Detection with confidence measures
Multiple prediction combination and confidence measures for marine object detection
... cascade confidence measure is proposed, equivalent to the boosting ‘margin’; it uses information about how well the cascade features match the image region being ...face detection show that this ...
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Multiple prediction combination and confidence measures for marine object detection
... object detection, where a detector must pass over thousands of negative image regions for each true ...object detection algorithms and count the true positives and false positives for that threshold, but ...
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Multiple prediction combination and confidence measures for marine object detection
... Portions of this chapter were previously presented at the 19 th Australian Joint Confer- ence on Artificial Intelligence (Horton et al., 2006). Virtual attribute subsetting is a meta-classification technique which will ...
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Multiple prediction combination and confidence measures for marine object detection
... object detection method will be effective on a variety of ...object detection algorithms in this thesis. For the first (face detection) an existing cascade was used, so the only dataset required was ...
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Multiple prediction combination and confidence measures for marine object detection
... Increasing the random angle range makes the positive samples more varied, so the corresponding increase in features and feature area as the angle range increases is not surprising. A property that was not anticipated is ...
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Multiple prediction combination and confidence measures for marine object detection
... a confidence measurement from the features, and the cascade could combine the stage confidences to return an overall confidence ...The confidence measurement also amounts to measuring the margin of a ...
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Multiple prediction combination and confidence measures for marine object detection
... Haar Classifier Cascades were developed for face detection (Viola & Jones, 2001b) and have otherwise been applied to finding similar mostly-rigid objects. Seahorses are much more flexible. Even annotating whole ...
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Multiple prediction combination and confidence measures for marine object detection
... object detection, it would be useful to find some aspect of the images or the cascades trained on them which could predict the best angle range to use – however, investigating this would involve experiments with ...
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Multiple prediction combination and confidence measures for marine object detection
... K¨olsch, M., & Turk, M. 2004b. Robust hand detection. Proc. 6th IEEE International Conference on Automatic Face and Gesture Recognition, 614–619. Kruppa, H., Santana, M.C., & Schiele, B. 2003. Fast and robust face ...
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Multiple prediction combination and confidence measures for marine object detection
... tection using the confidence-based methods described in chapter 6. As in section 5.4, graphs are shown in pairs, with the first showing the angle range increasing from 0 ◦ to the approximately best range, and the ...
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Multiple prediction combination and confidence measures for marine object detection
... K¨ olsch, M., & Turk, M. 2004b. Robust hand detection. Proc. 6th IEEE International Conference on Automatic Face and Gesture Recognition, 614–619. Kruppa, H., Santana, M.C., & Schiele, B. 2003. Fast and robust ...
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Towards Confidence Measures on Fundamental Frequency Estimations
... 4.2. Classifier training and global performance As the F0 detection algorithms works quite well on clean data, the amount of incorrect estimated values (i.e., negative exam- ples) on clean data is too small for a ...
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Confidence Measures for Error Discrimination in an Interactive Predictive Parsing Framework
... error detection capabilities during the IPP process: in the h0v1 PCFG they are able to dis- cern about 25% of incorrect constituents at most stages of the IPP process, with a slight bump up to 27% after about 7 ...
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Measures of metacognition on signal-detection theoretic models
... a confidence rating on a multi-point ...′ measures can be obtained: as with type I d ′ analyses, multiple measurements of each hit and false alarm rate would be obtained by using multiple thresholds for ...
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Evaluating measures of optimism and sport confidence
... Table 1. Fit Statistics for the LOT-R, Sport Confidence Inventory, and Carolina Sport Confidence Inventory Measurement Models Note. ** p < .01, *** p < .001 df = degrees of freedom; CFI = comparative fit ...
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Statistical Confidence Measures for Probabilistic Parsing
... a confidence measure refers to its ability to detect erroneous ...the Confidence Error Rate (CER) and the Receiver Operating Characteristic (ROC) curve with its corresponding integrated area (IROC) [19, ...
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Confidence measures for deep learning in domain adaptation
... proposed confidence measures proved to be related to the performance of a classifier and, in addition, they did not require the labels of the target dataset to be ...proposed confidence ...
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CONFIDENCE BUILDING MEASURES AND INTERNATIONAL CYBER SECURITY
... transparency measures, emphasis was also placed on the role private sector actors could play in supporting and developing cooperative ...cooperative measures in which companies play an important ...
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Exploiting confidence measures for missing data speech recognition
... Exploiting confidence measures for missing data speech recognition Christophe Cerisara LORIA UMR 7503 - France Automatic speech recognition in highly non-stationary noise, for instance with a competing ...
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Confidence Levels for CVaR Risk Measures and Minimax Limits*
... the confidence level of CVaR is set close to 1, the CVaR risk measure approximates the extreme (worst scenario) risk ...risk measures and its impact on optimal decision making when we wish to minimize the ...
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