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This paper presents a new face detection method. We train a model that predicts the Jaccard distance between a sample sub-window and the ground truth face location. This model produces continuous outputs as opposite to the binary output produced by the wid ...
Many classes of objects can now be successfully detected with statistical machine learning techniques. Faces, cars and pedestrians, have all been detected with low error rates by learning their appearance in a highly generic manner from extensive training ...
When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. More ...
Automatic analysis of spoken conversations has recently searched for phenomena like agreement/disagreement in collaborative and non- conflictual discussions (e.g., meetings). This work adds a novel dimension investigating conflicts in spontaneous conversat ...
Efficient, real-time and unsupervised data analysis is one of the key elements for achieving scientific success in complex engineering and physical systems, of which three examples are the currently operating Joint European Torus (JET) and the soon-to-be-b ...
This work shows how to develop distributed versions of block blind estimation techniques that have been proposed before for batch processing. Using diffusion adaptation techniques, data are accumulated at the nodes to form estimates of the auto-correlation ...
Domain adaptation of a language model aims at re-estimating word sequence probabilities in order to better match the peculiarities of a given broad topic of interest. To achieve this task, a common strategy consists in retrieving adaptation texts from the ...
Domain adaptation of a language model aims at re-estimating word sequence probabilities in order to better match the peculiarities of a given broad topic of interest. To achieve this task, a common strategy consists in retrieving adaptation texts from the ...
Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervise ...
Monitoring traffic events in computer network has become a critical task for operators to maintain an accurate view of a network's condition, to detect emerging security threats, and to safeguard the availability of resources. Conditions detrimental to a n ...