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Author  |
Juan C. Basurto, Patricia Chávez and Hernán Córdova |

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Title |
A Proximity-Aware Transparent Handoff Mobility Scheme for VoIP Communication over Infrastructure Mesh Networks |
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Conference Article |
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2011 |
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International Congress of Electronic, Electrical and Systems Engineering-INTERCON 2011 |
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Wireless Mesh Networks; Quality of Service; Mobility Management; Voice over IP. |
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Mobility Management plays a key role in Voice-over- IP (VoIP) communications over Wireless Mesh Networks (WMN) as clients should maintain adequate levels of Quality of Service (QoS) as they move across the network. This paper presents PATH, a Proximity-Aware Transparent Handoff mobility scheme for real time voice communications over wireless mesh networks. Our study focuses on Medium Access Control (MAC) layer procedures and relies on gratuitous ARP unicasting in order to provide fast-handoffs. An experimental evaluation has been conducted and its results are shown in this paper. |
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cidis @ cidis @ |
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20 |
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Juca Aulestia M., Labanda Jaramillo M., Guaman Quinche J., Coronel Romero E., Chamba Eras L., & Roberto Jacome Galarza |

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Title |
Open innovation at university: a systematic literature review |
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Journal Article |
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2020 |
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Advances in Intelligent Systems and Computing |
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1159 AISC, 2020 |
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3-14 |
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cidis @ cidis @ |
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189 |
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Author  |
Julien Poujol; Cristhian A. Aguilera; Etienne Danos; Boris X. Vintimilla; Ricardo Toledo; Angel D. Sappa |

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Title |
A visible-Thermal Fusion based Monocular Visual Odometry |
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Conference Article |
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2015 |
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Iberian Robotics Conference (ROBOT 2015), International Conference on, Lisbon, Portugal, 2015 |
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417 |
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517-528 |
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Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion |
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The manuscript evaluates the performance of a monocular visual odometry approach when images from different spectra are considered, both independently and fused. The objective behind this evaluation is to analyze if classical approaches can be improved when the given images, which are from different spectra, are fused and represented in new domains. The images in these new domains should have some of the following properties: i) more robust to noisy data; ii) less sensitive to changes (e.g., lighting); iii) more rich in descriptive information, among other. In particular in the current work two different image fusion strategies are considered. Firstly, images from the visible and thermal spectrum are fused using a Discrete Wavelet Transform (DWT) approach. Secondly, a monochrome threshold strategy is considered. The obtained representations are evaluated under a visual odometry framework, highlighting their advantages and disadvantages, using different urban and semi-urban scenarios. Comparisons with both monocular-visible spectrum and monocular-infrared spectrum, are also provided showing the validity of the proposed approach. |
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cidis @ cidis @ |
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44 |
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Author  |
Leo Ramos & Angel D. Sappa |


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Title |
Multispectral Semantic Segmentation for Land Cover Classification: An Overview |
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2024 |
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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Vol. 17 |
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14295-14336 |
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19391404 |
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cidis @ cidis @ |
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250 |
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Author  |
Leo Thomas Ramos & Angel D. Sappa |

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Title |
Leveraging U-Net and selective feature extraction for land cover classification using remote sensing imagery |
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2025 |
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Scientific Reports |
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cidis @ cidis @ |
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270 |
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Author  |
Leo Thomas Ramos & Angel D. Sappa |
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Title |
Dual-branch ConvNeXt-based Network with Attentional Fusion Decoding for Land Cover Classification Using Multispectral Imagery |
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2025 |
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IEEE SoutheastCon 2025 |
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cidis @ cidis @ |
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271 |
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Author  |
Leo Thomas Ramos & Angel D. Sappa |
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Title |
Enhanced Aerial Scene Classification Through ConvNeXt Architectures and Channel Attention |
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Conference Article |
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2025 |
Publication |
10th International Congress on Information and Communication Technology |
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cidis @ cidis @ |
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272 |
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Author  |
Low S., Inkawhich N., Nina O., Sappa A. and Blasch E. |

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Title |
Multi-modal Aerial View Object Classification Challenge Results-PBVS 2022. |
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Conference Article |
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Year |
2022 |
Publication |
Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. |
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CONFERENCE |
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2022-June |
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417-425 |
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This paper details the results and main findings of the
second iteration of the Multi-modal Aerial View Object
Classification (MAVOC) challenge. This year’s MAVOC
challenge is the second iteration. The primary goal of
both MAVOC challenges is to inspire research into methods for building recognition models that utilize both synthetic aperture radar (SAR) and electro-optical (EO) input
modalities. Teams are encouraged/challenged to develop
multi-modal approaches that incorporate complementary
information from both domains. While the 2021 challenge
showed a proof of concept that both modalities could be
used together, the 2022 challenge focuses on the detailed
multi-modal models. Using the same UNIfied COincident
Optical and Radar for recognitioN (UNICORN) dataset and
competition format that was used in 2021. Specifically, the
challenge focuses on two techniques, (1) SAR classification
and (2) SAR + EO classification. The bulk of this document is dedicated to discussing the top performing methods
and describing their performance on our blind test set. Notably, all of the top ten teams outperform our baseline. For
SAR classification, the top team showed a 129% improvement over our baseline and an 8% average improvement
from the 2021 winner. The top team for SAR + EO classification shows a 165% improvement with a 32% average
improvement over 2021. |
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cidis @ cidis @ |
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177 |
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Author  |
Luis C. Herrera, Leslie del R. Lima, Nayeth I. Solorzano, Jonathan S. Paillacho & Dennys Paillacho. |

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Title |
Metrics Design of Usability and Behavior Analysis of a Human-Robot-Game Platform. |
Type |
Conference Article |
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2021 |
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The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communication in Computer and Information Science |
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1388 |
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164-178 |
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cidis @ cidis @ |
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191 |
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Author  |
Luis Chuquimarca, Boris Vintimilla & Sergio Velastin |


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Title |
Banana Ripeness Level Classification using a Simple CNN Model Trained with Real and Synthetic Datasets. |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) Lisbon, 19-21 Febrero 2023 |
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Vol. 5 |
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536 - 543 |
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21845921 |
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cidis @ cidis @ |
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202 |
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