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This paper proposes a deep learning model, named DeepSleepNet, for automatic sleep stage scoring based on raw single-channel EEG. Most of the existing methods rely on hand-engineered features, which require prior knowledge of sleep analysis. Only a few of them encode the temporal information, such as transition rules, which is important for identifying the next sleep stages, into the extracted features...
Over-segmentation is often used in text recognition to generate candidate characters. In this paper, we propose a neural network-based over-segmentation method for cropped scene text recognition. On binarized text line image, a segmentation window slides over each connected component, and a neural network is used to classify whether the window locates a segmentation point or not. We evaluate several...
Character string recognition based on over segmentation by integrating character classifier and context models has been demonstrated successful. Geometric context models characterizing the candidate character likeliness and between character relationship have shown benefits in several scripts but have not been evaluated in numeral string recognition. Compared with Chinese scripts mixed with alphanumeric...
In face recognition, LBP (Local Binary Patterns) is a very popular method, which can solve the defects of the traditional local feature extraction methods with fixed scale and small extraction scale. However, the LBP operator only describes the relationship between the center pixel and its neighborhood pixels, it ignores the relationship among the operators. 3DLBP (3 Dimensions Local Binary Patterns)...
The implementation of azimuth recognition technology for current mobile phone platform is mainly based on hardware (such as gyroscopes) and software (such as compass). Those related methods have shortcomings or limitations. This article proposes an improved algorithm based on SIFT to implement azimuth recognition. This method uses the camera to obtain image data, matching with the data in the information...
This paper presents a design of simultaneous localization and mapping (SLAM) for an omni-directional mobile robot using an omni-directional camera. A method is proposed to realize visual SLAM of the omni-directional mobile robot based on extended Kalman filter (EKF). Taking advantage of the 360deg view of omni-directional images, visual reference scan approach is adopted in the SLAM design. Features...
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