检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Zhang, Qi Wang, Huamin Shen, Hangchi Duan, Shukai Wen, Shiping Huang, Tingwen College of Artificial Intelligence Southwest University Chongqing400715 China Chongqing Key Laboratory of Brain Inspired Computing and Intelligent Chips Chongqing400715 China College of Information Engineering University of Technology Sydney Australian Institute of Artificial Intelligence Sydney2007 Australia Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen518055 China

Recently, it can be noticed that most models based on spiking neural networks (SNNs) only use a same level temporal resolution to deal with speech classification problems, which makes these models cannot learn the information of input data at different temporal scales. Additionally, owing to the different time lengths of the data before and after the sub-modules of many models, the effective residual connections cannot be applied to optimize the training processes of these models. To solve these problems, on the one hand, we reconstruct the temporal dimension of the audio spectrum to propose a novel method named as Temporal Reconstruction (TR) by referring the hierarchical processing process of the human brain for understanding speech. Then, the reconstructed SNN model with TR can learn the information of input data at different temporal scales and model more comprehensive semantic information from audio data because it enables the networks to learn the information of input data at different temporal resolutions. On the other hand, we propose the Non-Aligned Residual (NAR) method by analyzing the audio data, which allows the residual connection can be used in two audio data with different time lengths. We have conducted plentiful experiments on the Spiking Speech Commands (SSC), the Spiking Heidelberg Digits (SHD), and the Google Speech Commands v0.02 (GSC) datasets. According to the experiment results, we have achieved the state-of-the-art (SOTA) result 81.02% on SSC for the test classification accuracy of all SNN models, and we have obtained the SOTA result 96.04% on SHD for the classification accuracy of all models. Furthermore, on the non-spiking dataset GSC, we can achieve a test classification accuracy of 95.63%, which surpasses the original baseline SNN-Delays. Meanwhile, the method proposed in this paper can speed up the model’s processing speed and reduce its energy consumption. Copyright © 2024, The Authors. All rights reserved.

关键词： Spatio-temporal data

来源：评论

学校读者我要写书评

暂无评论

ESO-Based Control for 2-D Networked Control Systems With Markov-Type DoS Attacks

引用

IEEE Transactions on Network Science and Engineering 2025年

作者： Cheng, Peng He, Shuping Xiao, Gaoxi Zhang, Weidong Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and Automation Anhui University 230601 China Anhui University National Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology School of Electrical Engineering and Automation Hefei230601 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore Shanghai Jiao Tong University Department of Automation Shanghai200240 China

This article aims to investigate the issue of the extended state observer (ESO)-based controller design for a two-dimensional (2-D) networked control system (NCS), where the communication channel suffers from Markov-type denial-of-service (DoS) attacks. The concerned system is developed by the Fornasini-Marchesini second (FMII) model. Firstly, the evolution of the DoS attacks is characterized with the help of a Markov jump process with two modes, which can eliminate the need for an explicit energy description. Moreover, a 2-D information compensation mechanism is devised, which utilizes the most recently received bidirectional signals unaffected by DoS attacks to ensure continuous input to the ESO, thereby mitigating the impact of communication interruptions. With the aid of the ESO, the developed control scheme ensures system stabilization and guarantees ultimate uniform boundedness under DoS attacks. Finally, a simulation example is conducted to validate the soundness and effectiveness of the presented control strategy, and the analysis of the Markov-type DoS attack intensity on system stability is presented as well. © 2013 IEEE.

关键词： Networked control systems

来源：评论

学校读者我要写书评

暂无评论

Diverse and High-Quality Food Image Generation from Only Food Names

引用

ACM Transactions on Multimedia computing, Communications and Applications 2025年第5期21卷

作者： Yu, Dongjian Min, Weiqing Jin, Xin Jiang, Qian Jin, Ying Jiang, Shuqiang School of Software Yunnan University Kunming China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

