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Automatic identification of HEp-2 cell images has received an increasing research attention. Feature representations play a critical role in achieving good identification performance. Much recent work has focused on supervised feature learning. Typical methods consist of BoW model (based on hand-crafted features) and deep learning model (learning hierarchical features). However, these labels used...
This paper presents a novel error concealment method for AMR-WB codec, using excitation search constraint at the encoder and a linear prediction of the pitch and gains of the adaptive codebook and the innovative codebook at the decoder to enhance speech quality after a frame erasure. The experimental results demonstrate that the proposed method achieves performance improvement over the existing methods.
A novel Boundary-Scan circuit compatible with IEEE 1149.1 standard and designed for our SOI-Based FPGA is presented in this paper. The new Boundary-Scan circuit serves the test of FPGA at the chip as well as board level and the added features facilitate the configuration and verification functions of FPGA. The Boundary-Scan circuit in this paper has been implemented in an SRAM-Based FPGA fabricated...
Data hiding is a type of information hiding technology. A data hiding method based on H.264 encoded video sequences is presented in this paper. The proposed method uses the parity of the coefficients after transformation and quantization to hide the desirable data. The digital data hidden by this approach can be recovered correctly by data recovering process and extracted directly from the encoded...
This paper presents a study on joint coding of video plus depth utilizing the correlation between video and depth. The Rate Distortion Optimization (RDO) technique has been employed in H.264 for intra prediction mode selection to achieve better coding efficiency. The proposed method considers the color video and depth video to compress jointly, which is based on the RDO mode decision algorithm and...
A method of using two-class classifiers in emotion recognition was discussed. Emotion classes were divided into pairs for improved feature selection and optimization. Each pair of emotions was classified by a two-class classifier and the final recognition result was reached by a correlation decoder. Compared with n-class classifier, using two-class classifiers for each pair of emotions is more suitable...
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