Verb errors are one of the most common grammar errors made by non-native writers of English. This work especially focus on an important type of verb usage errors, subject-verb agreement for the third person singular f...
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Verb errors are one of the most common grammar errors made by non-native writers of English. This work especially focus on an important type of verb usage errors, subject-verb agreement for the third person singular forms, which has a high proportion in errors made by non-native English learners. Existing work has not given a satisfied solution for this task, in which those using supervised learning method usually fail to output good enough performance, and rule-based methods depend on advanced linguistic resources such as syntactic parsers. In this paper, we propose a rule-based method to detect and correct the concerned errors. The proposed method relies on a series of rules to automatically locate subject and predicate in four types of sentences. The evaluation shows that the proposed method gives state-of-The-Art performance with quite limited linguistic resources.
The growing study in RGB-D sensor and 3D point cloud have made new progress in obstacle avoidance for the visually impaired. However, it remains a challenging problem due to the difficulty in design a robust and real-...
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The AGM postulates are for the belief revision (revision by a single belief), and the DP postulates are for the iterated revision (revision by a finite sequence of beliefs). Li (The Computer Journal 50:378–390, 2007)...
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Although significant success has been achieved in fine-grained visual categorization, most of existing methods require bounding boxes or part annotations for training and test, resulting in limited usability and flexi...
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Although significant success has been achieved in fine-grained visual categorization, most of existing methods require bounding boxes or part annotations for training and test, resulting in limited usability and flexibility. To conquer these limitations, we aim to automatically detect the bounding box and parts for fine-grained object classification. The bounding boxes are acquired by a transferring strategy which infers the locations of objects from a set of annotated training images. Based on the generated bounding box, we propose a multiple-layer Orientational Spatial Part (OSP) model to generate a refined description for the object. Finally, we employ the output of deep Convolutional Neural Network (dCNN) as the feature and train a linear SVM as object classifier. Extensive experiments on public benchmark datasets manifest the impressive performance of our method, i.e., Classification accuracy achieves 63.9% on CUB-200-2011 and 75.6% on Aircraft, which are actually higher than many existing methods using manual annotations.
Large-field high-resolution electron tomography enables visualizing detailed mechanisms under global structure. As field enlarges, the processing time increases and the distortions in reconstruction become more critic...
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ABGP is a special cognitive model, which consists of awareness, beliefs, goals and plans. As most agent architectures, ABGP agents obtain knowledge from the natural scenes only through single preestablished rules as w...
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ISBN:
(纸本)9781509001644
ABGP is a special cognitive model, which consists of awareness, beliefs, goals and plans. As most agent architectures, ABGP agents obtain knowledge from the natural scenes only through single preestablished rules as well, don't directly capture the natural scenes information like human visual. Inspired by the biological visual cortex (V1) and the higher brain areas perceiving visual features, we propose a novel deep network model convolutional generative stochastic model (CGSM) used to visual feature representation, and firstly introduce it into the awareness module of the cognitive model ABGP to construct a state-of-the-art cognitive model ABGP-CGSM. For the novel cognitive model ABGP-CGSM, we construct a rat-robot maze search simulation platform to show the validity recognizing natural scenes. According to the simulation results on the noise and noiseless natural scenes, the rat-robot implemented by ABGP-CGSM has an excellent success rate when passing through the maze. The simulation shows that the ABGP-CGSM model proposed in our work can directly enhance the capability of communication between agent and natural scenes, improve the ability to cognize the real world as human being and conduct the agent to plan independently its path in terms of the visual information from the natural scenes.
Particle selection from cryo-electron microscopy (cryo-EM) images is very important for high-resolution reconstruction of macromolecular structure. However, the accuracy of existing selection methods are normally rest...
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＜正＞Cryo-electron tomography（ET）plays an important role in revealing biological structures,ranging from macromolecule scale to subcellular *** acquiring series of pictures with different angular assignment,one per...
＜正＞Cryo-electron tomography（ET）plays an important role in revealing biological structures,ranging from macromolecule scale to subcellular *** acquiring series of pictures with different angular assignment,one performs an inverse radon transform and gets the 3D structure of biological ***,since high angle
Curvelet transform is the combination of the multi-scale analysis and multi-directional analysis transforms, which is more suitable for objects with curves. Applications of the curvelet transform have increased rapidl...
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