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Adaptive tag selection for image annotation 15

Adaptive tag selection for image annotation

引用

15th Pacific-Rim Conference on Multimedia, PCM 2014

作者： He, Xixi Li, Xirong Yang, Gang Xu, Jieping Jin, Qin Key Lab of DEKE Renmin University of China 100872 China Multimedia Computing Lab Renmin University of China 100872 China Shanghai Key Laboratory of Intelligent Information Processing 200443 China

ISBN: (纸本)9783319131672

Not all tags are relevant to an image, and the number of relevant tags is image-dependent. Although many methods have been proposed for image auto-annotation, the question of how to determine the number of tags to be selected per image remains open. The main challenge is that for a large tag vocabulary, there is often a lack of ground truth data for acquiring optimal cutoff thresholds per tag. In contrast to previous works that pre-specify the number of tags to be selected, we propose in this paper adaptive tag selection. The key insight is to divide the vocabulary into two disjoint subsets, namely a seen set consisting of tags having ground truth available for optimizing their thresholds and a novel set consisting of tags without any ground truth. Such a division allows us to estimate how many tags shall be selected from the novel set according to the tags that have been selected from the seen set. The effectiveness of the proposed method is justified by our participation in the ImageCLEF 2014 image annotation task. On a set of 2,065 test images with ground truth available for 207 tags, the benchmark evaluation shows that compared to the popular top-k strategy which obtains an F-score of 0.122, adaptive tag selection achieves a higher Fscore of 0.223. Moreover, by treating the underlying image annotation system as a black box, the new method can be used as an easy plug-in to boost the performance of existing systems. © Springer International Publishing Switzerland 2014.

关键词： Image annotation

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Prosody Prediction with Discriminative Representation Method 3

Prosody Prediction with Discriminative Representation Method

引用

3rd International Conference on Pattern Recognition and Machine Learning, PRML 2022

作者： Zhang, Jipeng Yilahun, Hankiz Feng, Xiaoqin Chen, Yunlin Yang, Xipeng Hamdulla, Askar School of Information Science and Engineering Xinjiang University of China China Xinjiang Key Laboratory of Signal Detection and Processing China Xinjiang Key Laboratory of Multilingual Information Technology China Mobvoi Ai Lab Suzhou China

ISBN: (数字)9781665499507

ISBN: (纸本)9781665499507

Rhythm affects the naturalness and intelligibility of Text-To-Speech (TTS). However, rhythm prediction remains a great challenge, usually in two aspects: 1) the united annotation is a relatively difficult task, which depends on expert's experience. 2) traditional methods based on conditional random field (CRF), which heavily rely on feature engineering, such as word segmentation, part of speech(pos) etc. For above problems, we propose a method to reduce the dependency for united annotation data and conduct the joint experiment which use one unified model on independent data. Meanwhile, we also propose an algorithm of Layer Look Up Table (LLUT): use an embedding layer to learn a discriminative representation for different level of prosody data without any feature engineering. By using this method, the classifier can share the parameters and predict for different prosody level separately, which reduces the number of trainable model parameters. In order to better represent the input text, we use the pre-training model, like BERT, to provide the semantic information. Our experiment shows that the method of LLUT, is better able to acquire the discriminative meaning of different prosody levels. And also, our algorithm is proved to be general for sequence annotation tasks thus we can do extra task, like polyphone-prosody prediction. © 2022 IEEE.

关键词： Forecasting

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Exploration and Practice of Teaching Reform of Computer Public Courses Under Big Data Environment

Exploration and Practice of Teaching Reform of Computer Publ...

引用

International Conference on Cyber Security Intelligence and Analytics, CSIA 2020

作者： Zhang, Hua Wang, Jiong Wu, Zhengyuan College of Computer and Control Engineering Minjiang University Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (纸本)9783030433055

Computers are the necessary professional knowledge of modern talents, and universities offer computer public courses to meet the needs of social talents development. At present, there are many problems existing in the computer courses teaching in colleges and universities, such as loose content, lagging mode, slow feedback, etc., and the classroom teaching is not efficient. Based on the big data environment, applying information technology to the teaching of computer public courses can re-plan the course, improve the teaching mode, collect students’ teaching evaluation, and improve the teaching effect. The article will analyze the problems existing in the teaching process of computer public courses in China, and propose corresponding reform strategies, aiming at promoting the development of teaching in colleges and universities, improving the quality of talents and meeting the development needs of the times. © Springer Nature Switzerland AG 2020.

