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13 results on '"Zhang, Jicun"'

1. ASM: Audio Spectrogram Mixer

Author

Ji, Qingfeng, Zhang, Jicun, and Wang, Yuxin

Subjects
Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Transformer structures have demonstrated outstanding skills in the deep learning space recently, significantly increasing the accuracy of models across a variety of domains. Researchers have started to question whether such a sophisticated network structure is actually necessary and whether equally outstanding results can be reached with reduced inference cost due to its complicated network topology and high inference cost. In order to prove the Mixer's efficacy on three datasets Speech Commands, UrbanSound8k, and CASIA Chinese Sentiment Corpus this paper applies amore condensed version of the Mixer to an audio classification task and conducts comparative experiments with the Transformer-based Audio Spectrogram Transformer (AST)model. In addition, this paper conducts comparative experiments on the application of several activation functions in Mixer, namely GeLU, Mish, Swish and Acon-C. Further-more, the use of various activation functions in Mixer, including GeLU, Mish, Swish, and Acon-C, is compared in this research through comparison experiments. Additionally, some AST model flaws are highlighted, and the model suggested in this study is improved as a result. In conclusion, a model called the Audio Spectrogram Mixer, which is the first model for audio classification with Mixer, is suggested in this study and the model's future directions for improvement are examined.

Published
2024

2. CoT-Enhanced CNN-ViT Fusion with Adaptive Token Learning for Precise Facial Expression Recognition

Author

Xiong, Lingxin, Zhang, Jicun, Zheng, Xiaojia, Wang, Yuxin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yadav, Sanjay, editor, Arya, Yogendra, editor, Pandey, Shailesh M., editor, Gherabi, Noredine, editor, and Karras, Dimitrios A., editor

Published
2024
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6. Research on Luggage Package Extraction of X-ray Images Based on Edge Sensitive Multi-Channel Background Difference Algorithm.

Author

Song, Xueping, Zhang, Shuyu, Yang, Jianming, and Zhang, Jicun

Subjects
X-ray imaging, MACHINE learning, ALGORITHMS, LUGGAGE, GRAYSCALE model, DEEP learning
Abstract

Many security detectors do not have the ability to output individual luggage package images and are not compatible with deep learning algorithms. In this paper, a luggage package extraction of X-ray images based on the ES-MBD (Edge Sensitive Multi-channel Background Difference Algorithm) method is proposed, which is aiming at the problem that background difference binarization is insensitive to texture features and edge detection binarization is insensitive to smooth areas. In this method, X-ray luggage package images from complex original video images are used as a key target, the RGB three-channel background difference is calculated from the original X-ray image, the edge detection of the grayscale map is performed using the Sobel operator optimized by local gradient enhancement, and the morphological expansion process is performed on the combined results to obtain the complete wrapping target. The Suzuki algorithm is used to detect the outline of the binarized package image, match the package frame area and determine the key target. The ES-MBD method solves the problem of information loss in the traditional binarization method, and retains the information of insensitive regions while reducing noise. Through experimental comparison, the accuracy of ES-MBD binarization method reaches 97.3%, the recall rate reaches 96.5%, and ES-MBD method has obvious advantages in key target extraction of X-ray images. [ABSTRACT FROM AUTHOR]

Published
2023
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10. Blueberry anthocyanin-enriched extract ameliorates transverse aortic constriction-induced myocardial dysfunction via the DDAH1/ADMA/NO signaling pathway in mice.

Author

Hu, Weiqing, Wang, Wenyue, Ma, Qing, Liu, Tao, Zhang, Jiefeng, and Zhang, Jicun

Subjects
ASYMMETRIC dimethylarginine, LEFT ventricular hypertrophy, BLUEBERRIES, WESTERN immunoblotting, MICE, OXIDATIVE stress
Abstract

Blueberry anthocyanin-enriched extract (BAE) has been demonstrated to protect against cardiovascular diseases by activating multiple target genes. The present study investigated the effects of BAE on transverse aortic constriction (TAC)-induced myocardial dysfunction in mice and explored its possible molecular mechanisms. A total of 30 male mice were divided randomly into control, TAC and TAC + BAE groups. Mice in the TAC + BAE groups were administered BAE by oral gavage for 6 consecutive weeks. Myocardial dysfunction was assessed using echocardiogram, histopathology, TUNEL assay, immunofluorescence staining, reverse transcription-quantitative PCR and western blot analysis. The results demonstrated that BAE treatment significantly ameliorated heart weight, left ventricular weight, myocardial dysfunction, left ventricular hypertrophy and fibrosis. In addition, BAE treatment alleviated TAC-induced inflammation, oxidative stress and apoptosis. Notably, BAE treatment markedly reduced asymmetric dimethylarginine (ADMA) concentration and significantly increased dimethylarginine dimethylaminohydrolase 1 (DDAH1) expression and nitric oxide (NO) production. The present data indicated that BAE treatment ameliorated TAC-induced myocardial dysfunction, oxidative stress, inflammatory response and apoptosis via the DDAH1/ADMA/NO signaling pathway. [ABSTRACT FROM AUTHOR]

Published
2020
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11. A low-power parallel-to-serial conversion circuit for CMOS image sensors

Author

Chen Nan, Zhang Jicun, Yao Libin, and Liu Chuanming

Subjects
CMOS sensor, Engineering, business.industry, Amplifier, Pulse generator, Diode-or circuit, Hardware_PERFORMANCEANDRELIABILITY, Circuit extraction, CMOS, Hardware_INTEGRATEDCIRCUITS, Electronic engineering, Image sensor, business, Hardware_LOGICDESIGN, Electronic circuit
Abstract

A low-power parallel-to-serial conversion circuit for CMOS image sensors (CIS) aimed for high-data-rate and power-restricted applications, is introduced in this paper. Parallel data are scanned and serialized by the delay-locked loop (DLL)-based pulse generator, wired-AND circuit and a current-mode amplifier. Unlike the conventional parallel-to-serial conversion circuit in CMOS image sensors, the proposed circuit doesn't need a clock tree and therefore consumes much less power. The circuit is designed in a 0.35μm CMOS process. The simulation results show that the power consumption of the proposed parallel-to-serial conversion circuit is reduced significantly compared to the conventional circuits especially in high-data-rate CMOS image sensor applications. The proposed circuit for 12-bit × 256-column CMOS image sensor is capable to operate at the data rate of 600 Mbps consuming 4.07 mW, which is 0.7% and 2.5% of the power consumption of the conventional shift-register scheme and the clock-gating scheme, respectively.

Published
2015

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