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Titlebook: Computer Analysis of Images and Patterns; 19th International C Nicolas Tsapatsoulis,Andreas Panayides,Mario Vento Conference proceedings 20

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https://doi.org/10.1007/978-1-4613-3560-3vel data set that resembles the watermeter digits with a focus on their deformations by bubbles. We report on promising experimental recognition results, based on a deep and recurrent network architecture performed on our data set.
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Measurement and Measurement Uncertainty,performance of . for more than 120,000 query images on about 6.9 million database images of the OpenImages data set. The results show that our approach achieves high-quality retrieval results and low search latencies.
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Systems Analysis for Water Technologyce the change map for the pair of images. Experiments were carried out using two remotely sensed image datasets. The weakly supervised method proposed in this paper offers better results in comparison to both weakly supervised- and unsupervised-based state-of-the-art models and techniques.
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Jennifer L. Beverly,David L. Martelley the information of the contours and the flat regions of the original color image, plus the relations between them. Using both the . and .-trees, this new topological representation prevents some classical drawbacks that appear when working with a single tree. An implementation in OCTAVE/MATLAB validates the correctness of our algorithm.
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: Semantic Image Similarity Search by Deep Hashing with Elasticsearchperformance of . for more than 120,000 query images on about 6.9 million database images of the OpenImages data set. The results show that our approach achieves high-quality retrieval results and low search latencies.
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John Sessions,Pamela Overhulserreal world cases, like the one we deal in the current paper, remain impractical. In the framework of the current work, we also examine and discuss, in a critical way, the effectiveness of transfer learning for real face verification cases through specific examples.
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