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| Author | Silva Steven, Paillacho Dennys, Verdezoto Nervo, Hernandez Juan David | ||||
| Title | TOWARDS ONLINE SOCIALLY ACCEPTABLE ROBOT NAVIGATION | Type | Conference Article | ||
| Year | 2022 | Publication | IEEE INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING, | Abbreviated Journal | |
| Volume | 2022-August | Issue | Pages | 707-714 | |
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| Call Number | cidis @ cidis @ | Serial | 199 | ||
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| Author | Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. | ||||
| Title | LDC: Lightweight Dense CNN for Edge Detection. | Type | Journal Article | ||
| Year | 2022 | Publication | IEEE Access journal | Abbreviated Journal | |
| Volume | Vol. 10 | Issue | Pages | pp. 68281-68290 | |
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| Call Number | cidis @ cidis @ | Serial | 183 | ||
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| Author | Pereira J., Mora M. & W. Agila | ||||
| Title | Qualitative Model to Maximize Shrimp Growth at Low Cost | Type | Journal Article | ||
| Year | 2021 | Publication | 5th Ecuador Technical Chapters Meeting (ETCM 2021), Octubre 12 – 15 | Abbreviated Journal | |
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| Call Number | cidis @ cidis @ | Serial | 167 | ||
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| Author | Patricia L. Suarez, Dario Carpio, Angel D. Sappa and Henry O. Velesaca | ||||
| Title | Transformer based Image Dehazing. | Type | Conference Article | ||
| Year | 2022 | Publication | 16TH International Conference On Signal Image Technology & Internet Based Systems SITIS 2022. | Abbreviated Journal | |
| Volume | Issue | Pages | 148-154 | ||
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| Call Number | cidis @ cidis @ | Serial | 195 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title | Vegetation Index Estimation from Monospectral Images | Type | Conference Article | ||
| Year | 2018 | Publication | 15th International Conference, Image Analysis and Recognition (ICIAR 2018), Póvoa de Varzim, Portugal. Lecture Notes in Computer Science | Abbreviated Journal | |
| Volume | 10882 | Issue | Pages | 353-362 | |
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| Abstract | This paper proposes a novel approach to estimate Normalized Difference Vegetation Index (NDVI) from just the red channel of a RGB image. The NDVI index is defined as the ratio of the difference of the red and infrared radiances over their sum. In other words, information from the red channel of a RGB image and the corresponding infrared spectral band are required for its computation. In the current work the NDVI index is estimated just from the red channel by training a Conditional Generative Adversarial Network (CGAN). The architecture proposed for the generative network consists of a single level structure, which combines at the final layer results from convolutional operations together with the given red channel with Gaussian noise to enhance details, resulting in a sharp NDVI image. Then, the discriminative model estimates the probability that the NDVI generated index came from the training dataset, rather than the index automatically generated. Experimental results with a large set of real images are provided showing that a Conditional GAN single level model represents an acceptable approach to estimate NDVI index. |
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| Call Number | gtsi @ user @ | Serial | 82 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title | Adaptive Harris Corners Detector Evaluated with Cross-Spectral Images | Type | Conference Article | ||
| Year | 2018 | Publication | International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing | Abbreviated Journal | |
| Volume | 721 | Issue | Pages | ||
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| Abstract | This paper proposes a novel approach to use cross-spectral images to achieve a better performance with the proposed Adaptive Harris corner detector comparing its obtained results with those achieved with images of the visible spectra. The images of urban, field, old-building and country category were used for the experiments, given the variety of the textures present in these images, with which the complexity of the proposal is much more challenging for its verification. It is a new scope, which means improving the detection of characteristic points using crossspectral images (NIR, G, B) and applying pruning techniques, the combination of channels for this fusion is the one that generates the largest variance based on the intensity of the merged pixels, therefore, it is that which maximizes the entropy in the resulting Cross-spectral images. Harris is one of the most widely used corner detection algorithm, so any improvement in its efficiency is an important contribution in the field of computer vision. The experiments conclude that the inclusion of a (NIR) channel in the image as a result of the combination of the spectra, greatly improves the corner detection due to better entropy of the resulting image after the fusion, Therefore the fusion process applied to the images improves the results obtained in subsequent processes such as identification of objects or patterns, classification and/or segmentation. |
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| Notes | 1 | Approved | no | ||
| Call Number | gtsi @ user @ | Serial | 84 | ||
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| Author | Tommy David Beltran Borbor, Raul Josue Villao Rodriguez, Luis Enrique Chuquimarca Jiménez, Boris Xavier Vintimilla Burgos & Sergio Alejandro Velastin | ||||
