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Author |
Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa |
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Title |
Fine-tuning based deep covolutional networks for lepidopterous genus recognition |
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2016 |
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XXI IberoAmerican Congress on Pattern Recognition |
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1-9 |
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This paper describes an image classi cation approach ori- ented to identify specimens of lepidopterous insects recognized at Ecuado- rian ecological reserves. This work seeks to contribute to studies in the area of biology about genus of butter ies and also to facilitate the reg- istration of unrecognized specimens. The proposed approach is based on the ne-tuning of three widely used pre-trained Convolutional Neural Networks (CNNs). This strategy is intended to overcome the reduced number of labeled images. Experimental results with a dataset labeled by expert biologists, is presented|a recognition accuracy above 92% is reached. 1 Introductio |
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cidis @ cidis @ |
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53 |
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Author |
Angely Oyola; Dennis G. Romero; Boris X. Vintimilla |
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Title |
A Dijkstra-based algorithm for selecting the Shortest-Safe Evacuation Routes in dynamic environments (SSER) |
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2017 |
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The 30th International Conference on Industrial, Engineering, Other Applications of Applied Intelligent Systems (IEA/AIE 2017) |
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131-135 |
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cidis @ cidis @ |
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55 |
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Author |
Sianna Puente; Cindy Madrid; Miguel Realpe; Boris X. Vintimilla |
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Title |
An Empirical Comparison of DCNN libraries to implement the Vision Module of a Danger Management System |
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2017 |
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2017 International Conference on Deep Learning Technologies (ICDLT 2017) |
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Part F128535 |
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60-65 |
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cidis @ cidis @ |
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56 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Cross-spectral Image Patch Similarity using Convolutional Neural Network |
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2017 |
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2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM) |
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1-5 |
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Call Number |
cidis @ cidis @ |
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57 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Learning to Colorize Infrared Images |
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Conference Article |
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2017 |
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15th International Conference on Practical Applications of Agents and Multi-Agent Systems |
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cidis @ cidis @ |
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58 |
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Author |
Cristhian A. Aguilera; Xaver Soria; Angel D. Sappa; Ricardo Toledo |
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Title |
RGBN Multispectral Images: a Novel Color Restoration Approach |
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Conference Article |
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2017 |
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15th International Conference on Practical Applications of Agents and Multi-Agent Systems |
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619 |
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155-163 |
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no |
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cidis @ cidis @ |
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59 |
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Author |
Angel J. Valencia; Roger M. Idrovo; Angel D. Sappa; Douglas Plaza G.; Daniel Ochoa |
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Title |
A 3D Vision Based Approach for Optimal Grasp of Vacuum Grippers |
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Conference Article |
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2017 |
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2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM) |
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1-6 |
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Call Number |
cidis @ cidis @ |
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60 |
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Author |
Dennis G. Romero; Roberto Yoncon; Angel Guale; Bonny Bayot; Fanny Panchana |
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Title |
Evaluación de técnicas de clasificación orientadas a la identificación automática de órganos del camarón a partir de imágenes histológicas |
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Conference Article |
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2017 |
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15th LACCEI International Multi-Conference for Engineering, Education, and Technology |
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2017-July |
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1-6 |
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Call Number |
cidis @ cidis @ |
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61 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Infrared Image Colorization based on a Triplet DCGAN Architecture. |
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Conference Article |
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2017 |
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13th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2017. (This paper has been selected as “Best Paper Award” ) |
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2017-July |
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212-217 |
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cidis @ cidis @ |
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62 |
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Author |
Jorge L. Charco; Boris X. Vintimilla; Angel D. Sappa |
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Title |
Deep learning based camera pose estimation in multi-view environment. |
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Conference Article |
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2018 |
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14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) |
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224-228 |
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This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and rotation as output. The proposed approach is trained from scratch on a large data set that takes as input a pair of images from the same scene. This new architecture is compared with a previous approach using standard metrics, obtaining better results on the relative camera pose. |
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gtsi @ user @ |
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93 |
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