Some Birds of Prey from the Upper Pliocene of Kansas
Some birds of prey from the Upper Pliocene of Kansas.---Although many arian fossils from the local faunas of the Rexroad formation (Upper Pliocene), Meade County, Kansas, have now been reported, several species of birds of prey remain. These fossils, which Dr. C. W. Hibbard of The University of Michigan Museum of Paleontology a.nd his field parties collected, come from the Rexroad and Fox Canyon local faunas of the Rexroad formation. These two localities arc described by Hibbard (1950). The two local faunas have been treated as one in the past, but Hibbard's (1967) latest view is that they arc distinct. The Fox Canyon local fauna is now considered to be older than the Rexroad and is distinct on the basis of its small mammals (Hibbard, 1967). Birds have bccn reported previously from these local faunas by Wetmore (1944), Tordoff (1951, 1959), Brodkorb (1964, 1967), Collins (1964), Ford (1966), Murray (1967), a.nd Fcduccia (1967, 1968). The birds of prey represented arc as follows: Accipiter sp.---Two distal ends of tibiotarsi represent an accipitcr approximately the size of the Recent A. cooperi, but the clements arc not sufficiently diagnostic to warrant the naming of a new species or the definite assignment of the fossils to the Recent form. One bone, a 42-mm piece of the distal end of a left tibiotarsus (UMMP No. V57506, from the Rexroad local fau.na, loc. no. 3) measures 10.8 mm in width through condyles. The same measurement for eight specimens of Recent A. cooperi females gives a mcan of 10.1 mm, with a range of 9.2-10.9 mm. The smaller fossil, a 17.1-mm piece of the distal end of a left tibiotarsus (UMMP No. V45422, from the Rexroad local fauna, loc. UM-K3-53) measures 9.0 mm in width through condyles. The same measurement for five males of Recent A. cooperi gives a mean of 8.5 mm, with a range of 8.3-8.8 mm. Whether or not both fossils represent females or one a female and the other a male cannot bc dctcrmi.ned, but it is probably best to assume that only one species is represented. Buteo sp.--A fragment of a right coracold (UMMP No. V24767, from the Fox Canyon local fauna, loc. UM-K1-47) represents a large species of Buteo close in size and morphology to B. jamaicensis, but it is too fragmentary to permit allocation. No useful measurements could be taken.
Grebes from the Late Pliocene of North America
The Pliocene grebe fauna of North America is not well known. Brodkorb (1963a) lists two extinct species, Pliodytes lanquisti Brodkorb from the Lower Pliocene of Florida and Podiceps subparvus (L. Miller and Bowman) from the Middle Pliocene of California, and one extant species, Podiceps caspicus (= nigricollis) from the Middle Pliocene of Kansas. In addition, there are unnamed grebe remains from the Pliocene of Arizona (Wetmore, 1924), California (Miller and Bowman, 1958; Howard, 1963), Idaho (Wetmore, 1933; Brodkorb, 1958), and Kansas (Wetmore, 1944). Thus I am fortunate to have the opportunity to study and to report on the many grebe specimens that have been collected in Pliocene deposits in Kansas and Idaho by Claude W. Hibbard and his assistants. These specimens are in the collections of The University of Michigan Museum of Paleontology (UMMP). The nomenclature of the grebes has changed considerably since the publication of Peters' Check-list (1931), and so I have used the names applied by Storer (1963).
Integrating Local CNN and Global CNN for Script Identification in Natural Scene Images
Script identification in natural scene images is a key pre-step for text recognition and is also an indispensable condition for automatic text understanding systems that are designed for multi-language environments. In this paper, we present a novel framework integrating Local CNN and Global CNN both of which are based on ResNet-20 for script identification. We first obtain a lot of patches and segmented images based on the aspect ratios of the images. Subsequently, these patches and segmented images are used as inputs to Local CNN and Global CNN for training, respectively. Finally, to get the final results, the Adaboost algorithm is used to combine the results of Local CNN and Global CNN for decision-level fusion. Benefiting from such a strategy, Local CNN fully exploits the local features of the image, effectively revealing subtle differences among the scripts that are difficult to distinguish such as English, Greek, and Russian. Moreover, Global CNN mines the global features of the image to improve the accuracy of script identification. The experimental results demonstrate that our approach has a good performance on four public datasets.