Brian Christopher Becker

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Face recognition is becoming a widely used technique to organize and tag photos. Whether searching, viewing, or organizing photos on the web or in personal photo albums , there is a growing demand to index real-world photos by the subjects in them. Even consumer platforms such as Google Picasa, Microsoft Photo Gallery, and social network sites such as(More)
Keywords: Open-universe face recognition Large-scale classification Uncontrolled datasets Sparse representations a b s t r a c t With millions of users and billions of photos, web-scale face recognition is a challenging task that demands speed, accuracy, and scalability. Most current approaches do not address and do not scale well to Internet-sized(More)
BACKGROUND Airway clearance is frequently needed by patients suffering from blunt chest wall trauma. High Frequency Chest Wall Oscillation (HFCWO) has been shown to be effective in helping to clear secretions from the lungs of patients with cystic fibrosis, bronchiectasis, asthma, primary ciliary dyskinesia, emphysema, COPD, and many others. Chest wall(More)
This paper evaluates face recognit real-world application of Facebook usually present results in terms constrained face datasets, it is difficult would work on natural data in a real We present a method to automatically face images from Facebook, resulting i representing over 500 users. From datasets, we evaluate a variety of recognition algorithms (PCA,(More)
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