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检索条件"任意字段=International Conference on Computer and Automation Engineering"

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A New Approach to Design Smart Surveillance System by Enhancing Doorbell Mechanism 2nd

A New Approach to Design Smart Surveillance System by Enhanc...

引用

2nd international conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Dwivedi, Shashank Tiwari, Amit Kumar Sankalp, Prem Gupta, Pradeep Shubbham Malviya, Abhishek Department of Computer Science and Engineering United Institute of Technology Uttar Pradesh Prayagraj211008 India

ISBN: (纸本)9789819776023

Smart Doorbell and Locking system is a system of interconnected IoT devices and sensors. This is an IOT device for home or office automation. Traditional doorbells serve the purpose but this smart doorbell can save plenty of time with the help of face recognition module. The purpose of this project is not just limited in saving time but it also offers some safety features. This device is just a step towards smart homes. Although there are plenty of commercial smart doorbells available but they are quite expensive and some of them lacks features that this project offers. This device can connect to Wi-Fi and can be accessed with mobile devices which is time-saving and provides complete control of this device through fingertips. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Face recognition IOT OpenCV Raspberry Pi Smart doorbell Smart lock

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Improvement of Depth Mapping and Occlusion Removal Method Using Integral Imaging 23

Improvement of Depth Mapping and Occlusion Removal Method Us...

引用

23rd international conference on Control, automation and Systems, ICCAS 2023

作者： Sakanoue, Haruka Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Kyushu Institute of Technology Department of Computer Science and Networks Fukuoka Iizuka820-8502 Japan School of ICT Robotics and Mechanical Engineering Iitc Hankyong National University Kyonggi-do Anseong17579 Korea Republic of

ISBN: (纸本)9788993215274

In this paper, we propose the depth mapping and occlusion removal method using integral imaging (InIm). InIm is a method to obtain 3D information by capturing and reconstructing an object from multiple viewpoints. InIm can remove occlusion using parallax obtained by photographing an object from multiple viewpoints. However, occlusion removal uses a unit matrix to calculate the number of overlaps, which results in an overall darkening of the image. To solve this problem, this paper aims to improve occlusion removal by using the matrix of the mask image to calculate the number of overlaps. InIm can provide depth mapping that shows the distance from an object as pixel values. However, when there is an occlusion in front of the object, it is difficult to provide depth mapping object due to the influence of the occlusion. To solve this problem, we propose a method of depth mapping and occlusion removal method using InIm. Our method is expected to make great progress in improving safety in the field of autonomous driving. © 2023 ICROS.

关键词： Mapping

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UAV detection technology research based on deep learning 7

UAV detection technology research based on deep learning

引用

7th international conference on computer Network, Electronic and automation, ICCNEA 2024

作者： Wang, Yu Bai, Xiaojun Di, Liuhua Zhao, Shifeng School of Computer Science and Engineering Xi’an Technological University Xi’an China East China Section TechnoPro China Wuxi China

In the process of UAV target recognition, the target is small, the feature is not obvious, and the recognition accuracy is low, a UAV target detection method called YOLOv8-UD is proposed based on YOLOv8. This method replaces downsampling layers with SPD convolutions to mitigate fine-grained feature loss issues. It employs a BiFPN structure to get information which is multi-scale, enhancing representation of global semantic message and Improve awareness of small goals. As a result, to target detection, it significantly enhances the correctness and effectiveness. Additionally, to address difficulty of detecting low-resolution small targets, the network structure was modified by adding a detection head, for small target, thereby enhancing capability to detect it. Combining an improved loss function based on Inner-IoU accelerated model convergence and improved detection accuracy of samples at high IoU thresholds. We can tell by experiments that The algorithm proposed in this paper have 0.805 and 0.334 in mAP(0.5) and mAP(0.5:0.95) metrics, respectively. Compared to YOLOv8, improvements of 4.6% and 7% are achieved in mAP(0.5) and mAP (0.5:0.95) metrics. The experiments validate that the proposed way significantly enhances accuracy to UAV small target detection. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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MFFNet: Multi-modal Feature Fusion Network for Instance Segmentation of Froth Flotation Images 2

MFFNet: Multi-modal Feature Fusion Network for Instance Segm...

