Abstract: Novel phosphorescent heteroleptic iridium complexes with phenylpyridine and dibenzo-containing ligands are provided. Alkyl substitution at specific positions on the ligands gives rise to compounds with improved OLED properties, including saturated green emission.

Abstract: A compound is disclosed that has a metal coordination complex structure having at least two ligands coordinated to the metal; wherein the compound has a first substituent R1 at one of the ligands' periphery; wherein a first distance is defined as the distance between the metal and one of the atoms in R1 where that atom is the farthest away from the metal among the atoms in R1; wherein the first distance is also longer than any other atom-to-metal distance between the metal and any other atoms in the compound; and wherein when a sphere having a radius r is defined whose center is at the metal and the radius r is the smallest radius that will allow the sphere to enclose all atoms in the compound that are not part of R1, the first distance is longer than the radius r by at least 2.9 ?.

Abstract: Facial image bucketing is disclosed, whereby a query for facial image recognition compares the facial image against existing candidate images. Rather than comparing the facial image to each candidate image, the candidate images are organized or clustered into buckets according to their facial similarities, and the facial image is then compared to the image(s) in most-likely one(s) of the buckets. The organizing uses particular selected facial features, computes distance between the facial features, and selects ones of the computed distances to determine which facial images should be organized into the same bucket.

Abstract: Facial image bucketing is disclosed, whereby a query for facial image recognition compares the facial image against existing candidate images. Rather than comparing the facial image to each candidate image, the candidate images are organized or clustered into buckets according to their facial similarities, and the facial image is then compared to the image(s) in most-likely one(s) of the buckets. The organizing uses particular selected facial features, computes distance between the facial features, and selects ones of the computed distances to determine which facial images should be organized into the same bucket.

Abstract: Facial image bucketing is disclosed, whereby a query for facial image recognition compares the facial image against existing candidate images. Rather than comparing the facial image to each candidate image, the candidate images are organized or clustered into buckets according to their facial similarities, and the facial image is then compared to the image(s) in most-likely one(s) of the buckets. The organizing uses particular selected facial features, computes distance between the facial features, and selects ones of the computed distances to determine which facial images should be organized into the same bucket.

Abstract: Generating weights for biometric tokens in probabilistic matching systems is disclosed, where these weights are generated from computations performed on matched sets and unmatched sets of a reference data set. In an embodiment, scores from a similarity scoring function are distributed among bins, and a weight is computed for each bin as the log of (the matched set ratio/the unmatched set ratio), where the ratios are computed as the number of scores in a particular bin as compared to the total size of the set. The weights may then be used subsequently with scores computed by the scoring function to assess confidence of a computed similarity score, and are directed toward making the output of the probabilistic matching system more data-driven and more accurate.

Abstract: Generating weights for biometric tokens in probabilistic matching systems is disclosed, where these weights are generated from computations performed on matched sets and unmatched sets of a reference data set. In an embodiment, scores from a similarity scoring function are distributed among bins, and a weight is computed for each bin as the log of (the matched set ratio/the unmatched set ratio), where the ratios are computed as the number of scores in a particular bin as compared to the total size of the set. The weights may then be used subsequently with scores computed by the scoring function to assess confidence of a computed similarity score, and are directed toward making the output of the probabilistic matching system more data-driven and more accurate.

Abstract: Facial image bucketing is disclosed, whereby a query for facial image recognition compares the facial image against existing candidate images. Rather than comparing the facial image to each candidate image, the candidate images are organized or clustered into buckets according to their facial similarities, and the facial image is then compared to the image(s) in most-likely one(s) of the buckets. The organizing uses particular selected facial features, computes distance between the facial features, and selects ones of the computed distances to determine which facial images should be organized into the same bucket.

Abstract: Generating weights for biometric tokens in probabilistic matching systems is disclosed, where these weights are generated from computations performed on matched sets and unmatched sets of a reference data set. In an embodiment, scores from a similarity scoring function are distributed among bins, and a weight is computed for each bin as the log of (the matched set ratio/the unmatched set ratio), where the ratios are computed as the number of scores in a particular bin as compared to the total size of the set. The weights may then be used subsequently with scores computed by the scoring function to assess confidence of a computed similarity score, and are directed toward making the output of the probabilistic matching system more data-driven and more accurate.