Food image generation holds promising application prospects in food design, advertising, and food education. However, the existing methods rely on information such as recipes, ingredients, or food names, which leads to generated food images with less intra-class diversity. When recipes, ingredients, and food names are identical for the same food, the real-world images may vary significantly in appearance. The question of how to simultaneously ensure the quality and diversity of the generated images is a key issue. To this end, we employ pre-trained diffusion model and Transformer to propose a method for generating diverse and high-quality images of both Chinese and Western food, named CW-Food. Different from previous works that utilize an overall food feature to generate new images, CW-Food first decouples the food images to obtain common intra-class features and private instance features. Additionally, we design a Transformer-based feature fusion module to integrate the common and private features, in order to avoid the shortcomings of conventional methods. Moreover, we also utilize a pre-trained diffusion model as our backbone, which is fine-tuned using LoRA with the fused multi-variate features. Extensive experiments on four datasets demonstrate the advantages of our proposed method, producing diverse and high-quality food images encompassing both Chinese and Western cuisines. To the best of our knowledge, our work is the first attempt to generate Chinese food images using only food names. © 2025 Copyright held by the owner/author(s).

关键词： Food ingredients

来源：评论

学校读者我要写书评

暂无评论

Disentangled Generation Network for Enlarged License Plate Recognition and A Unified Dataset

arXiv

引用

arXiv 2022年

作者： Li, Chenglong Yang, Xiaobin Wang, Guohao Zheng, Aihua Tan, Chang Jia, Ruoran Tang, Jin Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China iFLYTEK Co. Ltd. Hefei230088 China

License plate recognition plays a critical role in many practical applications, but license plates of large vehicles are difficult to be recognized due to the factors of low resolution, contamination, low illumination, and occlusion, to name a few. To overcome the above factors, the transportation management department generally introduces the enlarged license plate behind the rear of a vehicle. However, enlarged license plates have high diversity as they are non-standard in position, size, and style. Furthermore, the background regions contain a variety of noisy information which greatly disturbs the recognition of license plate characters. Existing works have not studied this challenging problem. In this work, we first address the enlarged license plate recognition problem and contribute a dataset containing 9342 images, which cover most of the challenges of real scenes. However, the created data are still insufficient to train deep methods of enlarged license plate recognition, and building large-scale training data is very time-consuming and high labor cost. To handle this problem, we propose a novel task-level disentanglement generation framework based on the Disentangled Generation Network (DGNet), which disentangles the generation into the text generation and background generation in an end-to-end manner to effectively ensure diversity and integrity, for robust enlarged license plate recognition. Extensive experiments on the created dataset are conducted, and we demonstrate the effectiveness of the proposed approach in three representative text recognition frameworks. © 2022, CC BY.

关键词： Optical character recognition

来源：评论

学校读者我要写书评

暂无评论

A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trends

arXiv

引用

arXiv 2023年

作者： Mei, Jiaxin Zhou, Tao Huang, Kaiwen Zhang, Yizhe Zhou, Yi Wu, Ye Fu, Huazhu Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Computer Science and Engineering Southeast University Nanjing China Institute of High Performance Computing A*STAR Singapore

Early detection and assessment of polyps play a crucial role in the prevention and treatment of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist clinicians in accurately locating and segmenting polyp regions. In the past, people often relied on manually extracted lower-level features such as color, texture, and shape, which often had problems capturing global context and lacked robustness to complex scenarios. With the advent of deep learning, more and more medical image segmentation algorithms based on deep learning networks have emerged, making significant progress in the field. This paper provides a comprehensive review of polyp segmentation algorithms. We first review some traditional algorithms based on manually extracted features and deep segmentation algorithms, and then describe benchmark datasets related to the topic. Specifically, we carry out a comprehensive evaluation of recent deep learning models and results based on polyp size, taking into account the focus of research topics and differences in network structures. Finally, we discuss the challenges of polyp segmentation and future trends in the field. Copyright © 2023, The Authors. All rights reserved.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Dual-Scale Enhanced and Cross-Generative Consistency Learning for Semi-Supervised Medical Image Segmentation

SSRN

引用

SSRN 2024年

作者： Gu, Yunqi Zhou, Tao Zhang, Yizhe Zhou, Yi He, Kelei Gong, Chen Zhu, Huafu PCA Lab The Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Information Science and Technology Nanjing210094 China School of Computer Science and Engineering Southeast University Nanjing211189 China Medical School Nanjing University National Institute of Healthcare Data Science Nanjing210023 China Institute of High Performance Computing A*STAR Singapore

