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8th International Conference on Control, Robotics and Cybernetics, CRC 2023

作者： Feng, Chao Jia, Zhiwei Zhang, Wupeng Changsha University of Science and Technology School of Electrical and Infomation Engineering Changsha China

ISBN: (纸本)9798350330588

Structured scenes are characterized by complex road conditions and poor GPS signals, and map degradation and degradation of positioning accuracy often occur when robots build maps of structured scenes. Aiming at the above problems, a low-cost multi-sensor-periodize fusion SLAM system is designed, which fuses four low-cost sensors, namely, 2D LIDAR, RBGD camera, inertial measurement unit, and wheel odometer. A sub-echelon data processing session is designed in the motion initialization session, and a sensor multi-strategy selection method is designed in the optimization and alignment session to maintain the robustness of map building and localization with less computational effort for optimization. Compared with the traditional method, it can improve the positioning accuracy and constrain the map degradation rate to less than 5%, which substantially improves the value of practical engineering applications while meeting the requirements. © 2024 IEEE.

关键词： Degradation

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GMTS: GNN-based multi-scale transformer siamese network for remote sensing building change detection

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International Journal of Digital Earth 2023年第1期16卷 1685-1706页

作者： Xinyang Song Zhen Hua Jinjiang Li School of Infomation and electronic engineering Shandong Technology and Business UniversityInstitute of Network Technology(ICT)YantaiPeople's Republic of China School of Computer Science and Technology Shandong Technology and Business UniversityYantaiPeople's Republic of China

With the remarkable success of change detection(CD)in remote sensing images in the context of deep learning,many convolutional neural network(CNN)based methods have been *** the current research,to obtain a better context modeling method for remote sensing images and to capture more spatiotemporal characteristics,several attention-based methods and transformer(TR)-based methods have been *** research has also continued to innovate on TR-based methods,and many new methods have been *** of them require a huge number of calculation to achieve good ***,using the TR-based mehtod while maintaining the overhead low is a problem to be ***,we propose a GNN-based multi-scale transformer siamese network for remote sensing image change detection(GMTS)that maintains a low network overhead while effectively modeling context in the spatiotemporal *** also design a novel hybrid backbone to extract *** with the current CNN backbone,our backbone network has a lower overhead and achieves better ***,we use high/low frequency(HiLo)attention to extract more detailed local features and the multi-scale pooling pyramid transformer(MPPT)module to focus on more global features ***,we leverage the context modeling capabilities of TR in the spatiotemporal domain to optimize the extracted *** have a relatively low number of parameters compared to that required by current TR-based methods and achieve a good effect improvement,which provides a good balance between efficiency and performance.

关键词： Remote sensing(RS) change detection(CD) depthwise over-parameterized convolutional(DO-Conv) attention mechanism transformer graph convolution

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Path Planning Considering Energy Consumption of Crawler Robots in Mountain Environments

Path Planning Considering Energy Consumption of Crawler Robo...

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2024 IEEE/SICE International Symposium on System Integration, SII 2024

作者： Adachi, N. Date, H. Graduate School of Science and Technology Programs in Systems and Infomation Engineering University of Tsukuba Ibaraki Tsukuba3058577 Japan

ISBN: (纸本)9798350312072

In the forestry industry, the demand for task automation is increasing to solve the labor shortage problem. We examine the path planning problem for tasks such as afforestation, harvesting, and surveying, in which a robot travels a predetermined set of locations. We specifically address the problem of path planning for minimization of energy consumption for the operation of a crawler robot in an environment with slopes. This problem requires consideration of the energy loss caused by ascending and descending in the mountainous environment, besides the energy loss due to friction during on-the-spot rotation specific to the crawler robot, and is impossible to treat as the standard Traveling Salesman Problem(TSP). We apply the Generalized Traveling Salesman Problem (GTSP) known as the TSP extension to this problem. This allows the proposed method to account for energy consumption during movement. We modeled the energy consumption of the robot during straight movements and rotations through a preliminary experiment. A graph reflecting the energy consumption model can be generated for evaluation of the path planning by setting the points to be traversed on the point cloud map after 3D scanning of an outdoor unstructured terrain field with flat ground and sloped ground. It is confirmed that the proposed method can plan a path that reduces energy consumption by 22% for a standard TSP solution that quasi-minimizes Euclidean distance. © 2024 IEEE.

关键词： Motion planning

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Design of Dual-Function Radar Communication System Based on Delayed Jump Mapping LFM 8

Design of Dual-Function Radar Communication System Based on ...

