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International Conference on Wireless communications and Signal processing (WCSP)

作者： Peiqing Bai Ziguan Cui Zongliang Gan Guijin Tang Feng Liu Image Processing & Image Communication Lab Nanjing University of Posts & Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts & Telecommunications Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9781509028610

Visually salient object or region detection in images is an active research field in recent years. Inspired by that curvelets can provide multi-scale sparse representation of objects with edges and textures, in this paper, we propose a novel saliency detection model based on fast discrete curvelet transform (SDCT) to detect more compact salient objects in an image. First, fast discrete curvelet transform is used to acquire multi-scale representation of feature maps in CIELab color space. Then the feature maps are transformed to feature salient maps based on dissimilarity measure between patches in a global manner. Finally, the complementary feature salient maps at each scale and each color channel are merged linearly to obtain unitary saliency map. Experimental results on MSRA saliency benchmark database show that the proposed SDCT model outperforms the most state-of-the-art saliency detection models in spatial and frequency domain with higher overall performance, especially acquires more compact salient object and suppresses background saliency effectively, which is desirable for many computer vision applications.

关键词： Transforms Feature extraction image color analysis Frequency-domain analysis Computational modeling Visualization image edge detection

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Extended State Observer Based Fault-Tolerant Predictive Control for a Four-Mecanum Wheels Mobile Robot 14

Extended State Observer Based Fault-Tolerant Predictive Cont...

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14th IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, CYBER 2024

作者： Yang, Binghao Wang, Dongliang Wen, Ziling Wei, Wu Li, Wenji Fan, Zhun Shantou University Key Lab of Digital Signal and Image Processing of Guangdong Province Guangdong 515063 China Shantou University School of Department of Electronic and Information Engineering Guangdong 515063 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangdong Guangzhou510640 China School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou510641 China

ISBN: (纸本)9798331506056

The application of unmanned vehicles in industrial cargo transportation is becoming increasingly widespread, particularly playing a significant role in transporting heavy-duty goods. However, when performing such tasks, whether in single-vehicle transportation or multi-vehicle collaborative transportation, the occurrence of wheel failures can potentially lead to serious safety accidents. Therefore, this paper proposes a fault-tolerant control scheme, establishing a kinematic model considering disturbances and failures, and adopts model predictive control for trajectory tracking. Additionally, an extended state observer is introduced to observe system states and counteract disturbances. To address potential failure issues, a controller reconstruction strategy is proposed. Finally, the effectiveness and superiority of the controller is validated through numerical simulation and comparative experiment. © 2024 IEEE.

关键词： Mobile robots

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An Activity-List based Nested Partitions algorithm for Resource-Constrained Project Scheduling

An Activity-List based Nested Partitions algorithm for Resou...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Lei Xiao Jing Tian Zhenyuan Liu School of Automation Huazhong University of Science and Technology Wuhan Hubei Province China Key Laboratory of Education Ministry for Image Processing and Intelligent Control University of Science and Technology Wuhan Hubei Province China

In this paper, we propose an Activity-List based Nested Partitions algorithm for solving the Resource-Constrained Project Scheduling Problem(RCPSP). This algorithm is based on traditional Serial Scheduling scheme (SSS) and partitions the feasible solution space which is formulated by activity-lists into subregions by the nested partitions approach. We also utilize Double Justification as local search to improve the solutions. The algorithm is tested on J120 in PSPLIB with the result that the algorithm is relatively effective for solving large-scale, complex RCPSPs.

关键词： Partitioning algorithms Algorithm design and analysis Heuristic algorithms Job shop scheduling Educational institutions Processor scheduling

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Hydrostatic Pressure Responsive Mechanism for Room Temperature Phosphorescence: A Theoretical Perspective

SSRN

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SSRN 2023年

作者： Wang, Yan Han, Shulin Mu, Qingfang Liu, Huanling Chuankui, Wang Fan, Jianzhong Shandong Province Key Laboratory of Medical Physics and Image Processing Technology Institute of Materials and Clean Energy School of Physics and Electronics Shandong Normal University Jinan250014 China

