Sparse Coding on Stereo Video for Object Detection

Deep Convolutional Neural Networks (DCNN) require millions of labeled training examples for image classification and object detection tasks, which restrict these models to domains where such datasets are available. In this paper, we explore the use of unsupervised sparse coding applied to stereo-video data to help alleviate the need for large amounts of labeled data. We show that replacing a typical supervised convolutional layer with an unsupervised sparse-coding layer within a DCNN allows for better performance on a car detection task when only a limited number of labeled training examples is available. Furthermore, the network that incorporates sparse coding allows for more consistent performance over varying initializations and ordering of training examples when compared to a fully supervised DCNN. Finally, we compare activations between the unsupervised sparse-coding layer and the supervised convolutional layer, and show that the sparse representation exhibits an encoding that is depth selective, whereas encodings from the convolutional layer do not exhibit such selectivity. These result indicates promise for using unsupervised sparse-coding approaches in real-world computer vision tasks in domains with limited labeled training data

Planet formation around stars of various masses: The snow line and the frequency of giant planets

We use a semi-analytic circumstellar disk model that considers movement of the snow line through evolution of accretion and the central star to investigate how gas giant frequency changes with stellar mass. The snow line distance changes weakly with stellar mass; thus giant planets form over a wide range of spectral types. The probability that a given star has at least one gas giant increases linearly with stellar mass from 0.4 M_sun to 3 M_sun. Stars more massive than 3 M_sun evolve quickly to the main-sequence, which pushes the snow line to 10-15 AU before protoplanets form and limits the range of disk masses that form giant planet cores. If the frequency of gas giants around solar-mass stars is 6%, we predict occurrence rates of 1% for 0.4 M_sun stars and 10% for 1.5 M_sun stars. This result is largely insensitive to our assumed model parameters. Finally, the movement of the snow line as stars >2.5 M_sun move to the main-sequence may allow the ocean planets suggested by Leger et. al. to form without migration.Comment: Accepted to ApJ. 12 pages of emulateap

The discovery of a low mass, pre-main-sequence stellar association around gamma Velorum

We report the serendipitous discovery of a population of low mass, pre-main sequence stars (PMS) in the direction of the Wolf-Rayet/O-star binary system gamma^{2} Vel and the Vela OB2 association. We argue that gamma^{2} Vel and the low mass stars are truly associated, are approximately coeval and that both are at distances between 360-490 pc, disagreeing at the 2 sigma level with the recent Hipparcos parallax of gamma^{2} Vel, but consistent with older distance estimates. Our results clearly have implications for the physical parameters of the gamma^{2} Vel system, but also offer an exciting opportunity to investigate the influence of high mass stars on the mass function and circumstellar disc lifetimes of their lower mass PMS siblings.Comment: Monthly Notices of the Royal Astronomical Society, Letters - in pres

Sidestepping Copyright: British Fairy Tale Anthologies of the 19th Century

One question is how in the golden period of fairy tale anthologising the work of the anthologists escaped the complete influence of copyright law with its paradigm of the individually authored work. The answer, it is suggested, lies, in part, in the early anthologists who formed a folklore society, saw themselves as anthropologists of folk culture, and treated copyright as largely irrelevant for the sake of their perception of the common good, and, in part, in the structure of copyright law itself which does not mandate but simply permits proprietary rights to be asserted