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8th International Conference on Signal and Image Processing, ICSIP 2023

作者： Xu, Rui Wen, Ruiming Huang, Zihan Li, Gang Wen, Guangjun University of Electronic Science and Technology of China School of Information and Communication Engineering China University of Electronic Science and Technology of China School of Infomation and Software Engineering China

ISBN: (纸本)9798350397932

The deterioration of dual-function performance and increased complexity of communication receivers challenge the efficiency of dual-functional radar-communication (DFRC) system based on linear frequency modulation (LFM). This paper designs a delayed jump mapping LFM (DJM-LFM) waveform-based DFRC system. The frequency delay jumps are generated at the specific points in the LFM cycle to modulate data. After carrier mixing and undersampling, the communication receiver realizes dechirp in the digital domain, to reduce the performance requirements of the coherent signal generation and sampling. In the radar processing link, we propose the breakpoint area deletion and concatenation (BADC) scheme, making the radar performance of DFRC consistent with that of unmodulated frequency modulated continuous wave radar (FMCW). The simulation results show that, compared with the scheme without compensation, the BADC scheme reduces the sidelobe amplitude of the range domain profile by about 38 dB. DJM-LFM reduces the symbol error rate of 2 dB compared with existing DFRC schemes based on the LFM waveform. © 2023 IEEE.

关键词： Deterioration

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Fruit Image Classification Based on ResNet50 and Transfer Learning 4

Fruit Image Classification Based on ResNet50 and Transfer Le...

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4th International Conference on Computer Vision and Data Mining, ICCVDM 2023

作者： Lin, Hao Yu, Liuming Wan, Mengsha Chen, Xiaolin Wang, Chunlin School of Informatics Yunnan Normal University Kunming650000 China School of Information Science Technology Chuxiong Normal University Chuxiong China School of education China West Normal University Nanchong637000 China School of Infomation Science and Technology Qiongtai Normal University Hainan Haikou571127 China

ISBN: (纸本)9781510674448

Developing the cash crop industry and helping rural revitalization is China's long-term development plan, applying image recognition technology to the field of cash crops, and efficiently realizing the picking and classification of crops. In this paper, three transfer learning methods are used to compare the transfer learning effects of AlexNet, VGG16, ResNet50 and other networks to select the most suitable model for fruit classification. ResNet50 migration training fully connected models can not only shorten the training time, but also achieve higher accuracy under the same iteration cycle. The accuracy of ResNet50 migration training fully connected layer model is 97%. The accuracy rate is improved by 17% compared to VGG13. © 2024 SPIE.

关键词： Fruits

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Hypernetwork-Assisted Parameter-Efficient Fine-Tuning with Meta-Knowledge Distillation for Domain Knowledge Disentanglement

Hypernetwork-Assisted Parameter-Efficient Fine-Tuning with M...

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2024 Findings of the Association for Computational Linguistics: NAACL 2024

作者： Li, Changqun Wang, Linlin Lin, Xin Huang, Shizhou He, Liang School of Computer Science and Technology East China Normal University China Shanghai Key Laboraiory of Multdimensional Infomation Procesing China Shanghai Artificial Intelligence Laboratory China

ISBN: (纸本)9798891761193

Domain adaptation from labeled source domains to the target domain is important in practical summarization scenarios. However, the key challenge is domain knowledge disentanglement. In this work, we explore how to disentangle domain-invariant knowledge from source domains while learning specific knowledge of the target domain. Specifically, we propose a hypernetwork-assisted encoder-decoder architecture with parameter-efficient fine-tuning. It leverages a hypernetwork instruction learning module to generate domain-specific parameters from the encoded inputs accompanied by task-related instruction. Further, to better disentangle and transfer knowledge from source domains to the target domain, we introduce a meta-knowledge distillation strategy to build a meta-teacher model that captures domain-invariant knowledge across multiple domains and use it to transfer knowledge to students. Experiments on three dialogue summarization datasets show the effectiveness of the proposed model. Human evaluations also show the superiority of our model with regard to the summary generation quality. © 2024 Association for Computational Linguistics.

关键词： Distillation

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Developing a Differential Evolution with Adaptive Evaluation Function to Treat Real Optimization Problems with Black-box Constraints 14

Developing a Differential Evolution with Adaptive Evaluation...

