Formation and tidal evolution of hot super-Earths in multiple planetary systems

Hot super-Earths are exoplanets with masses < 10 Earth masses and orbital periods < 20 days. Around 8 hot super-Earths have been discovered in the neighborhood of solar system. In this lecture, we review the mechanisms for the formation of hot super-Earths, dynamical effects that play important roles in sculpting the architecture of the multiple planetary systems. Two example systems (HD 40307 and GJ 436) are presented to show the formation and evolution of hot super-Earths or Neptunes.Comment: 12 pages, 4 color figures, Lecture in 'Extrasolar planets in Multi-Body systems: Theory and Observation',Torun (Poland), August 25-29, 2008, to appear in European Astronomical Society Publication Serie

Fine-grained Image Classification by Exploring Bipartite-Graph Labels

Given a food image, can a fine-grained object recognition engine tell "which restaurant which dish" the food belongs to? Such ultra-fine grained image recognition is the key for many applications like search by images, but it is very challenging because it needs to discern subtle difference between classes while dealing with the scarcity of training data. Fortunately, the ultra-fine granularity naturally brings rich relationships among object classes. This paper proposes a novel approach to exploit the rich relationships through bipartite-graph labels (BGL). We show how to model BGL in an overall convolutional neural networks and the resulting system can be optimized through back-propagation. We also show that it is computationally efficient in inference thanks to the bipartite structure. To facilitate the study, we construct a new food benchmark dataset, which consists of 37,885 food images collected from 6 restaurants and totally 975 menus. Experimental results on this new food and three other datasets demonstrates BGL advances previous works in fine-grained object recognition. An online demo is available at http://www.f-zhou.com/fg_demo/