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As our knowledge, there is no dialog system for mental health-care domain in Hindi. This may be due to unavailability of user utterances corpora in Hindi for this domain. In this paper, we propose a novel algorithmic approach for user utterance ...

Aiming at the problems that most of the text classification models based on neural network are easy to overfit and ignore key words in sentences in the training process, an improved text classification model is proposed. The proposed model is a Bi-...

This article addresses the problem of learning compositional Chinese sentence representations, which represent the meaning of a sentence by composing the meanings of its constituent words. In contrast to English, a Chinese word is composed of characters,...

In this paper, we introduce a novel model for embedding image spatial information into a feature vector based on an extension of spatial pyramid model (SPM). Our novel model considers the spatial distributions of both visual words and visual word ...

We propose a Deep Neural Network (DNN) structure for RFID-based activity recognition. RFID data collected from several reader antennas with overlapping coverage have potential spatiotemporal relationships that can be used for object tracking. We ...

Text information contained in scene images is very helpful for high‐level image understanding. In this study, the authors propose to learn co‐occurrence of local strokes for scene text recognition by using a spatiality embedded dictionary (SED). Unlike ...

Pooling strategies, such as max pooling and sum pooling, have been widely used to obtain the global representations for action videos. However, these pooling strategies have several disadvantages. First, they are easily affected by unwanted background ...

A major challenge in real-world feature matching problems is to tolerate the numerous outliers arising in typical visual tasks. Variations in object appearance, shape, and structure within the same object class make it harder to distinguish inliers from ...

This paper presents a method of max-pooling spatially-coherent pyramid matching (MpScPM). Higher-layer representations are generated from lower-layer subregions, by a biologically-inspired max pooling strategy. Second, instead of reshaping the pyramid ...

We propose an image classification framework by leveraging the non-negative sparse coding, low-rank and sparse matrix decomposition techniques (LR-Sc^+ SPM). First, we propose a new non-negative sparse coding along with max pooling and spatial pyramid ...