关键词： Big data

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The textual semantic lens

The textual semantic lens

引用

7th International Conference on Semantics, Knowledge, and Grids, SKG 2011

作者： Xu, B. Zhuge, H. Chinese Academy of Sciences Key Lab of Intelligent Information Processing Institute of Computing Technology Beijing 100080 China Graduate School Chinese Academy of Sciences China

ISBN: (纸本)9780769545158

People often feel the limitation of time to read the continuously increasing articles they need to read. It is a grand challenge to handle the explosion of articles. To understand how humans read articles and get the meaning is the basis of improving the efficiency of reading articles. The underlying semantic links between language units of different granularities reflect some basic semantics. Sentence is the basic language unit for accurately indicating semantics. By defining concepts and the dependent set of sentences, and constructing the semantic link network of dependent sentences and semantic link network of concepts, this paper proposes the textual semantic lens with a set of functions for helping people comprehend articles. Integrating with the semantic link networks of articles, the semantic lens can help people efficiently read large-scale articles. © 2011 IEEE.

关键词： Semantics

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Trajectory Planning of Launch Vehicle Orbital Injection Segment Under Engine Failure Based on DDPG Algorithm

Trajectory Planning of Launch Vehicle Orbital Injection Seg...

引用

Chinese intelligent Automation Conference, CIAC 2023

作者： Xiang, Zhuo Wang, Bo Liu, Lei Fan, Huijin National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789819961863

Traditional methods for rocket orbiting have serious deficiencies in orbital accuracy and computational efficiency, and cannot handle engine failure which leads to thrust drop. Accordingly, this manuscript designs a trajectory planning algorithm based on DDPG for the launch vehicle into orbit, transforms the rocket orbiting into an MDP problem, and constructs reward functions that satisfy the flight process and terminal constraints. The simulation results show that this method has significantly improved the accuracy of orbiting and calculation efficiency, and has the ability to adjust to suitable orbit adaptively under failure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Rockets

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Research of Scene Text Detection Algorithms 5

Research of Scene Text Detection Algorithms

引用

5th International Conference on intelligent Robotics and Control Engineering, IRCE 2022

作者： Chen, Mengmeng Ibrayim, Mayire Hamdulla, Askar School of Information Science and Engineering Xinjiang University Xinjiang Key Laboratory of Signal Detection and Processing Xinjiang Urumqi China School of Information Science and Engineering Xinjiang University Xinjiang Key Laboratory of Multilingual Information Technology Xinjiang Urumqi China

ISBN: (数字)9781665469951

ISBN: (纸本)9781665469951

With the development of artificial intelligence, obtaining textual information from natural scenes has become a hot topic. There are still huge challenges for curved text and arbitrary orientation text detection in real-world scenes. In this work, we briefly introduce the development of text detection algorithms in recent years and study a typical lightweight detection algorithm. We have improved the algorithm to different degrees to make it more suitable for detection of the curved text. Finally, we select the three most representative public text datasets for experiments. Experiments conducted on CTW1500, ICDAR2015, and MSRA-TD500 have demonstrated the superiority of this model. © 2022 IEEE.

关键词： Deep learning

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Multi-font printed Mongolian document recognition system

Multi-font printed Mongolian document recognition system

引用

Document Recognition and Retrieval XVI

作者： Peng, Liangrui Liu, Changsong Ding, Xiaoqing Wang, Hua Jin, Jianming Department of Electronic Engineering Tsinghua University Beijing 100084 China Tsinghua National Laboratory for Information Science Technology State Key Laboratory of Intelligent Technology and Systems China

Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-fonttype variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts. © 2009 SPIE-IS&T.