引用

2nd international conference on Artificial Intelligence, Human-computer Interaction and Robotics, AIHCIR 2023

作者： Dong, Wenkai Liu, Leiming Chen, Xiaoqi Ma, Jianfu Zhang, Tianxiang Li, Jiangyun School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Sichuan Tori Information Engineering Co. Ltd. Sichuan China

ISBN: (纸本)9798350360363

In the field of ore resource processing, froth flotation is widely used to separate minerals. The common methods for assessing flotation status heavily rely on on-site observations by workers, which makes it difficult to ensure long-term stability. Traditional machine learning methods have limited accuracy in froth image segmentation, and the performance of semantic segmentation methods is restricted by inter-class imbalances caused by semantic labels. The extremely dense distribution in froth images also makes it in-sufficient to distinguish foreground from background using only the single modal. So, we design a four-camera system to generate multi-modal data (images and point clouds). The data are labeled at instance-level to create a FF4000 dataset. Based on instance segmentation, we propose a multi-modal feature fusion network named MFFNet, and experimental results demonstrate its effectiveness on the FF4000 dataset. © 2023 IEEE.

关键词： Semantics

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Design of Current Reference Controller for Inverter-Based Resources to Emulate Short-Circuit Behavior of a Synchronous Generator 17

Design of Current Reference Controller for Inverter-Based Re...

引用

17th international conference on Protection and automation in Power System, IPAPS 2023

作者： Jafarian, Peyman Hashemi, Sayyed Mohammad Sanaye-Pasand, Majid Tehran Iran University of Tehran School of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350311532

Renewable resources are mostly interfaced to the grid through inverter systems with dictated behavior during short-circuit faults depending on the manufacturer design and specifications. The unconventional short-circuit behavior of inverter-based resources (IBR) challenges the conventional protective functions, causing spurious tripping for some external fault conditions and no tripping for some internal faults. An approach to alleviate the IBR protection issues is to develop new protective functions compatible with the fault response of IBRs. However, in a transmission system with high penetration of IBRs, many protective relays throughout the grid could be affected so that replacement of a large number of conventional relays is not practically feasible. Rather, it is economically beneficial to design the control system of IBRs so as to mimic the fault behavior of a conventional synchronous machine. This paper presents a current reference controller for the full-converter IBRs to utilize the maximum current capability of the inverter power-electronic switches while emulating the incremental sequence current magnitudes of a conventional synchronous generator. Conducting simulation studies in the PSCAD/EMTDC program, it is shown than the proposed method is well capable of achieving the mentioned goal for all fault types. © 2023 IEEE.

关键词： Electric power transmission

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Application of Blockchain in College Network Ideological and Political Education 5

Application of Blockchain in College Network Ideological and...

引用

5th international conference on computer Network, Electronic and automation, ICCNEA 2022

作者： Xie, Junqiang Qiao, Yanhong Huyan, Xiaorong Yang, Fei Qiao, Siyuan Xi'an Technological University School of Computer Science and Engineering Xi'an China Qiming Xingchen Information Technology Co. LTD. Technology Department Xi'an China Xi'an Technological University Publicity Department Xi'an China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

At present, the model of 'Internet+' has been integrated into every aspect of social life, and the era of big data has accelerated the two-way process of social networking and network socialization. As another disruptive technology after cloud computing, Internet of things and big data, blockchain technology has highlighted its application value in many fields. Therefore, the discussion on the development and application of blockchain technology in the field of education has attracted much attention. This paper deeply discusses the application, approach and method of block chain technology in the network ideological and political education in universities, as well as the practical approach to the construction of application scenarios. © 2022 IEEE.

关键词： Blockchain

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Opportunities of Machine Learning Techniques in the Catering Industry- A Survey 2

Opportunities of Machine Learning Techniques in the Catering...

