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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Economically sustainable growth of small-scale perovskite manufacturing in alternative PV markets
摘要： This paper proposes a new computational method for retrieving shapes under unpredictable conditions such as when occlusion, geometric distortion, and differences in image resolution occur simultaneously. The human visual system retrieves shapes from incomplete information in the real world, and it has inspired a lot of computational methods of retrieving shapes. In order to retrieve shapes, the observed shapes are decided to be alike or unlike remembered shapes in memory after the comparison of these shapes. To compare the observed and remembered shapes, they must first be appropriately represented so that the points on each shape can be mapped and compared. For this reason, the shape retrieval process needs an appropriate shape representation and shape mapping methods. Moreover, the shape representations should be normalized before the mapping process. However, a normalization process for representations under unpredictable conditions has not yet been established. In this paper, we describe a shape retrieval method that enables us to retrieve shapes under unpredictable conditions with a suitable normalization process. Using curvature partition and angle-length profile, our shape retrieval method normalizes the shape representation before it does the mapping. As a result, unlike the previously proposed methods, it can be used under unpredictable conditions such as when occlusion, geometric distortion, and differences in image resolution occur simultaneously.
关键词： occlusion,Shape recognition,shape retrieval,curvature partition,geometric parameter
更新于2025-09-23 15:19:57
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A Quantification Procedure for Interior Performance of Architectural Openings Associated with Dye-Sensitized Solar Cells
摘要： Windows with various colors are important design elements used widely ranging from traditional architecture to contemporary buildings to express the architectural fa?ade, the interior atmosphere, and so on. Recently, there is a possibility that solar cells can be used to replace windows with various colors. In particular, attempts to manufacture windows using Dye-Sensitized Solar Cells (DSSCs) are actively underway. Accordingly, there is a need to determine physical and environmental performances of DSSCs. This study attempted a methodological approach to evaluate indoor environmental performance of windows and DSSCs. The concept of color gamut overage normally used in the field of displays was utilized to evaluate color expressions. In addition, a standard visual inspection table suggested by the International Ophthalmological Society was used to evaluate the recognition of shapes. This study compared performances between RGB color windows and DSSCs using the two above previous concepts. Measurement data showed that most DSSCs performed poorly in comparison with architectural color windows. However, some DSSCs showed good enough performances that could be used as alternatives of architectural color windows. Green DSSCs with VLT 18% had a color gamut similar to clear glasses. Blue DSSCs with VLT 18% were found to have similar or better shape recognition than current architectural color windows. Based on these results, limitations of DSSCs as alternatives of architectural color windows and their future development directions are suggested.
关键词： indoor environment,shape recognition,color gamut overage,color environment,dye-sensitized solar cells,architectural window
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Designing of CZTSSe Based SnS Thin Film Solar Cell for Improved Conversion Efficiency: A Simulation Study with SCAPS
摘要： This paper proposes a new computational method for retrieving shapes under unpredictable conditions such as when occlusion, geometric distortion, and differences in image resolution occur simultaneously. The human visual system retrieves shapes from incomplete information in the real world, and it has inspired a lot of computational methods of retrieving shapes. In order to retrieve shapes, the observed shapes are decided to be alike or unlike remembered shapes in memory after the comparison of these shapes. To compare the observed and remembered shapes, they must first be appropriately represented so that the points on each shape can be mapped and compared. For this reason, the shape retrieval process needs an appropriate shape representation and shape mapping methods. Moreover, the shape representations should be normalized before the mapping process. However, a normalization process for representations under unpredictable conditions has not yet been established. In this paper, we describe a shape retrieval method that enables us to retrieve shapes under unpredictable conditions with a suitable normalization process. Using curvature partition and angle-length profile, our shape retrieval method normalizes the shape representation before it does the mapping. As a result, unlike the previously proposed methods, it can be used under unpredictable conditions such as when occlusion, geometric distortion, and differences in image resolution occur simultaneously.
关键词： curvature partition,Shape recognition,geometric parameter,occlusion,shape retrieval
更新于2025-09-19 17:13:59