Medical image segmentation plays a crucial role in computer-aided diagnosis. However, existing methods heavily rely on fully supervised training, which requires a large amount of labeled data with time-consuming pixel-wise annotations. Moreover, accurately segmenting lesions poses challenges due to variations in shape, size, and location. To address these issues, we propose a novel Dual-scale Enhanced and Cross-generative consistency learning framework for semi-supervised medical image Segmentation (DEC-Seg). First, we propose a Cross-level Feature Aggregation (CFA) module that integrates cross-level adjacent layers to enhance the feature representation ability across different resolutions. To address scale variation, we present a scale-enhanced consistency constraint, which ensures consistency in the segmentation maps generated from the same input image at different scales. This constraint helps handle variations in lesion sizes and improves the robustness of the model. Furthermore, we propose a cross-generative consistency scheme, in which the original and perturbed images can be reconstructed using cross-segmentation maps. This consistency constraint allows us to mine effective feature representations and boost the segmentation performance. To produce more accurate segmentation maps, we propose a Dual-scale Complementary Fusion (DCF) module that integrates features from two scale-specific decoders operating at different scales. Extensive experimental results on polyp segmentation from colonoscopy images, skin lesion segmentation from dermoscopic images, and Brain glioma segmentation from MRI images demonstrate the effectiveness of our DEC-Seg against other state-of-the-art semi-supervised segmentation approaches. © 2024, The Authors. All rights reserved.

关键词： Computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

An Improved Light Efficiency Led Array Design by Increasing Uniformity for Pea Sprouts

SSRN

引用

SSRN 2024年

作者： Du, Li Xu, Yang Wang, Can Chen, Yiyi Zhang, Junhua Ma, Bin Chen, Danyan School of Information and Artificial Intelligence Anhui Agricultural University Anhui Hefei230036 China School of Engineering Anhui Agricultural University Anhui Hefei230036 China Anhui Provincial Engineering Research Center for Agricultural Information Perception and Intelligent Computing Anhui China Intelligent Agriculture Research Institute Anhui Agricultural University Anhui Hefei230036 China Anhui Provincial Key Laboratory of Smart Agricultural Technology and Equipment Anhui Hefei230036 China

Light distribution is one of the important factors affecting plant growth in facility lighting. However, the traditional lighting has the problem of uneven illumination, which increases the difficulty of cultivation management and brings challenges to standardized plant production. Achieving the best light environment is of great significance to the high efficiency production. In order to effectively solve the problem of uneven distribution of light in the planting layer, this study proposes a high light efficiency LED array design by increasing uniformity based on the improved genetic algorithm. It has been verified by optical simulation, spectrometer measurement and the pea sprouts cultivation. The simulation results showed that the illumination uniformity of optimized LED array and traditional square LED array were 91.72% and 85.74% respectively. The uniformity of illuminance measured by spectrometer were 92.40% and 80.11% respectively. In addition, the effects of two LED arrays on the growth of pea sprouts were compared. The total light intensity of the optimized LED array was reduced by 20.12%, but the yield of pea sprouts increased by 8.58%. The light intensity needed to produce pea sprouts per unit mass was reduced by 26.46%, and the energy efficiency and economic efficiency were also improved. Therefore, the LED array designed based on improved genetic algorithm has high illumination uniformity and light use efficiency, and provides a new idea for pea sprout production and lighting optimization strategy. © 2024, The Authors. All rights reserved.

关键词： Light emitting diodes

来源：评论

学校读者我要写书评

暂无评论

Cell-Free Massive MIMO-OFDM for High-Speed Train Communications

arXiv

引用

arXiv 2022年

作者： Zheng, Jiakang Zhang, Jiayi Björnson, Emil Li, Zhetao Ai, Bo The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Department of Computer Science KTH Royal Institute of Technology Kista Sweden The Hunan International Scientific and Technological Cooperation Base of Intelligent Network Key Laboratory of Intelligent Computing & Information Processing Ministry of Education Xiangtan University Hunan411105 China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China

