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9. An End to End Method for Scene Text Detection and Recognition

Author

Geng, Jing, Cao, Congjun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ye, Zhuangzhi, editor, Xu, Min, editor, Yang, Li, editor, Zhang, Linghao, editor, and Zhu, Rengao, editor

Published
2021
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11. Preparation of Super-Hydrophobic Surface via Fluorinated Epoxy Resin and Nano-SiO2

Author

Hou, Chengmin, Kou, Yanping, Cao, Congjun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ye, Zhuangzhi, editor, Xu, Min, editor, and Yang, Li, editor

Published
2020
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12. Optimal Tone Reproduction of Different Oil Painting Style Images

Author

Geng, Jing, Cao, Congjun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ye, Zhuangzhi, editor, Xu, Min, editor, and Yang, Li, editor

Published
2020
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13. Preparation of Low Temperature Sintered Graphene/Silver Nanocomposite-Based Conductive Ink

Author

Zou, Qingqing, Cao, Congjun, Zhu, Huayang, Hou, Chengmin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ouyang, Yun, editor, Xu, Min, editor, Yang, Li, editor, and Ren, Yuhui, editor

Published
2019
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14. Influence of Image Noise on Digital Photo Definition

Author

Geng, Jing, Cao, Congjun, Qi, Yonghong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ouyang, Yun, editor, Xu, Min, editor, Yang, Li, editor, and Ren, Yuhui, editor

Published
2019
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15. High-Simulation Oil-Painting-Style Images Based on Stroke Characteristics

Author

Geng, Jing, Cao, Congjun, Qi, Yonghong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Zhao, Pengfei, editor, Ouyang, Yun, editor, Xu, Min, editor, Yang, Li, editor, and Ren, Yuhui, editor

Published
2019
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20. High Image Quality Tone Adjustment Methods for Binary Images

Author

Geng, Jing, Cao, Congjun, Wu, Weiguo, Angrisani, Leopoldo, Series editor, Arteaga, Marco, Series editor, Chakraborty, Samarjit, Series editor, Chen, Jiming, Series editor, Chen, Tan Kay, Series editor, Dillmann, Ruediger, Series editor, Duan, Haibin, Series editor, Ferrari, Gianluigi, Series editor, Ferre, Manuel, Series editor, Hirche, Sandra, Series editor, Jabbari, Faryar, Series editor, Kacprzyk, Janusz, Series editor, Khamis, Alaa, Series editor, Kroeger, Torsten, Series editor, Ming, Tan Cher, Series editor, Minker, Wolfgang, Series editor, Misra, Pradeep, Series editor, Möller, Sebastian, Series editor, Mukhopadhyay, Subhas Chandra, Series editor, Ning, Cun-Zheng, Series editor, Nishida, Toyoaki, Series editor, Panigrahi, Bijaya Ketan, Series editor, Pascucci, Federica, Series editor, Samad, Tariq, Series editor, Seng, Gan Woon, Series editor, Veiga, Germano, Series editor, Wu, Haitao, Series editor, Zhang, Junjie James, Series editor, Zhao, Pengfei, editor, Ouyang, Yun, editor, Xu, Min, editor, Yang, Li, editor, and Ren, Yuhui, editor

Published
2018
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21. Preparation of Super-Hydrophobic Cotton Fabric with Crosslinkable Fluoropolymer

Author

Ma, Yaling, Cao, Congjun, Hou, Chengmin, Angrisani, Leopoldo, Series editor, Arteaga, Marco, Series editor, Chakraborty, Samarjit, Series editor, Chen, Jiming, Series editor, Chen, Tan Kay, Series editor, Dillmann, Ruediger, Series editor, Duan, Haibin, Series editor, Ferrari, Gianluigi, Series editor, Ferre, Manuel, Series editor, Hirche, Sandra, Series editor, Jabbari, Faryar, Series editor, Kacprzyk, Janusz, Series editor, Khamis, Alaa, Series editor, Kroeger, Torsten, Series editor, Ming, Tan Cher, Series editor, Minker, Wolfgang, Series editor, Misra, Pradeep, Series editor, Möller, Sebastian, Series editor, Mukhopadhyay, Subhas Chandra, Series editor, Ning, Cun-Zheng, Series editor, Nishida, Toyoaki, Series editor, Panigrahi, Bijaya Ketan, Series editor, Pascucci, Federica, Series editor, Samad, Tariq, Series editor, Seng, Gan Woon, Series editor, Veiga, Germano, Series editor, Wu, Haitao, Series editor, Zhang, Junjie James, Series editor, Zhao, Pengfei, editor, Ouyang, Yun, editor, Xu, Min, editor, Yang, Li, editor, and Ren, Yuhui, editor

Published
2018
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25. A Continuous Non-Invasive Blood Pressure Prediction Method Based on Deep Sparse Residual U-Net Combined with Improved Squeeze and Excitation Skip Connections.

