This is followed by calculating inter-class similarity matrices for distillation using KL divergence between distributions of each pair of classes. To further improve the effectiveness of the proposed method, an Adaptive Loss Weighting (ALW) training strategy is proposed. Unlike existing methods, the ...
Chen, D.Y., Tian, X.P., Shen, Y.T., Ouhyoung, M.: On visual similarity based 3D model retrieval. Eurographics. Computer Graphics Forum, 223–232 (2003) Google Scholar Gu, X., Gortler, S., Hoppe, H.: Geometry Images. In: Proc. SIGGRAPH, pp. 355–361 (July 2002) Google Sc...
We find that the fusion of these two penalty signals will lead to a good trade-off between the intra-class similarity and inter-class separability, thereby greatly improving the generalization ability of learned features. We also investigate various network architectures for FVR application in terms ...
CosSIF: Cosine similarity-based image filtering to overcome low inter-class variation in synthetic medical image datasets - mominul-ssv/cossif
The novelty of this paper lies in two parts. In the first part, we develop the CosSIF algorithm, designed to compute and record the cosine similarity and cosine distance for each image in a target class with all other images in one or more secondary classes. The record generated by the ...
The similarity to a query is given by the mean of the similarity to a query according to each index. This simple fusion was more effective than other fusion methods we have tested =-=[25]-=-. C. Mixed Retrieval The last module of our retrieval system concerns the fusion between text ...
Firstly, the algorithm introduces the spatial information of hyperspectral images into the classification task through the superpixel definition based on the entropy rate, which not only reduces the spatial redundancy information of hyperspectral images but also uses the similarity of ...
It was apparent that the migration of the transitional area could be characterized and showed similarity to a simple hypothesized model of land cover change. The comparison of fuzzy classifications was able to provide a richer information base on class membership and its dynamics than that obtainable...
However, IVUS plaque segmentation encounters two major challenges: (1) the variability in plaque shapes makes it difficult to locate plaques accurately, and (2) distinguishing plaque types is challenging due to the similarity in visual features among different types. To tackle these challenges, we ...
Relevance Feedback attempts to reduce the semantic gap between a user's perception of similarity and a feature-based representation of an image by asking the user to provide feedback regarding the relevance or non-relevance of the retrieved images. This is intra-query learning. However, in most...