关键词： Digital libraries

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A decoupled hybrid structure for active noise control with uncorrelatednarrowband disturbances 43

A decoupled hybrid structure for active noise control with u...

引用

43rd International Congress on Noise Control Engineering: Improving the World Through Noise Control, INTERNOISE 2014

作者： Wu, Lifu Qiu, Xiaojun Burnett, Ian S. Cheng, Eva Guo, Yecai Royal Melbourne Institute of Technology School of Electrical and Computer Engineering Australia Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science and Technology 210044 China

ISBN: (纸本)9780909882037

In real active noise control (ANC)applications,the following situations frequently occur, one isthat disturbances only present at the error sensor and havelowcorrelation with reference signal, the other is thatthere is no enough space or ideal position for locating the reference sensor to satisfy causality condition. Thusthe residual noise after feedforward control can be seen as uncorrelated narrowband disturbancesin these situationsand ahybrid adaptive feedforward and feedback structure is often utilized to cope with this *** efforts have been paid to improve the performance of the hybrid ANC system, nevertheless, few interests are concerned about the combination method between the feedforward and feedback structure. After investigating the conventional combination method of hybrid feedforward and feedback system, this paper introduces analternate combination method for hybrid ANC systemwhich featuresthat itavoidsthe coupling between the feedforward and feedback structures and both structures are concatenated to attenuate the ambient noise. Simulations are carried out to validatethe effectiveness of the introduced methodfor ANCwith uncorrelated narrowband disturbances.

关键词： Hybrid systems

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Short-Term Building Load Forecast Based on Patch Learning with Long Short-Term Memory Network and Support Vector Regression 1

引用

2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021

作者： Dan, Zhaohui Wang, Bo Fan, Huijin Liu, Lei Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Artificial Intelligence and Automation School Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789811651885

ISBN: (纸本)9789811651878

This paper proposes a novel short-term building load forecasting approach under the framework of patch learning, a novel data-driven model that aggregates a global model and several patch models to further reduce forecasting errors. A PL-LSTM-SVR model is hereby employed to address such a time-series based forecasting problem, where the long short-term memory network is considered as the global model and the support vector regression is selected as the patch model. To obtain satisfying performances, an infinity norm measurement is selected to evaluate load forecasting errors and identify patch locations. Furthermore, a genetic algorithm with elitist preservation strategy is introduced for hyperparameter tuning. The performances of the proposed PL-LSTM-SVR model are tested and verified on two different data sets, and compared with four advanced building load forecasting models on several common metrics. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Long short-term memory

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Vibration Error Compensation Imaging Algorithm for Arc Array SAR Besed on Parameter Estimation 6

Vibration Error Compensation Imaging Algorithm for Arc Array...

引用

6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Dong, Yifan Wu, Congfei Xu, Wei Huang, Pingping Tan, Weixian Hong, Wen College of Information Engineering Inner Mongolia University of Technology China Inner Mongolia Key Laboratory of Radar Technology and Application Hohhot China Institute of Electronics Chinese Academy of Sciences China Key Laboratory of Technology in Geospatial Information Processing and Application System Beijing China

ISBN: (纸本)9781728129129

Arc array synthetic aperture radar (SAR) is a novel array imaging system for wide-area observation, with wide observation range and high resolution. Arc array synthetic aperture radar uses W-band as carrier signal, and W-band wavelength is short. The small high-frequency vibration of the helicopter-borne platform will cause significant changes in the phase of the echo signal, which will seriously deteriorate the imaging performance of arc array synthetic aperture radar. Based on the high order approximate imaging algorithm of arc array radar, this paper proposes a vibration phase error compensation imaging algorithm based on Short-time Fourier transform (STFT) parameter estimation. The algorithm uses the high-order approximation imaging algorithm of curved array radar to perform high-order approximation of the slant range model, compensates the range cell migration (RCM) and range azimuth coupling in the two-dimensional frequency domain, and finally realizes the vibration error compensation in the range Doppler domain. The simulation results of the lattice target verify the effectiveness of the imaging method. © 2019 IEEE.

关键词： Synthetic aperture radar

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