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2024 International Conference on Image processing and Artificial Intelligence, ICIPAl 2024

作者： Xie, Ruidong Zhang, Zheqi Zhu, Pei Ma, Wenle Yi, Yingmin Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

ISBN: (纸本)9781510681514

A multi-level feature weighted fusion based image classification method for silicon single crystal growth process has been proposed to address the issue of the long silicon single crystal pulling times at industrial sites, which prevents timely understanding of the crystal growth process. A multi-level feature weighted fusion method was employed to identify and classify the growth process of silicon single crystals. A Czochralski single crystal silicon growth process recognition system was then designed. A comparison of the experimental results obtained from this design with the traditional single image classification method clearly showed that using different levels of silicon single crystal image information simultaneously effectively improved the accuracy of silicon single crystal growth image classification. © 2024 SPIE.

关键词： Image classification

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Keycap character detection model based on target classification 7

Keycap character detection model based on target classificat...

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2024 7th International Conference on intelligent Manufacturing and Automation, IMA 2024

作者： Xiong, Taiping Zhu, Zhiguo Wang, Tinghao School of Computer and Information Security Guilin University of Electronic Technology Guangxi Guilin541004 China Key Laboratory of Image Graphics and Intelligent Processing in Guangxi Guilin University of Electronic Technology Guangxi Guilin541004 China

The production process of keycaps may result in surface character defects. The existing keycap character defect detection technology has low efficiency and accuracy, hindering the automation of keycap manufacturing. Addressing the challenge of extracting the entire keyboard from illuminated regions, this paper proposes a method using image feature points for template matching to extract the region of interest. Subsequently, leveraging prior knowledge, the paper addresses character segmentation and extraction on the keyboard. For character detection, the paper preprocesses images and classifies them by using an S-VGG network, yielding corresponding labels. © Published under licence by IOP Publishing Ltd.

关键词： Template matching

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Research on financial social public opinion communication model based on variation mechanism 6

Research on financial social public opinion communication mo...

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6th International Conference on Electronic information technology and Computer Engineering, EITCE 2022

作者： Huang, Maojun Hong, Mei Dong, Lin Yuan, Da Key Laboratory of Intelligent Information Processing Shandong Technology and Business University Shandong Yantai264005 China

ISBN: (纸本)9781450397148

In the context of rapid development of the Internet, the place of spreading financial public opinion is converted from traditional offline places to major online social platforms. Mastering the development mechanism of financial social opinion dissemination on online social media can effectively estimate the length of influence of public opinion and the scope of affected people, and provide effective guidance to relevant staff. Based on the Susceptible Infected Recovered Model, this paper divides the people involved in opinion diffusion into commenters and discussers, and introduces the variation mechanism to design the Susceptible-comment-discussion-removal model, then simulates the model to study the effects of different initial states and parameters on the model, and finally verifies the validity of the model by combining the real data of stock bars. The simulation experiments and validation show that the model can effectively describe the spread of public opinion among the user groups of financial social platforms when it occurs, and provide a valid reference for related workers. However, the content of public opinion, the personal influence of communicators, and the lag effect of communication all have an impact on communication, and these issues need to be addressed in future research. © 2022 Association for Computing Machinery.

关键词： Social aspects

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Infrared ship target detection method under complex sea background conditions

Infrared ship target detection method under complex sea back...

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2024 Applied Optics and Photonics China: Optical Sensing, Imaging technology, and Applications, AOPC 2024

作者： Chuangang, Xu Yuexing, Wang Tian, Tian Tianjin Jinhang Institute of Technical Physics Tianjin300308 China National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9781510687820