| Title | Fruit Deformity Classification through Single-Input and Multi-Input Architectures based on CNN Models using Real and Synthetic Images | Type | Conference Article | ||
| Year | 2025 | Publication | Lecture Notes in Computer Science: 27th The Iberomican Congress on Pattern Recognition CIARP 2024 Talca 26 – 29 November 2024 | Abbreviated Journal | |
| Volume | Vol. 15368 LNCS | Issue | Pages | 46-62 | |
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| ISSN | 03029743 | ISBN | 978-303176606-0 | Medium | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 251 | ||
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| Author | Carlos Monsalve; Alain April and Alain Abran | ||||
| Title | Measuring software functional size from business process models | Type | Journal Article | ||
| Year | 2011 | Publication | International Journal of Software Engineering and Knowledge Engineering | Abbreviated Journal | |
| Volume | Vol. 21 | Issue | Pages | pp. 311–338 | |
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| Abstract | ISO 14143-1 specifies that a functional size measurement (FSM) method must provide measurement procedures to quantify the functional user requirements (FURs) of software. Such quantitative information, functional size, is typically used, for instance, in software estimation. One of the international standards for FSM is the COSMIC FSM method — ISO 19761 — which was designed to be applied both to the business application (BA) software domain and to the real-time software domain. A recurrent problem in FSM is the availability and quality of the inputs required for measurement purposes; that is, well documented FURs. Business process (BP) models, as they are commonly used to gather requirements from the early stages of a project, could be a valuable source of information for FSM. In a previous article, the feasibility of such an approach for the BA domain was analyzed using the Qualigram BP modeling notation. This paper complements that work by: (1) analyzing the use of BPMN for FSM in the BA domain; (2) presenting notation-independent guidelines for the BA domain; and (3) analyzing the possibility of using BP models to perform FSM in the real-time domain. The measurement results obtained from BP models are compared with those of previous FSM case studies. | ||||
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| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 19 | ||
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| Author | Mónica Villavicencio; Alain Abran | ||||
| Title | Facts and Perceptions Regarding Software Measurement in Education and in Practice: Preliminary Results | Type | Journal Article | ||
| Year | 2011 | Publication | Journal of Software Engineering and Application | Abbreviated Journal | |
| Volume | Issue | Pages | pp. 227-234 | ||
| Keywords | Software measurement, education, software engineering | ||||
| Abstract | How is software measurement addressed in undergraduate and graduate programs in universities? Do organizations consider that the graduating students they hire have an adequate knowledge of software measurement? To answer these and related questions, a survey was administered to participants who attended the IWSM-MENSURA 2010 conference in Stuttgart, Germany. Forty-seven of the 69 conference participants (including software development practitioners, software measurement consultants, university professors, and graduate students) took part in the survey. The results indicate that software measurement topics are: A) covered mostly at the graduate level and not at the undergraduate level, and B) not mandatory. Graduate students and professors consider that, of the measurement topics covered in university curricula, specific topics, such as measures for the requirements phase, and measurement techniques and tools, receive more attention in the academic context. A common observation of the practitioners who participated in the survey was that students hired as new employees bring limited software measurement-related knowledge to their organizations. Discussion of the findings and directions for future research are presented. | ||||
| Address | 2 CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil, Ecuador | ||||
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| Call Number | cidis @ cidis @ | Serial | 17 | ||
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| Author | Miguel Oliveira; Vítor Santos; Angel D. Sappa; Paulo Dias; A. Paulo Moreira | ||||
| Title | Incremental Texture Mapping for Autonomous Driving | Type | Journal Article | ||
| Year | 2016 | Publication | Robotics and Autonomous Systems Journal | Abbreviated Journal | |
| Volume | Vol. 84 | Issue | Pages | pp. 113-128 | |
| Keywords | Scene reconstruction, Autonomous driving, Texture mapping | ||||
| Abstract | Autonomous vehicles have a large number of on-board sensors, not only for providing coverage all around the vehicle, but also to ensure multi-modality in the observation of the scene. Because of this, it is not trivial to come up with a single, unique representation that feeds from the data given by all these sensors. We propose an algorithm which is capable of mapping texture collected from vision based sensors onto a geometric description of the scenario constructed from data provided by 3D sensors. The algorithm uses a constrained Delaunay triangulation to produce a mesh which is updated using a specially devised sequence of operations. These enforce a partial configuration of the mesh that avoids bad quality textures and ensures that there are no gaps in the texture. Results show that this algorithm is capable of producing fine quality textures. | ||||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 50 | ||
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