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The cost of forest sampling can be reduced substantially by the ability to estimate forest and tree parameters directly from aerial photographs. However, in order to do so it is necessary to be able to accurately identify individual treetops and then to define the region in the vicinity of the treetop that encompasses the crown extent. These two steps(More)
BACKGROUND Crofton weed (Ageratina adenophora) is one of the most hazardous invasive plant species, which causes serious economic losses and environmental damages worldwide. However, the sequence resource and genome information of A. adenophora are rather limited, making phylogenetic identification and evolutionary studies very difficult. Here, we report(More)
Mangrove stands of differing species composition are hard to distinguish in conventional, coarse resolution satellite images. The new generation of meter-level satellite imagery provides a unique opportunity to achieve this goal. In this study, an IKONOS Geo bundle image and a QuickBird Standard bundle image were acquired for a study area located at Punta(More)
A central finding in many cortical areas is that single neurons can match behavioral performance in the discrimination of sensory stimuli. However, whether this is true for natural behaviors involving complex natural stimuli remains unknown. Here we use the model system of songbirds to address this problem. Specifically, we investigate whether neurons in(More)
Broomcorn millet (Panicum miliaceum L.) is one of the world's oldest cultivated cereals, which is well-adapted to extreme environments such as drought, heat, and salinity with an efficient C4 carbon fixation. Discovery and identification of genes involved in these processes will provide valuable information to improve the crop for meeting the challenge of(More)
This paper presents a simulation of a biological olfactory neural system with a KIII set, which is a high-dimensional chaotic neural network. The KIII set differs from conventional artificial neural networks by use of chaotic attractors for memory locations that are accessed by, chaotic trajectories. It was designed to simulate the patterns of action(More)
Mobile devices people carry in their pockets every day can use various means to connect to data services all around the Internet, e.g., 2G, 3G and WLAN. This has been an important development towards an easily accessible and always-on the Internet. While radio connectivity, bits rates in particular, has developed tremendously during the recent years,(More)
We present a method for automatically extracting salient object from a single image, which is cast in an energy minimization framework. Unlike most previous methods that only leverage appearance cues, we employ an auto-context cue as a complementary data term. Benefitting from a generic saliency model for bootstrapping, the segmentation of the salient(More)
This paper reviews existing population estimation methods in the GIS and remote sensing literatures. The methods can be grouped into two categories: areal interpolation methods and statistical modeling methods. Areal interpolation methods can be further separated into two categories depending on whether ancillary information is used. Statistical modeling(More)
We present a spatio-temporal energy minimization formulation for simultaneous video object discovery and co-segmentation across multiple videos containing irrelevant frames. Our approach overcomes a limitation that most existing video co-segmentation methods possess, i.e., they perform poorly when dealing with practical videos in which the target objects(More)