ISBN: (纸本)9781510687813

In complex sea environments, the signal-to-noise ratio and contrast of infrared images constantly change due to factors such as wave motion, wave reflection, changes in solar altitude angle, target distance, and uneven distribution of thermal radiation, resulting in missed and false detections in infrared ship detection. In the image, ship targets are generally present in the vicinity of the sea antenna. Therefore, by determining the position of the sea sky line, the approximate area of the ship target in the image can be determined, thereby suppressing possible interference from unrelated objects in the sky and sea outside this range and reducing the probability of false detection of infrared ship targets. And in order to solve the possible interference effects of sea clutter and clouds in traditional sea antenna extraction methods, this paper proposes a sea antenna difference extraction algorithm. By enhancing the gray vertical gradient difference between rows, the sea antenna is extracted. Compared with other typical sea antenna extraction algorithms, the accuracy of the sea antenna extraction method in this paper is improved by 7.2%. The infrared image of ships has significant noise, which is affected by the attenuation of atmospheric transmission over long distances on the sea surface. The contrast of ship targets is low, making it difficult to directly extract ship features;Moreover, the infrared imaging of ship targets is greatly affected by factors such as season, weather, and lighting, especially in harsh weather conditions such as clouds, rain, and snow, which can seriously affect the imaging effect and make the infrared images of ships blurry. Therefore, in order to effectively achieve the detection and recognition of ship targets, this paper preprocesses the infrared images of ships before detection. An improved inverse harmonic filtering algorithm is proposed, which first adopts a gradient enhancement strategy, and then eliminates the bright spot interf

关键词： Submarine geophysics

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Feature Attention Complex-Valued-Based CNN for Ship Target Recognition of SAR Images 2

Feature Attention Complex-Valued-Based CNN for Ship Target R...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Pan, Hongxin Yang, Chao Yin, Yifei Liang, Bin Shi, Hao Wu, Guanghui Beijing Institute of Technology Chongqing Innovation Center Chongqing China Shanghai Institute of Satellite Engineering Shanghai China Beijing Institute of Technology National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing China

ISBN: (纸本)9798331515669

The details regarding targets within Synthetic Aperture Radar (SAR) imagery are typically conveyed and maintained in complex-valued form. Namely, the information regarding both the amplitude and phase is essential. In the process of recognizing targets with SAR, the network only utilizes the amplitude image as input, while the phase information is neglected, resulting in poor recognition performance. This paper proposes a Feature Attention Complex-Valued-Based convolutional neural Network (FACV-Net) for SAR ship recognition to overcome these issues, which effectively utilizes phase information to improve target recognition. Firstly, to meet the requirements of network training in complex domains, a series of complex-valued operation blocks have been constructed. Moreover, a new complex-valued Attention Module (CAM) is introduced to ensure that the network focuses on the amplitude and phase characteristics of the target separately. Additionally, to address the mismatch problem between the amplitude and phase data, two distinct methods for complex-valued max-pooling are utilized. Ultimately, the performance of the proposed FACV-Net is assessed using the OpenSARship dataset, and the results indicate that this novel approach surpasses conventional networks in terms of recognition accuracy. When the CAM is added, the performance of the network sees a further enhancement of around 3% in accuracy. These findings confirm the proposed method's effectiveness and advantage over others. © 2024 IEEE.

关键词： Cams

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FUZZY ALIGNMENTS IN DIRECTED ACYCLIC GRAPH FOR NON-AUTOREGRESSIVE MACHINE TRANSLATION 11

FUZZY ALIGNMENTS IN DIRECTED ACYCLIC GRAPH FOR NON-AUTOREGRE...

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11th International Conference on Learning Representations, ICLR 2023

作者： Ma, Zhengrui Shao, Chenze Gui, Shangtong Zhang, Min Feng, Yang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Harbin Institute of Technology Shenzhen China

Non-autoregressive translation (NAT) reduces the decoding latency but suffers from performance degradation due to the multi-modality problem. Recently, the structure of directed acyclic graph has achieved great success in NAT, which tackles the multi-modality problem by introducing dependency between vertices. However, training it with negative log-likelihood loss implicitly requires a strict alignment between reference tokens and vertices, weakening its ability to handle multiple translation modalities. In this paper, we hold the view that all paths in the graph are fuzzily aligned with the reference sentence. We do not require the exact alignment but train the model to maximize a fuzzy alignment score between the graph and reference, which takes captured translations in all modalities into account. Extensive experiments on major WMT benchmarks show that our method substantially improves translation performance and increases prediction confidence, setting a new state of the art for NAT on the raw training data. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Benchmarking

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Transmission and Reception of 17×480 Gbit/s PDM-16QAM with Tx/Rx I/Q Imbalance Compensation and Simplified MLSE for Metro-Regional 400G Optical Communications

Transmission and Reception of 17×480 Gbit/s PDM-16QAM with ...

