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Attributes now play a vital role for characterizing a crowded scene. Compared to low-level visual features, processing informed by attributes can capture rich semantic information. However, to effectively assign attributes to a crowded scene still remains a challenging task. In this letter, inspired by a recently proposed zero-shot learning framework, a novel attribute assignment method that maps...
Crop segmentation from the images captured in the outdoor field is a complex task in agriculture automation, let alone detecting some specific crops with one method. Cotton, as one of the four major economic crops, is of great significance to the development of the national economy. In this paper, a novel strategy based on the deep learning is utilized to establish the crop classifier in the RGB vector...
In order to help patients achieve effective and coordinating multi-joints movement easily, the paper presents an active training method of a lower limb rehabilitation robot based on constrained trajectory. The realization process of the method is as follows. The patient's movement intention is recognized by analyzing the signals from torque sensors installed in rehabilitation robot joints, and the...
In this paper, we propose an automatic scoring method for the open answer task of the Japanese speaking test SJ-CAT. The proposed method first extracts a set of features from an input answer utterance and then estimates a vocabulary richness score by human raters, which ranges from 0 to 4, by employing SVR (support vector regression). We devised a novel set of features, namely text statistics weighted...
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