Cell-free (CF) massive multiple-input multiple-output (MIMO) systems show great potentials in low-mobility scenarios, due to cell boundary disappearance and strong macro diversity. However, the great Doppler frequency offset (DFO) leads to serious inter-carrier interference in orthogonal frequency division multiplexing (OFDM) technology, which makes it difficult to provide high-quality transmissions for both high-speed train (HST) operation control systems and passengers. In this paper, we focus on the performance of CF massive MIMO-OFDM systems with both fully centralized and local minimum mean square error (MMSE) combining in HST communications. Considering the local maximum ratio (MR) combining, the large-scale fading decoding (LSFD) cooperation and the practical effect of DFO on system performance, exact closed-form expressions for uplink spectral efficiency (SE) expressions are derived. We observe that cooperative MMSE combining achieves better SE performance than uncooperative MR combining. In addition, HST communications with small cell and cellular massive MIMO-OFDM systems are compared in terms of SE. Numerical results reveal that the CF massive MIMO-OFDM system achieves a larger and more uniform SE than the other systems. Finally, the train antenna centric (TA-centric) CF massive MIMO-OFDM system is designed for practical implementation in HST communications, and three power control schemes are adopted to optimize the propagation of TAs for reducing the impact of the DFO. Copyright © 2022, The Authors. All rights reserved.

关键词： MIMO systems

来源：评论

学校读者我要写书评

暂无评论

Fine-grained pseudo-code generation method via code feature extraction and transformer

arXiv

引用

arXiv 2021年

作者： Yang, Guang Zhou, Yanlin Chen, Xiang Yu, Chi School of Information Science and Technology Nantong University China Ministry of Industry and Information Technology China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University China

Pseudo-code written by natural language is helpful for novice developers’ program comprehension. However, writing such pseudo-code is time-consuming and laborious. Motivated by the research advancements of sequence-to-sequence learning and code semantic learning, we propose a novel deep pseudo-code generation method DeepPseudo via code feature extraction and Transformer. In particular, DeepPseudo utilizes a Transformer encoder to perform encoding for source code and then use a code feature extractor to learn the knowledge of local features. Finally, it uses a pseudo-code generator to perform decoding, which can generate the corresponding pseudo-code. We choose two corpora (i.e., Django and SPoC) from real-world large-scale projects as our empirical subjects. We first compare DeepPseudo with seven state-of-the-art baselines from pseudo-code generation and neural machine translation domains in terms of four performance measures. Results show the competitiveness of DeepPseudo. Moreover, we also analyze the rationality of the component settings in DeepPseudo. Copyright © 2021, The Authors. All rights reserved.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Asynchronous Tag-based Physical-Layer Authentication in Wireless Communications

引用

IEEE Transactions on Wireless Communications 2025年

作者： Tan, Haijun Xu, Yuntao Du, Jiewei Xie, Ning Li, Hongbin Peng Cheng Laboratory Control and Network Foundation Laboratory Frontier Research Center Shenzhen518107 China Shenzhen University State Key Laboratory of Radio Frequency Heterogeneous Integration The Guangdong Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen518060 China Beijing Jiaotong University School of Electronic and Information Engineering Beijing100044 China National Innovation Center of High Speed Train Qingdao266111 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

Tag-based physical-layer authentication (PLA) has gained significant research interest due to its high security and low complexity compared to traditional upper-layer authentication mechanisms. However, conventional tag-based PLA schemes often require strict synchronization between the tag and the source message before transmission, which may limit their practicality and effectiveness. To address this limitation, we propose an asynchronous tag-based PLA scheme, where the tag and the source message are transmitted asynchronously with an intentional time delay introduced at the transmitter. The proposed scheme enhances both compatibility and security without compromising robustness. We provide a theoretical analysis of the proposed scheme, and derive closed-form expressions to characterize its performance. Furthermore, theoretical comparisons with existing methods yield insightful conclusions regarding the advantages of the proposed approach. The scheme is implemented and extensively evaluated through simulations, where the theoretical results exhibit strong agreement with the simulation outcomes, thereby validating its effectiveness. © 2025 IEEE.

关键词： asynchronous closed form intentional timing delay Physical-layer authentication tag-based

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：