Resultados de búsqueda - "computer vision"

Tolerance to spittlebugs (Aeneolamia varia) in Urochloa spp. and Megathyrsus maximus grasses: A dataset for plant damage phenotyping por Ruiz-Hurtado, Andres Felipe, Espitia-Buitrago, Paula, Hernández, Luis Miguel, Jauregui, Rosa N., Cardoso, Juan Andres

Materias: “…imagery-computer vision…”
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Maturity assessment of ‘Rojo Brillante’ persimmon by Hyperspectral Imaging por Munera, Sandra, Blasco, José, Cubero, Sergio, Besada, Cristina, Salvador, Alejandra, Talens, Pau, Aleixos, Nuria

Materias: “…Computer vision…”
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Enlace del recurso

Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging por Munera, Sandra, Besada, Cristina, Aleixos, Nuria, Talens, Pau, Salvador, Alejandra, Sun, Da-Wen, Cubero, Sergio, Blasco, José

Materias: “…Diospyros kaki, internal fruit quality, soluble tannins, astringency, classification, computer vision.…”
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Enlace del recurso

Astringency assessment of persimmon by hyperspectral imaging por Munera, Sandra, Besada, Cristina, Blasco, José, Cubero, Sergio, Salvador, Alejandra, Talens, Pau, Aleixos, Nuria

Materias: “…Diospyros kaki, fruit internal quality, soluble tannins, distribution map, hyperspectral imaging, computer vision…”
Enlace del recurso
Enlace del recurso

Preliminary approach for the detection of olive trees infected by Xylella fastidiosa using a field robot and proximal sensing por López, Santiago, Cubero, Sergio, Aleixos, Nuria, Alegre, Vicente, Rey, Beatriz, Aguilar, Enrique, Blasco, José

Materias: “…Computer vision…”
Enlace del recurso
Enlace del recurso

Colour segmentation of citrus fruits images for stem location por Ruiz, L. A., Moltó, Enrique, Juste, Florentino

Materias: “…Computer vision…”
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Updating high-resolution image dataset for the automatic classification of phenological stage and identification of racemes in Urochloa spp. hybrids with expanded images and annota... por Arrechea-Castillo, Darwin Alexis, Espitia-Buitrago, Paula, Florian-Vargas, David, Estupinan, Ronald David, Velázquez-Hernández, Riquelmer, Ruiz-Hurtado, Andres Felipe, Hernandez, Luis Miguel, Jauregui, Rosa Noemi, Cardoso, Juan Andres

Materias: “…imagery-computer vision…”
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TreeEyed: A QGIS plugin for tree monitoring in silvopastoral systems using state of the art AI models por Ruiz-Hurtado, Andres Felipe, Bolaños, Juliana Perez, Arrechea-Castillo, Darwin Alexis, Cardoso, Juan Andres

Materias: “…imagery-computer vision…”
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La implementación de visión por computadora basada en Inteligencia Artificial reveló variabilidad en caracteres del durazno contenida en una colección de germoplasma por Sanchez, Gerardo, Churichi, Alan X., Valentini, Gabriel Hugo, Aballay, Maximiliano Martín

Materias: “…Computer Vision…”
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BioTango: aplicar la inteligencia artificial para transformar la fruticultura por Sanchez, Gerardo

Materias: “…Computer Vision…”
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Enlace del recurso

Detection of Invisible Damages in ‘Rojo Brillante’ Persimmon Fruit at Different Stages Using Hyperspectral Imaging and Chemometrics por Munera, Sandra, Rodríguez-Ortega, Alejandro, Aleixos, Nuria, Cubero, Sergio, Gómez-Sanchís, Juan, Blasco, José

Materias: “…Computer vision…”
Enlace del recurso
Enlace del recurso

TreeEyed: QGIS plugin for tree monitoring por Ruiz-Hurtado, Andres Felipe, Cardoso Arango, Juan Andres

Materias: “…imagery-computer vision…”
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Implementing artificial intelligence to measure meat quality parameters in local market traceability processes por Alvarez García, Wuesley Yusmein, Mendoza, Laura, Muñoz Vílchez, Yudith Yohany, Casanova Núñez Melgar, David, Quilcate Pairazaman, Carlos

Materias: “…Computer vision…”
Enlace del recurso
Enlace del recurso

Study of light penetration depth of a Vis-NIR hyperspectral imaging system for the assessment of fruit quality. A case study in persimmon fruit por García-García, José, Rodríguez-Ortega, Alejandro, Aleixos, Nuria, Blasco, José, Albert, Francisco, Munera, Sandra

Materias: “…Computer vision…”
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Enlace del recurso

Detección automática de podredumbres en cítricos mediante análisis de imágenes backscattering por Lorente, Delia, Cubero, Sergio, Blasco, José, Zude, Manuela, Regen, C., Palou, Lluís, Gómez-Sanchís, Juan

Materias: “…Computer vision…”
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Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying por Udomkun, Patchimaporn, Nagle, Marcus, Argyropoulos, D., Mahayothee, B., Müller, Joachim

“…This study aimed to assess the feasibility of a multi-sensor approach for predicting shrinkage of papaya during drying using computer vision methods in combination with optical scattering analysis of light at 650 nm. …”
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Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features por Blasco, José, Aleixos, Nuria, Gómez-Sanchís, Juan, Moltó, Enrique

“…In this paper, we present a computer vision system that was developed for the recognition and classification of the most common external defects in citrus. in order to discriminate between 11 types of defects, images of the defects were acquired in five spectral areas, including the study of near infrared reflectance and ultraviolet induced fluorescence. …”
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Quality Evaluation of Citrus Fruits por Blasco, José, Cubero, Sergio, Moltó, Enrique

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Enlace del recurso
Enlace del recurso

Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review por Cubero, Sergio, Lee, Won Suk, Aleixos, Nuria, Albert, Francisco, Blasco, José

“…Computer vision systems are becoming a scientific but also a commercial tool for food quality assessment. …”
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Enlace del recurso

Automatic correction of the effects of the light source on spherical objects. An application to the analysis of hyperspectral images of citrus fruits por Gómez-Sanchís, Juan, Moltó, Enrique, Camps-Valls, G., Gomez-Chova, L., Aleixos, Nuria, Blasco, José

“…This study proposes a method for correcting the adverse effects produced by the curvature of spherical objects in acquiring images with a computer vision system. Its suitability has been illustrated in a specific case of citrus fruits. …”
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