We propose a contextual framework for 2D image matching and registration using an ensemble feature. Our system is beneficial for registering image pairs ...
Jan 15, 2024 · In this work, we present a more intuitive approach to build and compare image similarity models based on labelled data in the form of A:R vs B:R.
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Aug 24, 2024 · In this work, we present a more intuitive approach to build and compare image similarity models based on labelled data in the form of A:R vs B:R.
Sep 10, 2024 · In this work, we present a more intuitive approach to build and compare image similarity models based on labelled data in the form of A:R vs B:R.
Jul 14, 2024 · Deep ensemble learning models combine the benefits of both deep learning models and ensemble learning, resulting in improved generalization ...
Our method incorporates contextual features derived from replies and uses a multi-view ensemble learning method specifically tailored to the problem on hand. A ...
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The overarching goals in image-based localization are scale, robustness, and speed. In recent years, approaches based on local features and sparse 3D point ...
The proposed CENet is trained in terms of end-to-end segmentation to match the resolution of input image, and allows us to fully explore contextual features ...
– Local invariant features are a powerful tool for finding correspondences between images since they are robust to cluttered background, occlusion and viewpoint ...
In this paper, we propose an approach based on ensemble learning to classify histology tissues stained with hematoxylin and eosin.