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Showing 1 to 4 of 4 for “"SURF Features"”.
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A highly accessible application for detection and classification of maize foliar diseases from leaf images
… that can be trained using either SIFT or SURF features. The solution was evaluated to establish classification accuracy, page load times when accessed from different networks and its cross-browser support. The system achieved 73.3% overall accuracy rate when tested using images identical …
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Using regions of interest to track landmarks for RGBD simultaneous localisation and mapping
… time. The proposed algorithm extracts features from a region of interest (ROI) to track landmarks for RGBD SLAM. This strategy is compared to the traditional method of extracting features from an entire image. The ROI algorithm is implemented via a pre-processing algorithm, which is …
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A Machine Learning Approach for the Objective Sonographic Assessment of Patellar Tendinopathy in Collegiate Basketball Athletes
… and convolutional neural networks (CNNs), use features learned from labelled images, to predict the class of an unlabelled image. SVMs work by creating an optimal hyperplane between classes of labelled data points, and then classifies an unlabelled datapoint depending on which side of the …
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A feature-based fingerprinting scheme robust to desynchronization
… geometric attacks. Our scheme uses compressed SURF (Speeded-Up Robust Features) image features as side information in order to estimate and invert any geometric attack in a given class. We consider simple linear attacks (affine transforms), and more complex ones (homography and image warping). …