applied Sciences (Switzerland) 11 (10319). ISSN: 20763417. doi: 10.3390/app112110319.

Object Detection Under Challenging Lighting Conditions Using High Dynamic Range Imagery
Mukherjee, R. ; Bessa, M. ; Melo-Pinto, P. ; Chalmers, A. (2021) Object Detection Under Challenging Lighting Conditions Using High Dynamic Range Imagery IEEE Acess 9 :71-83. doi: 10.1109/ACCESS.2021.3082293. (Impact factor, Quartile: 3.367, Q2).

Prediction of sugar content in port wine vintage grapes using machine learning and hyperspectral imaging
Gomes V., Reis M.S., Rovira-Más F., Mendes-Ferreira A., Melo-Pinto P., (2021) Prediction of sugar content in port wine vintage grapes using machine learning and hyperspectral imaging Processes 9 (1241). ISSN: 22279717. doi: 10.3390/pr9071241.

Towards robust Machine Learning models for grape ripeness assessment
Gomes V., Melo-Pinto P., (2021) Towards robust Machine Learning models for grape ripeness assessment JCSSE 2021 - 18th International Joint Conference on Computer Science and Software Engineering: Cybernetics for Human Beings (9493822). doi: 10.1109/JCSSE53117.2021.9493822.

Grapevine variety identification using “Big Data” collected with miniaturized spectrometer combined with support vector machines and convolutional neural networks
Fernandes A.M., Utkin A.B., Eiras-Dias J., Cunha J., Silvestre J., Melo-Pinto P., (2019) Grapevine variety identification using “Big Data” collected with miniaturized spectrometer combined with support vector machines and convolutional neural networks Computers and Electronics in Agriculture 163 (104855). doi: 10.1016/j.compag.2019.104855.

Assessment of grapevine variety discrimination using stem hyperspectral data and AdaBoost of random weight neural networks.
Fernandes, Armando; Utkin, Andrei; Eiras-Dias, José; Silvestre, José; Cunha, Jorge; Melo-Pinto, Pedro. (2018) Assessment of grapevine variety discrimination using stem hyperspectral data and AdaBoost of random weight neural networks. Applied Soft Computing 72 :140 - 155. doi: 10.1016/j.asoc.2018.07.059. (Impact factor, Quartile: 3.907, Q1).

Using Support Vector Regression and Hyperspectral Imaging for the Prediction of Oenological Parameters on Different Vintages and Varieties of Wine Grape Berries.
Silva, Rui; Gomes, Veronique; Mendes-Faia, Arlete; Melo-Pinto, Pedro (2018) Using Support Vector Regression and Hyperspectral Imaging for the Prediction of Oenological Parameters on Different Vintages and Varieties of Wine Grape Berries. Remote Sensing 10 (2). doi: 10.3390/rs10020312. (Impact factor, Quartile: 3.406, Q2).

Characterization of neural network generalization in the determination of pH and anthocyanin content of wine grape in new vintages and varieties.
Gomes, V, Fernandes, A, Martins-Lopes, P, Pereira, L, Faia, AM, Melo-Pinto, P (2017) Characterization of neural network generalization in the determination of pH and anthocyanin content of wine grape in new vintages and varieties. Food Chemisry 218 :40-46. ISSN: 0308-8146. doi: 10.1016/j.foodchem.2016.09.024. (Impact factor, Quartile: 4.529, Q1).

Comparison of different approaches for the prediction of sugar content in new vintages of whole Port wine grape berries using hyperspectral imaging.
Gomes, VM, Fernandes, AM, Faia, A, Melo-Pinto, P (2017) Comparison of different approaches for the prediction of sugar content in new vintages of whole Port wine grape berries using hyperspectral imaging. Computers And Electronics In Agriculture 140 :244-254. ISSN: 0168-1699. doi: 10.1016/j.compag.2017.06.009. (Impact factor, Quartile: 2.201, Q1).

