Results 11 to 20 of about 20,056 (237)
Evolutionary Spiking Neural Networks for Solving Supervised Classification Problems. [PDF]
Comput Intell Neurosci, 2019 This paper presents a grammatical evolution (GE)‐based methodology to automatically design third generation artificial neural networks (ANNs), also known as spiking neural networks (SNNs), for solving supervised classification problems. The proposal performs the SNN design by exploring the search space of three‐layered feedforward topologies with ...
López-Vázquez G +7 more
europepmc +2 more sources
Revista de Educación Matemática, 2021 Una Red Neuronal Artificial es un modelo matemático inspirado en el comportamiento biológico de las neuronas y en la estructura del cerebro, y que es utilizada para resolver un amplio rango de problemas. Debido a su flexividad, una única red neuronal es capaz de realizar diversas tareas.
Claudio Javier Tablada +1 more
openaire +2 more sources
Realización física de redes neuronales artificiales (neurocomputadores)
, 1995 Este libro presenta un intento serio y razonablemente completo de reflexión sobre el estado actual del conocimiento en el campo de la computación neuronal y en su forma de plantear y resolver algunos de estos problemas. Actualmente se entiende por computación neuronal toda computación modular, distribuida, con procesos y/o procesadores autónomos y de ...
Joan Cabestany +2 more
openalex +2 more sources
Reconocimiento del habla mediante redes neuronales artificiales
INTELIGENCIA ARTIFICIAL, 1997 M.J. Castro
openalex +2 more sources
Redes neuronales artificiales aplicadas en sistemas de predicción para la seguridad vial
Avances, 2020 En esta investigación se aplican redes neuronales artificiales para el análisis de variables que podrían tener influencia en la ocurrencia de accidentes de tránsito en carreteras de montaña.
Karina Patricia Carpio +1 more
doaj +1 more source
RFIDeep: Unfolding the potential of deep learning for radio‐frequency identification
Methods in Ecology and Evolution, Volume 14, Issue 11, Page 2814-2826, November 2023., 2023 Abstract Automatic monitoring of wildlife is becoming a critical tool in the field of ecology. In particular, Radio‐Frequency IDentification (RFID) is now a widespread technology to assess the phenology, breeding and survival of many species. While RFID produces massive datasets, no established fast and accurate methods are yet available for this type ...
Gaël Bardon +20 more
wiley +1 more source
JDDG: Journal der Deutschen Dermatologischen Gesellschaft, Volume 21, Issue 8, Page 863-871, August 2023., 2023 Zusammenfassung Hintergrund Dermatologische Erkrankungen sind in allen Bevölkerungsgruppen weit verbreitet. Das betroffene Körperteil ist für ihre Diagnose, Therapie und Forschung von Bedeutung. Die automatische Identifizierung der abgebildeten Körperteile in dermatologischen Krankheitsbildern könnte daher die klinische Versorgung verbessern, indem sie
Sebastian Sitaru +7 more
wiley +1 more source
Application of a deep learning image classifier for identification of Amazonian fishes
Ecology and Evolution, Volume 13, Issue 5, May 2023., 2023 To address the growing prevalence of large ecological datasets combined with a need for rapid species identification tools, we describe a novel application of a computer vision model, which is built to rapidly identify Amazonian fishes from captured image data.
Alexander J. Robillard +7 more
wiley +1 more source
Ciencia Ergo Sum, 2023 Se utilizan técnicas de reconocimiento de patrones para identificar hojas sanas y cuatro enfermedades de la planta del café Coffeea arabica. Las enfermedades son la roya del café, el minador de la hoja, phoma quema y Cercospora coffeicola. Para lograrlo,
Oscar Eder Flores Colorado +3 more
doaj +1 more source
Using deep convolutional neural networks to forecast spatial patterns of Amazonian deforestation
Methods in Ecology and Evolution, Volume 13, Issue 11, Page 2622-2634, November 2022., 2022 Abstract Tropical forests are subject to diverse deforestation pressures while their conservation is essential to achieve global climate goals. Predicting the location of deforestation is challenging due to the complexity of the natural and human systems involved but accurate and timely forecasts could enable effective planning and on‐the‐ground ...
James G. C. Ball +3 more
wiley +1 more source