Mostrando 10 resultados de: 14
Filtros aplicados
Publisher
2022 IEEE ANDESCON: Technology and Innovation for Andean Industry, ANDESCON 2022(1)
Computer Methods and Programs in Biomedicine(1)
Computer Science and Information Systems(1)
IET Computer Vision(1)
IET Image Processing(1)
Área temáticas
Ciencias de la computación(9)
Métodos informáticos especiales(7)
Programación informática, programas, datos, seguridad(3)
Enfermedades(2)
Funcionamiento de bibliotecas y archivos(2)
Automatic skin lesion boundary segmentation using deep learning convolutional networks with weighted cross entropy
OtherAbstract: An automatic segmentation of skin lesions from the dermoscopy images is a key procedure to accuratelPalabras claves:Autores:Edwin Valarezo AnazcoFuentes:googleAn automatic recognition of multi-class skin lesions via deep learning convolutional neural networks
OtherAbstract: An automatic recognition of skin lesions from dermoscopy images is a big challenge task due to the lPalabras claves:Autores:Edwin Valarezo AnazcoFuentes:googleA Single Wearable IMU-based Human Hand Activity Recognition via Deep Autoencoder and Recurrent Neural Networks
OtherAbstract:Palabras claves:Autores:Edwin Valarezo AnazcoFuentes:googleDetection and classification of the breast abnormalities in digital mammograms via regional Convolutional Neural Network
Conference ObjectAbstract: Automatic detection and classification of the masses in mammograms are still a big challenge and plaPalabras claves:Breast Cancer, Computer Aided Diagnosis, deep learning, Mass Detection and Classification, YOLOAutores:Al-Antari M.A., Al-Masni M.A., Edwin Valarezo Anazco, Gi G., Han S.M., Kim T.S., Kim T.Y., Park J.M., Rivera P.Fuentes:googlescopusAn Integrated ARMA-Based Deep Autoencoder and GRU Classifier System for Enhanced Recognition of Daily Hand Activities
ArticleAbstract: Recognition of hand activities of daily living (hand-ADL) is useful in the areas of human-computer iPalabras claves:Autoregressive processes, cnn, deep learning, hand activity recognition, rnn, wearable sensorsAutores:Edwin Valarezo Anazco, Kim T.S., Rivera P.Fuentes:googlescopusHand gesture recognition using single patchable six-axis inertial measurement unit via recurrent neural networks
ArticleAbstract: Recording human gestures from a wearable sensor produces valuable information to implement control gPalabras claves:Control gestures, Hand gesture recognition, Patchable IMU, Recurrent Neural Network, Six-axis inertial sensorAutores:Edwin Valarezo Anazco, Han S.J., Kim K., Kim T.S., Lee S., Rivera P.Fuentes:googlescopusHuman activities recognition with a single writs imu via a variational autoencoder and android deep recurrent neural nets
ArticleAbstract: Human Activity Recognition (HAR) is an active research field because of its versatility towards variPalabras claves:Android Deep Recurrent Neural Networks, Denoising Autoencoder, Human activity recognition, Mobile applicationAutores:Edwin Valarezo Anazco, Kim T.S., Park H., Park N., Rivera P.Fuentes:googlescopusHuman activity recognition using a single wrist IMU sensor via deep learning convolutional and recurrent neural nets
OtherAbstract: In this paper, the authors aimed to propose novel deep learning-based HAR systems with a single wrisPalabras claves:Autores:Edwin Valarezo AnazcoFuentes:googleTrilateral convolutional neural network for 3D shape reconstruction of objects from a single depth view
ArticleAbstract: In this study, the authors propose a novel three-dimensional (3D) convolutional neural network for sPalabras claves:Autores:Choi M.T., Edwin Valarezo Anazco, Kim T.S., Rivera P.Fuentes:googlescopusSimultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system
ArticleAbstract: Background and objective: Automatic detection and classification of the masses in mammograms are stiPalabras claves:Breast Cancer, Computer Aided Diagnosis, deep learning, Mass Detection and Classification, You Only Look Once (YOLO)Autores:Al-Antari M.A., Al-Masni M.A., Choi M.T., Edwin Valarezo Anazco, Gi G., Han S.M., Kim T.S., Kim T.Y., Park J.M., Rivera P.Fuentes:googlescopus