Computed tomography and radiographic assessment of congruity between the ulnar trochlear notch and humeral trochlea in large breed dogs.
Alves-Pimenta, S, Ginja, MM, Fernandes, AM, Ferreira, AJ, Melo-Pinto, P, Colaço, B (2017) Computed tomography and radiographic assessment of congruity between the ulnar trochlear notch and humeral trochlea in large breed dogs. Veterinary And Comparative Orthopaedics And Traumatology 30 :14-Aug. ISSN: 0932-0814. doi: 10.3415/VCOT-16-03-0045. (Impact factor, Quartile: 0.917, Q2).

Radiographic assessment of humeroulnar congruity in amedium and a large breed of dog.
Alves-Pimenta, S, Colaço, B, Fernandes, AM, Goncalves, L, Colaço, J, Melo-Pinto, P, Ginja, MM (2017) Radiographic assessment of humeroulnar congruity in amedium and a large breed of dog. Veterinary Radiology & Ultrasound 58 :627-633. ISSN: 1058-8183. doi: 10.1111/vru.12521. (Impact factor, Quartile: 1.137, Q2).

Projects

MultiCam - Low Cost Multispectral Camera (POCI-01-0247-FEDER-69271)
Concluded

Coordinator  /  José Luís Melo UTAD/CITAB Coordinator  /  Pedro Pinto
Start date  /  2021/02 Funding  /  ANI - COMPETE-POCI Reference  /  POCI-01-0247-FEDER-69271


INTERACT - Integrative Research in Environment, Agro-Chains and Technology
Concluded

Coordinator  /  Rui Cortes
Start date  /  2016/05 Funding  /  NORTE2020 Reference  /  NORTE-01-0145-FEDER-000017


Deus ex Machina: Symbiotic technology for societal efficiency gains
Concluded

UTAD/CITAB Coordinator  /  Pedro Pinto
Start date  /  2016/01 Funding  /  Norte2020 Reference  /  NORTE-01-0145-FEDER-000026


A New Tool for Intelligent Computing: Autoadapted Aggregation Functions for Classification and Decision Making Problems
Concluded

Coordinator  /  Humberto Bustince (UPNa, Spain) UTAD/CITAB Coordinator  /  Pedro Pinto
Start date  /  2014/11 Funding  /  Ministerio de Economia y Competitividad, Spain


VITINOV – Innovation in Harvesting Systems for Steep Slope Viticulture
Concluded

Coordinator  /  Fernando Alves UTAD/CITAB Coordinator  /  Eduardo Rosa
Start date  /  2014/09 Funding  /  ProDer Reference  /  PRODER 52306


PAFE – Program for Agro-food Environment - ENOEXEL
Concluded

Coordinator  /  Arlete Faia UTAD/CITAB Coordinator  /  Pedro Pinto
Start date  /  2013/01 Funding  /  CCDR-N Reference  /  NORTE-01-0124-FEDER-000033


Hyper - Aplicação de imagens hiperespectrais e redes neurais em viticultura
Concluded

Coordinator  /  Pedro Pinto
Start date  /  2012/04 Funding  /  FCT Reference  /  PTDC/EEA-AUT/121056/2010


Ciência em Sintonia
Concluded

Coordinator  /  Carla Marinho
Start date  /  2011/03 Funding  /  FEDER and Ciência Viva


Computer Vision for UAV
Concluded

Coordinator  /  Pascual Campoy UTAD/CITAB Coordinator  /  Pedro Pinto
Start date  /  2011/01 Funding  /  Plan Nacional de I + D + i 2008-2011. Ministerio de Ciencia y Innovación. Spain Reference  /  DPI2010-20751-C02-01


New Information Representation and Aggregation Model using Fuzzy Sets Extensions. Applications.
Concluded

Coordinator  /  Humberto Bustince UTAD/CITAB Coordinator  /  Pedro Pinto
Start date  /  2011/01 Funding  /  Plan Nacional de I + D + i 2010-2012. Ministerio de Ciencia y Innovación. Spain Reference  /  TIN2007-65981