Author

Lai, Kaixuan, Wang, Xusheng, and Cao, Congjun

Subjects
DIASTOLIC blood pressure, SYSTOLIC blood pressure, DEEP learning, BLOOD pressure, NETWORK performance, DEEP brain stimulation
Abstract

Arterial blood pressure (ABP) serves as a pivotal clinical metric in cardiovascular health assessments, with the precise forecasting of continuous blood pressure assuming a critical role in both preventing and treating cardiovascular diseases. This study proposes a novel continuous non-invasive blood pressure prediction model, DSRUnet, based on deep sparse residual U-net combined with improved SE skip connections, which aim to enhance the accuracy of using photoplethysmography (PPG) signals for continuous blood pressure prediction. The model first introduces a sparse residual connection approach for path contraction and expansion, facilitating richer information fusion and feature expansion to better capture subtle variations in the original PPG signals, thereby enhancing the network's representational capacity and predictive performance and mitigating potential degradation in the network performance. Furthermore, an enhanced SE-GRU module was embedded in the skip connections to model and weight global information using an attention mechanism, capturing the temporal features of the PPG pulse signals through GRU layers to improve the quality of the transferred feature information and reduce redundant feature learning. Finally, a deep supervision mechanism was incorporated into the decoder module to guide the lower-level network to learn effective feature representations, alleviating the problem of gradient vanishing and facilitating effective training of the network. The proposed DSRUnet model was trained and tested on the publicly available UCI-BP dataset, with the average absolute errors for predicting systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean blood pressure (MBP) being 3.36 ± 6.61 mmHg, 2.35 ± 4.54 mmHg, and 2.21 ± 4.36 mmHg, respectively, meeting the standards set by the Association for the Advancement of Medical Instrumentation (AAMI), and achieving Grade A according to the British Hypertension Society (BHS) Standard for SBP and DBP predictions. Through ablation experiments and comparisons with other state-of-the-art methods, the effectiveness of DSRUnet in blood pressure prediction tasks, particularly for SBP, which generally yields poor prediction results, was significantly higher. The experimental results demonstrate that the DSRUnet model can accurately utilize PPG signals for real-time continuous blood pressure prediction and obtain high-quality and high-precision blood pressure prediction waveforms. Due to its non-invasiveness, continuity, and clinical relevance, the model may have significant implications for clinical applications in hospitals and research on wearable devices in daily life. [ABSTRACT FROM AUTHOR]

Published
2024
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26. Advances in the noninvasive and minimally invasive sample collection for wearable electrochemical sensors.

Author

Lu, Danfeng, Yang, Chenxi, Chen, Luyang, Cao, Congjun, Xia, Weimin, Li, Guanglei, and Wen, Dan

Subjects
WEARABLE technology, ELECTROCHEMICAL sensors, POINT-of-care testing, FABRICATION (Manufacturing), COLLECTIONS
Abstract

Wearable electrochemical sensors, which can track various biomarkers in real‐time, is one of the most promising bioanalytical devices in the point of care testing and health management. Sample collection modules, as the important front‐end of the sensors, capture and transfer enough sample so as to achieve real‐time, precise and accurate detection. Noninvasive and minimally invasive techniques for sample collection are highly desired. However, it is still a key challenge to realize a reliable sample acquisition. Herein, we provide an overview on the progress in the sample collection methods for wearable electrochemical sensors. It covers the conventional and emerging methods/structures including reverse iontophoresis, microneedles, as well as microfluidic chips. The working principle, fabrication materials and manufacturing technologies will be introduced in detail. Finally, the present challenges and the development trend in the future of these approaches are also put forward. [ABSTRACT FROM AUTHOR]

Published
2024
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36. B-site doping of ZrO2 to improve the dielectric and energy storge performances of a BNBS-(Ti1−x,Zrx) ceramic.

