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Carlos Monsalve; Alain April; Alain Abran |
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BPM and requirements elicitation at multiple levels of abstraction: A review |
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Conference Article |
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2011 |
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IADIS International Conference on Information Systems 2011 |
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237-242 |
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Business process modeling, levels of abstraction, requirements elicitation, requirements modeling, review |
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Business process models can be useful for requirements elicitation, among other things. Software development depends on the quality of the requirements elicitation activities, and so adequately modeling business processes (BPs) is critical. A key factor in achieving this is the active participation of all the stakeholders in the development of a shared vision of BPs.
Unfortunately, organizations often find themselves left with inconsistent BPs that do not cover all the stakeholders’ needs
and constraints. However, consolidation of the various stakeholder requirements may be facilitated through the use of multiple levels of abstraction (MLA). This article contributes to the research into MLA use in business process modeling (BPM) for software requirements by reviewing the theoretical foundations of MLA and their use in various BP-oriented approaches. |
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CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL) Km. 30.5 vía Perimetral, |
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no |
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cidis @ cidis @ |
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15 |
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Charco, J.L., Sappa, A.D., Vintimilla, B.X., Velesaca, H.O. |
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Title |
Camera pose estimation in multi-view environments:from virtual scenarios to the real world |
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Journal Article |
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2021 |
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In Image and Vision Computing Journal. (Article number 104182) |
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Vol. 110 |
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Relative camera pose estimation, Domain adaptation, Siamese architecture, Synthetic data, Multi-view environments |
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This paper presents a domain adaptation strategy to efficiently train network architectures for estimating the relative camera pose in multi-view scenarios. The network architectures are fed by a pair of simultaneously acquired
images, hence in order to improve the accuracy of the solutions, and due to the lack of large datasets with pairs of
overlapped images, a domain adaptation strategy is proposed. The domain adaptation strategy consists on transferring the knowledge learned from synthetic images to real-world scenarios. For this, the networks are firstly
trained using pairs of synthetic images, which are captured at the same time by a pair of cameras in a virtual environment; and then, the learned weights of the networks are transferred to the real-world case, where the networks are retrained with a few real images. Different virtual 3D scenarios are generated to evaluate the
relationship between the accuracy on the result and the similarity between virtual and real scenarios—similarity
on both geometry of the objects contained in the scene as well as relative pose between camera and objects in the
scene. Experimental results and comparisons are provided showing that the accuracy of all the evaluated networks for estimating the camera pose improves when the proposed domain adaptation strategy is used,
highlighting the importance on the similarity between virtual-real scenarios. |
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English |
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cidis @ cidis @ |
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147 |
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Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin |
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Title |
Classifying Healthy and Defective Fruits with a Siamese Architecture and CNN Models |
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2024 |
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Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) |
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cidis @ cidis @ |
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245 |
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Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Colorizing Infrared Images through a Triplet Condictional DCGAN Architecture |
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2017 |
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19th International Conference on Image Analysis and Processing. |
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287-297 |
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gtsi @ user @ |
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66 |
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