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2023 Optical Fiber Communications Conference and Exhibition, OFC 2023

作者： Li, Fan Zou, Dongdong Ni, Weihao Chen, Zhiwei Yi, Xingwen Li, Zhaohui Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems School of Electronics and Information Technology Sun Yat-Sen University Guangzhou China Zhuhai China

ISBN: (纸本)9781957171180

We experimentally demonstrate a single-carrier 400G Metro/regional communications based on 60-GBaud PDM-16QAM over 430-km SMF-28. Joint GPD and GSOP and 4×4 MIMO LMS equalizer are adopted to compensate Rx/Tx I/Q imbalance, and simplified MLSE with 99.61% computational complexity reduction is employed to mitigate channel bandwidth constraint. © 2023 The Author(s).

关键词： Pulse width modulation

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Simultaneous segmentation and classification of colon cancer polyp images using a dual branch multi-task learning network

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Mathematical Biosciences and Engineering 2024年第2期21卷 2024-2049页

作者： Li, Chenqian Liu, Jun Tang, Jinshan School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan430065 China Department of Health Administration and Policy College of Public Health George Mason University FairfaxVA22030 United States

Accurate classification and segmentation of polyps are two important tasks in the diagnosis and treatment of colorectal cancers. Existing models perform segmentation and classification separately and do not fully make use of the correlation between the two tasks. Furthermore, polyps exhibit random regions and varying shapes and sizes, and they often share similar boundaries and backgrounds. However, existing models fail to consider these factors and thus are not robust because of their inherent limitations. To address these issues, we developed a multi-task network that performs both segmentation and classification simultaneously and can cope with the aforementioned factors effectively. Our proposed network possesses a dual-branch structure, comprising a transformer branch and a convolutional neural network (CNN) branch. This approach enhances local details within the global representation, improving both local feature awareness and global contextual understanding, thus contributing to the improved preservation of polyp-related information. Additionally, we have designed a feature interaction module (FIM) aimed at bridging the semantic gap between the two branches and facilitating the integration of diverse semantic information from both branches. This integration enables the full capture of global context information and local details related to polyps. To prevent the loss of edge detail information crucial for polyp identification, we have introduced a reverse attention boundary enhancement (RABE) module to gradually enhance edge structures and detailed information within polyp regions. Finally, we conducted extensive experiments on five publicly available datasets to evaluate the performance of our method in both polyp segmentation and classification tasks. The experimental results confirm that our proposed method outperforms other state-of-the-art methods. ©2024 the Author(s), licensee AIMS Press.

关键词： Classification (of information)

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USV Path Planning Based on ACO-SA Algorithm 42

USV Path Planning Based on ACO-SA Algorithm

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42nd Chinese Control Conference, CCC 2023

作者： Luo, Chuanshang Tang, Yifeng Huang, Zhihui Xu, Yifan Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

This paper solves USV path planning problem constrained by multiple factors via ant-colony optimization algorithm. First, this paper uses the ways of multi-objective optimization to model the USV path planning problem. An improved ant colony algorithm named ACO-SA is put forward afterwards to effectively solve the problem. The algorithm is a combination of ACO algorithm(ant colony algorithm) and SA algorithm(simulated annealing algorithm), which has three improments: change the initial distribution of pheromone to guide the search when the algorithm has just started running;change the heuristic function and state transition probability taking three factors into consideration;change the pheromone update rule and make the ants compete for the right to update pheromone by simulated annealing algorithm, and update the best solution by the same algorithm. Finally, simulation experiment and field experiment are conducted to check the validity of ACO-SA algorithm. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Simulated annealing

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Polynomial stacked-attention network for nationality classification

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Frontiers of Computer Science 2022年第4期16卷 215-217页

作者： Kunyan Li Jie Zhang Shiguang Shan Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing100190China University of Chinese Academy of Sciences Beijing100049China

1Introduction In recent years,nationality and region inference has atracted more and_more *** anthropological researches indicate that human faces are influenced by genes,and other external factors,e.g-,geographical environment[1].This relevance provides possible solutions for geographical area inference by ***,it remains a challenging task due to the tiny differences on faces for various countries,which is even hard for human beings to tell.

关键词： Polynomial s. network

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