Author

Ai, Na, Xia, Weimin, Lu, Tao, Cao, Congjun, Li, Jing, and Zhao, Mengjie

Abstract

A group of (0.65Bi0.5Na0.5–0.35Bi0.2Sr0.7)(Ti1−x,Zrx)O3 (BNBS-(Ti1−x,Zrx)) lead-free energy storage ceramic sheets are prepared by a conventional solid-state sintering method. We find that B-site doping of ZrO2 may minimize the grain size while not change the perovskite structure of BNBS-(Ti1−x,Zrx). As such, BNBS-(Ti1−x,Zrx) possesses the uniform grains and clear grain boundaries, resulting in a high dielectric permittivity (εr) of about 2080 and a low dielectric loss (tanδ) of 0.05 at 100 Hz. Due to the lattice distortion caused by Zr4+ entering the TiO6 octahedral lattice, Tm of BNBS-(Ti1−x,Zrx) decreases with the increase of ZrO2 doping content. Attractively, BNBS-(Ti1−x,Zrx) exhibits relatively slender polarization-electric field (P-E) loops at a high electric field of 100 kV/cm, and BNBS-(Ti0.97,Zr0.03) achieves considerable recycle discharging energy density (Wrec) of 1.47 J/cm3 and high efficiency (η) of 86.94%. Thus, as a block ceramic synthesized by convenient process, this result is superior to most of similar BNT-based materials, and may provide a reference for pulse power capacitors. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Bow image retrieval method based on SSD target detection

Author

Kaiyang Liao, Cao Congjun, Yuanlin Zheng, Guangfeng Lin, and Fan Bing

Subjects
Contextual image classification, business.industry, Computer science, Feature vector, Feature extraction, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020206 networking & telecommunications, 02 engineering and technology, Object (computer science), Object detection, Image (mathematics), Signal Processing, 0202 electrical engineering, electronic engineering, information engineering, Graph (abstract data type), 020201 artificial intelligence & image processing, Computer vision, Computer Vision and Pattern Recognition, Artificial intelligence, Electrical and Electronic Engineering, business, Image retrieval, Software
Abstract

The query image is usually a simple and single object in image retrieval, and the reference images in the database usually have many distractions. The precision of image retrieval can be greatly improved If the target regions in the database image are extracted during retrieval. So this paper proposes a Bow image retrieval method based on SSD target detection. First, the training gallery is manually annotated to record the location and size information. Second, the SSD target detection model is trained with the labeled training gallery to obtain the target object SSD model. Third, the SSD model is used to locate the similar target regions of the reference image and the query graph. Finally, the target region information is mapped into the convolutional features, and these feature vectors are used for image similarity matching. The performance of the proposed method is evaluated on Paris6k, Oxford5k, Paris106k and Oxford105k databases. The experimental results show that the accuracy of image retrieval will be greatly improved by adding optimization methods in the proposed image retrieval framework. The image retrieval accuracy of this method is higher than that of similar methods in recent years.

Published
2020

49. IR Feature Embedded BOF Indexing Method for Near-Duplicate Video Retrieval

Author

Ding Jie, Cao Congjun, Yuanlin Zheng, Zhang Mingzhu, Lei Hao, Kaiyang Liao, and Guangfeng Lin

Subjects
Radon transform, business.industry, Computer science, Quantization (signal processing), Search engine indexing, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Pattern recognition, 02 engineering and technology, Discriminative model, Principal component analysis, 0202 electrical engineering, electronic engineering, information engineering, Media Technology, 020201 artificial intelligence & image processing, Artificial intelligence, Electrical and Electronic Engineering, Invariant (mathematics), business, Transformation geometry, Video retrieval
Abstract

Due to the explosive increase in online videos, near-duplicate video retrieval (NDVR) has attracted much researcher attention. NDVR has very wide applications, such as copyright protection, online video monitoring, and automatic video tagging. Local features serve as elementary building blocks in many NDVR algorithms, and most of them exploit the local volume information using a bag of features (BOF) representation. However, such representation ignores potentially valuable information about the global distribution of interest points. Moreover, the discriminative power of the local descriptors is significantly reduced by the quantizer in BOF. Our motivation is that if we use the global features to classify the same or similar keyframes into the same class, it will be very useful in improving the performance of NDVR. In this paper, we present an improved radon transform (IR) feature which captures the detailed global geometrical distribution of interest points. It is calculated by using the 2D discrete Radon transform, and then applying a principal component analysis. Such IR feature is not only invariant to the geometry transformations but also robust to the noises. In addition, we propose a fusion strategy to combine the BOF representation with the global IR feature for further improving the recognition accuracy. Convincing experimental results on several publicly available datasets demonstrate that our proposed approach outperforms the state-of-the-art approaches in NDVR.

Published
2019

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