Stimulus-responsive organic room temperature phosphorescence (RTP) materials are a class of materials that show emission property changes (color, efficiency and lifetime) when subjected to diverse environmental stimuli including light, temperature, force, electricity, etc. The change of molecular stacking modes and intermolecular interactions can result in mechanical stimulus-induced emission switching behavior. Most of reported mechanical luminescent molecules show red-shifted emission under the action of mechanical stress such as pressure and grinding, but rarely show blue-shifted emission phenomenon. The underlying mechanism of this abnormal mechanoresponsive luminescent material is still unclear. Herein, based on density functional theory (DFT) and time-dependent density functional theory (TD-DFT) calculations, the photophysical properties with response to hydrostatic pressure of RTP molecules in crystal are theoretically studied. The excited state dynamic processes are investigated by using quantum mechanics and molecular mechanics (QM/MM) method coupled with thermal vibration correlation function (TVCF) method. Huang-Rhys factors and reorganization energies are analyzed, and natural atomic orbital is used to calculate the orbital information of the excited states. Furthermore, intermolecular interactions are visualized using independent gradient model based on Hirshfeld partition (IGMH) and quantitatively measured by the molecular force field energy decomposition method. Based on these methods, we focus on the effects of hydrostatic pressure induced molecular conformational transformations, the changes of intermolecular interactions and charge-transfer characteristics on the emission wavelengths, efficiencies and lifetimes under stimulation. Results show that the increase of pressure can blue-shift the RTP emissions which is mainly caused by the change of molecular conformation and the increase of bending vibration frequency. Under 2 Gpa, large spin-orbit coup

关键词： Quantum theory

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A directional-progressive search method for infrared small target detection 3

A directional-progressive search method for infrared small t...

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3rd Optoelectronics Global Conference, OGC 2018

作者： Zhang, Xiangyue Ding, Qinghai Luo, Haibo Hui, Bin Chang, Zheng Zhang, Junchao Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Opto-Electronic Information Processing CAS Shenyang110016 China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China Space Star Technology Co. Ltd Beijing100086 China

ISBN: (纸本)9781538673973

Infrared small target detection plays a key role in infrared precision guidance and infrared early-warning system. It has been a difficult problem for researchers to study on how to detect targets accurately at a long distance as early as possible. Most of the existing algorithms can detect small targets in simple backgrounds, but they would fail on the detection when the background clutters are chaotic and the signal to clutter ratio (SCR) is low. Therefore, we propose a new infrared small target detection method which called a directional-progressive search (DPS) method. Our method derives from a fact that a small target is an isotropic Gaussian distribution at a long distance, while clutters show different characteristics in different directions. Based on this difference, we decompose the original image into first-order sub-images with different directions by using a first-order directional derivative (FODD) filter. Then zero-crossing points are detected in each direction step by step to distinguish small targets and background clutters. After screening progressively, the positions where existing zero-crossing points in every sub-image can be confirmed as targets. Experimental results show that our method acquires higher detection rates and lower false alarm rates compared with other methods. At the same time, our method can still keep better performance under various complex backgrounds. The robustness of our method is strong. © 2018 IEEE.

关键词： Clutter (information theory)

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Speech Stuttering Detection and Removal Using Deep Neural Networks 11th

Speech Stuttering Detection and Removal Using Deep Neural Ne...

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11th International Conference on Computer Engineering and Networks, CENet2021

作者： Rajput, Shaswat Nersisson, Ruban Raj, Alex Noel Joseph Mary Mekala, A. Frolova, Olga Lyakso, Elena School of Electrical Engineering Vellore Institute of Technology Vellore India Key Laboratory of Digital Signal and Image Processing of Guangdong Province Department of Electronic Engineering College of Engineering Shantou University Shantou China School of Information Technology and Engineering Vellore Institute of Technology Vellore India St. Petersburg State University Saint Petersburg Russia

ISBN: (纸本)9789811665530

There are more than 70 million people worldwide who suffer from stuttering problems. This will affect the confidence of public speaking in people who suffer from this issue. To solve this problem many people take therapy sessions but the therapy sessions are a temporary solution, as soon as they leave therapy sessions this problem might arise again. This work aims to use state of the art machine learning algorithms that have improved over the past few years to solve this problem. We have used the dataset from UCLASS archives which provide the data for stuttered speech *** format with time-aligned transcriptions. We have tried different algorithms and optimized our model by hyper parameter tuning to maximize the model’s accuracy. The algorithm is tested on random speech data with low to heavy stuttering from the same dataset, and it is observed that there is significant reduction in the Word Error Rate (WER) for most of the test cases. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Learning algorithms

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Interpolating fine texturess with fields of experts prior

Interpolating fine texturess with fields of experts prior

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IEEE International Conference on image processing

作者： Kai Guo Xiaokang Yang Rui Zhang Songyu Yu Hongyuan Zha Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai Jiaotong University Shanghai China College of Computing Georgia Institute of Technology Atlanta GA USA

Traditional image interpolation methods assume that the local spatial structure of the low-resolution (LR) and high-resolution (HR) images are approximately the same, and use edge information of the LR image to estimate the missing pixels. This assumption, however, no longer holds for natural images with fine and dense textures. Consequently, those methods cannot restore dense textures well and tend to generate over-fitting visual effects. In this paper, a learned HR image prior is exploited to overcome the problems. In particular, we use Fields of Experts (FoE) with student's t-distribution experts to model the prior, taking advantage of its representative ability of non-Gaussian natures in images. Then Maximum a Posterior (MAP) estimation incorporating FoE prior is used to estimate the missing pixels. Experimental results compared with traditional interpolation methods demonstrate that our method not only can recover fine details and produce superior PSNR values, but also avoid the visual over-fitting problems.