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14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023

作者： Shiono, Yuma Hori, Takato Uchitane, Takeshi Ito, Nobuhiro Iwata, Kazunori Aichi Institute of Technology Graduate School of Business Administration and Computer Science Toyota Japan Aichi Institute of Technology Faculty of Infomation Science Toyota Japan Aichi University Faculty of Business Administration Nagoya Japan

ISBN: (纸本)9798350324228

In recent years, much attention has been paid to the development of evolutionary computation algorithms that can perform well not only on benchmark problems but also on real optimization problems. Wind Turbine Design optimization Problem (WTDOP) is a real optimization problem in Evolutionary Computation Competition in Japan. WTDOP has 22 constraints and they are described as black-box constraint functions. From previous studies, it was found that WTDOP has a multi-modal landscape fitness function. Hori et al. performed optimization by established a new evaluation function which includes objective function value and a penalty value of constraint violations and by using iDEaSm which is an evolutionary computation algorithm. However there were two issues. One is a fixed penalty which was added to the objective value of solution. Another is that the variety of solutions is not ensured. In order to overcome such issues, in this paper, two improvements are proposed and examined. One of the improvements is the adaptive evaluation function. By changing the penalty depending on the search depth, it is possible to search the boundary between the infeasible and feasible regions without eliminating the infeasible solutions in the early or middle stage of the search. Another is an additional mutation of solution candidates. The additional mutations ensure diversity stochastically and allow the search to continue after the initial convergence. From the comparison between proposed and previous algorithms, our proposed algorithm could find better solutions. Therefore, our proposed algorithm may have better possibility to solve other real optimization problems. © 2023 IEEE.

关键词： Evolutionary algorithms

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A Structured Scene-Oriented SLAM System Based on Low-Cost Multi-Sensor Fusion

A Structured Scene-Oriented SLAM System Based on Low-Cost Mu...

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International Conference on Cybernetics, Robotics and Control (CRC)

作者： Chao Feng Zhiwei Jia Wupeng Zhang School of Electrical and Infomation Engineering Changsha University of Science and Technology Changsha China

关键词：

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Transmission Efficiency Analysis and Data Calculation of *** Component in Front and Back Interaction Process 3

Transmission Efficiency Analysis and Data Calculation of ***...

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3rd International Conference on Computers, Information Processing and Advanced Education, CIPAE 2022

作者： Liu, Chenchen Wu, Chengmao School of Mechanical and Electrical Engineering Xichang College Xichang China School of Infomation Science and Technology Xichang College Xichang China

ISBN: (纸本)9781665468121

In order to explore the stability and efficiency of the four commonly used value-transfer components of the *** framework under the application layer of the Internet of Things (IOT) agricultural greenhouses, we achieved component development by combing the front end and implemented a business model with the *** framework on the backend in this paper. In addition, aiming at the problem of the efficiency of signal transfer between page components, we applied the MongoDB database system to explore and research transmission efficiency of four value transfer methods, such as value-transfer by routers with diameters, value-transfer by setting Session Storage cache, value-transfer from parent components to child components, and value-transfer by emit events' child components, and obtained response data through a simulation test, thus proving that the value-transfer method is more efficient in this environment. The paper provides an important solution for the key problems of similar environment platforms in the future. © 2022 IEEE.

关键词： Digital storage

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Uplink OFDMA Random Access Mechanism Based on Adaptive Modulation Backoff Step

Uplink OFDMA Random Access Mechanism Based on Adaptive Modul...

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Intelligent Computing and Wireless Optical Communications (ICWOC), International Conference on

作者： Xiao Zhu Yi Zhong Wei He Lijun Wang Tao Han School of Electronic Infomation and Communication HuaZhong University of Science and Technology Wuhan China Department of Information Science and Technology Wenhua College Wuhan China

ISBN: (数字)9798350374377

ISBN: (纸本)9798350374384

802.11ax introduces Orthogonal Frequency Division Multiple Access (OFDMA) and uplink OFDMA random access (UORA) technology to enhance user throughput and system efficiency in multi-user scenarios. However, as the number of users increases, the high collision rate of Stations (STAs) under the traditional UORA mechanism becomes inadequate to meet the transmission demands in dense scenarios. In this paper, we propose an adaptive UORA algorithm α-UORA, based on the traditional UORA algorithm. This algorithm dynamically adjusts the One-Backoff (OBO) contention window based on transmission conditions in dense scenarios. Simulation and analysis indicate that this algorithm significantly reduces the collision rate of STAs and improve user throughput in dense scenarios.

关键词： Wireless communication Heuristic algorithms Simulation OFDM Modulation IEEE 802.11ax Standard Throughput

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