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Multiple instance learning: A survey of problem characteristics and applications
Multiple instance learning (MIL) is a form of weakly supervised learning where training
instances are arranged in sets, called bags, and a label is provided for the entire bag. This …
instances are arranged in sets, called bags, and a label is provided for the entire bag. This …
Co-saliency detection via a self-paced multiple-instance learning framework
As an interesting and emerging topic, co-saliency detection aims at simultaneously
extracting common salient objects from a group of images. On one hand, traditional co …
extracting common salient objects from a group of images. On one hand, traditional co …
Deep multi-patch aggregation network for image style, aesthetics, and quality estimation
This paper investigates problems of image style, aesthetics, and quality estimation, which
require fine-grained details from high-resolution images, utilizing deep neural network …
require fine-grained details from high-resolution images, utilizing deep neural network …
Prototype selection for nearest neighbor classification: Taxonomy and empirical study
The nearest neighbor classifier is one of the most used and well-known techniques for
performing recognition tasks. It has also demonstrated itself to be one of the most useful …
performing recognition tasks. It has also demonstrated itself to be one of the most useful …
Log-based predictive maintenance
Success of manufacturing companies largely depends on reliability of their products.
Scheduled maintenance is widely used to ensure that equipment is operating correctly so as …
Scheduled maintenance is widely used to ensure that equipment is operating correctly so as …
Multiple instance learning for classification of dementia in brain MRI
Abstract Machine learning techniques have been widely used to detect morphological
abnormalities from structural brain magnetic resonance imaging data and to support the …
abnormalities from structural brain magnetic resonance imaging data and to support the …
A novel multiple-instance learning-based approach to computer-aided detection of tuberculosis on chest X-rays
To reach performance levels comparable to human experts, computer-aided detection
(CAD) systems are typically optimized following a supervised learning approach that relies …
(CAD) systems are typically optimized following a supervised learning approach that relies …