关键词： Interpolation Pixel image restoration Visual effects PSNR Layout image resolution image communication Information processing Biometrics

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CNN based Emotion Detection in Cross Linguistic Children speech 24

CNN based Emotion Detection in Cross Linguistic Children spe...

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24th International Congress on Acoustics, ICA 2022

作者： Lyakso, Elena Frolova, Olga Ruban, Nersisson Mekala, A. Mary Joseph Raj, Alex Noel Matveev, Anton Matveev, Yuri The Child Speech Research Group St. Petersburg State University St. Petersburg Russia School of Electrical Engineering VIT Vellore India School of Information Technology & Engineering VIT Vellore India Key Laboratory of Digital Signal and Image Processing of Guangdong Province Department of Electronics Engineering College of Engineering Shantou University China

The goal of this cross-linguistic study is to analyze the speech of children in the age group of 8-12 years and automatic classification of children's emotions from various speech data in Russian and Tamil languages. A standardized approach for the collection of speech (spontaneous and acting speech - emotional words, phrases, and meaningless texts) was used. Two emotional child speech corpora include the emotional speech of 95 Russian children and 40 Indian children were created. Annotation of the emotional speech was carried out in four categories "joy - neutral - sadness – anger" by two speech specialists of the same nationality of the child. The set of 2505 labeled audio files of Russian children and 418 labeled audio files of Tamil children were used. The SVM classifier shows slightly better results in Russian language, and the MLP classifier in Tamil. Inter-Cultural approach (mixed dataset of Russian and Indian speech) revealed that the accuracy of recognition of all emotions remains higher. In Cross-Cultural approach, on samples of Tamil speech, anger state is recognized better, and in samples of Russian speech – sad state. Using 5 Layered CNN Model, the accuracy was revealed for Russian speech is higher than for Indian children. © 2022 Proceedings of the International Congress on Acoustics. All rights reserved.

关键词： Emotion Recognition

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Fast Mode Decision for H.264 Video Encoder Based on MB Motion Characteristic

Fast Mode Decision for H.264 Video Encoder Based on MB Motio...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiangwen Wang Jun Sun Yunqiang Liu Renjie Li Institute of Image Communication & Information Processing Shanghai China Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Shanghai China Philips Research East Asia Shanghai China

Seven variable block sizes are adopted for inter-frame MB (macroblock) coding in H.264. This new feature achieves significant coding gain. However, the computation complexity of the mode decision is extremely high when RD (rate distortion) algorithm is used. In this paper, we propose a fast mode decision algorithm with fast coding block size selection based on MB motion characteristic for inter frames. In this algorithm, the residual_MB is first gotten through motion estimation for the MB. Then, the motion characteristic of the MB is extracted through careful analysis of the texture in the residual_MB. At last, the optimization mode for the MB is decided according to the motion characteristic. Experimental results show that the mode decision can save significantly computational complexity at cost of a little degradation of RD performance.

关键词： Motion estimation Rate-distortion Motion analysis Algorithm design and analysis Computational complexity Sun image communication Information processing Laboratories Asia

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Characterizing Excited States of Single Donor-Acceptor Molecule by High-Resolution Raman images

SSRN

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SSRN 2022年

作者： Chu, Dingwei Yu, Haizhen Wang, Li Wang, Chuan-Kui Song, Yuzhi Xie, Zhen Shandong Province Key Laboratory of Medical Physics and Image Processing Technology Institute of Materials and Clean Energy School of Physics and Electronics Shandong Normal University Jinan250014 China

The excited states of charge transfer (CT), local donor (LD) and local acceptor (LA) for donor-acceptor molecules play an important role in many applications. However, these excited quantum states are still impossible to be characterized by conventional experimental techniques. Optical spectroscopy with the supplement of density functional theory calculations is widely adopted to investigate excited states, but is often inefficient for the donor-acceptor molecule owing to substantial errors of functionals in describing CT states. Our calculations show that the resonance tip-enhanced Raman scattering images that utilizes the confined plasmonic field for CT, LD and LA states possess their exclusive imaging characterizations, giving unambiguous identification of different excited-state properties. In addition, the resonance Raman images provide a benchmark to reasonably estimate the accuracy of different functionals in describing excited states of the charge-transfer system. These findings extend the emerging Raman images to the characterization and improvement of functional donor-acceptor molecular materials. © 2022, The Authors. All rights reserved.

关键词： Density functional theory

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