Proceedings ArticleDOI
A compact and efficient image retrieval approach based on border/interior pixel classification
Renato O. Stehling,Mario A. Nascimento,Alexandre X. Falcão +2 more
- pp 102-109
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TLDR
Experimental results show that the BIC approach is consistently more compact, more efficient and more effective than state-of-the-art CBIR approaches based on sophisticated image analysis algorithms and complex distance functions.Abstract:
This paper presents \bic (Border/Interior pixel Classification), a compact and efficient CBIR approach suitable for broad image domains It has three main components: (1) a simple and powerful image analysis algorithm that classifies image pixels as either border or interior, (2) a new logarithmic distance (dLog) for comparing histograms, and (3) a compact representation for the visual features extracted from images Experimental results show that the BIC approach is consistently more compact, more efficient and more effective than state-of-the-art CBIR approaches based on sophisticated image analysis algorithms and complex distance functions It was also observed that the dLog distance function has two main advantages over vectorial distances (eg, L1): (1) it is able to increase substantially the effectiveness of (several) histogram-based CBIR approaches and, at the same time, (2) it reduces by 50% the space requirement to represent a histogramread more
Citations
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Journal ArticleDOI
Towards better exploiting convolutional neural networks for remote sensing scene classification
TL;DR: An analysis of three possible strategies for exploiting the power of existing convolutional neural networks (ConvNets or CNNs) in different scenarios from the ones they were trained: full training, fine tuning, and using ConvNets as feature extractors points that fine tuning tends to be the best performing strategy.
Proceedings ArticleDOI
Do deep features generalize from everyday objects to remote sensing and aerial scenes domains
TL;DR: ConvNets trained for recognizing everyday objects for the classification of aerial and remote sensing images obtained the best results for aerial images, while for remote sensing, they performed well but were outperformed by low-level color descriptors, such as BIC.
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Supervised pattern classification based on optimum-path forest
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Proceedings ArticleDOI
A PCA-based similarity measure for multivariate time series
Kiyoung Yang,Cyrus Shahabi +1 more
TL;DR: The results show the superiority of the approaches as compared to the traditional similarity measures for MTS datasets, such as Euclidean Distance (ED), Dynamic Time Warping (DTW), Weighted Sum SVD (WSSVD) and PCA similarity factor (SPCA ) in precision/recall.
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Automatic fruit and vegetable classification from images
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