引用

2nd international conference on Electronics and Renewable Systems, ICEARS 2023

作者： Arvindaraj, G. Manikandan, B. Rokesh, R. Abinaya, M. Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350346640

The human labor force is essential in manufacturing and packing food items. In some cases, human workers cause the food and catering industries to fail to maintain a demand-driven supply chain, food quality and ingredient planning. Industrial automation with mobile access is considered as the best solution to overcome these problems. The main intention of this study is to review various Artificial Intelligence (AI) techniques and find opportunities for incorporating Machine Learning (ML) in the catering industry, with a particular focus on the ingredient planner and its move toward automation. Mobile apps have become the most promising solution for several analysis, particularly for food delivery applications, but the need for food preparation in the field of catering services related to traditional techniques is still not well recognized. In this research, a qualitative analysis has been conducted for the 500 food items and their requirements through the survey, which will be implemented in the Ingredient Planner (IP) mobile application to help customers and caterers using AI-based techniques. Furthermore, a multi-functional model is implemented to fully utilize big data for ingredient analyses in food items, reducing computational time, manual calculation time, and food waste. © 2023 IEEE.

关键词： Big data

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Fatigue Driving Detection Based on Facial Multi-Information Feature Fusion 7

Fatigue Driving Detection Based on Facial Multi-Information ...

引用

7th international conference on computer Network, Electronic and automation, ICCNEA 2024

作者： Qu, Wenjing Wang, Zhongsheng School of Computer Science and Engineering Xi'an Technological University Xi'an China

Driver fatigue driving risk detection is one of the important areas of road traffic safety research in China. According to statistics, more than 40% of China's traffic accidents every year are related to driver fatigue. In order to reduce this risk, this paper proposes a new method based on facial multi-information feature fusion to realize real-time fatigue driving detection. The method includes using the camera to capture the driver's face image in real time, combining the face recognition in Dlib library and the detection of 68 key points, and implementing the face detection through OpenCV. Further, the opening and closing states of eyes and mouth were analyzed based on EAR and MAR algorithms, and a reasonable threshold was set to judge fatigue behavior. The HPE head pose estimation method is used to judge the fatigue state by considering the pitch Angle and roll Angle information. Finally, the improved rough set theory comprehensive evaluation method is used to carry out decision fusion processing on the feature results, and intuitively display the system detection results, which is convenient to evaluate the fatigue state of the current driver. The experimental results show that the multi-feature fusion detection method has good real-time performance, the accuracy rate is 94.55%, and the fatigue state can be detected quickly and accurately under various driving attitudes. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Face recognition

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Substation multi-target detection method based on improved YOLOX-s 5

Substation multi-target detection method based on improved Y...

引用

5th international conference on Frontiers Technology of Information and computer, ICFTIC 2023

作者： Cheng, Yexin Dai, Zuoxiao Wang, Xiaohui Shanghai University of Electric Power Yangpu School of Automation Engineering Shanghai China Shanghai Institute of Technical Physics Chinese Academy of Sciences Hongkou Shanghai China Taicang Institute of Optoelectronic Technology Suzhou China

ISBN: (纸本)9798350309034

With the advancement of national construction, the urgency of the safe operation of substations is constantly increasing, leading to a growing integration of power inspection equipment in daily substation inspection tasks. Due to the challenges posed by the complex background of the captured images and the minimal pixel occupancy of certain power equipment, which causes identification difficulties, this paper proposes an enhanced multi-object detection method for substations based on the YOLOX-s algorithm. The improved algorithm builds upon the YOLOX-s foundation, incorporating attention mechanisms at three output layer positions in its backbone extraction network, as well as in the intermediate layer channel output position, and refining its SPP structure. As a result, compared to the original YOLOX-s algorithm, while maintaining similar deployment conditions and detection speed, the modified approach has improved the mean average precision (IoU=0.5) of power target detection by 4.36%. This effectively addresses the issue of detecting small targets in the complex background of substations. © 2023 IEEE.

关键词： attention mechanism substation target detection

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Design And Implementation Of A PID Control System On A UAV Tracker Antenna

Design And Implementation Of A PID Control System On A UAV T...

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2023 international conference on Advanced Mechatronics, Intelligent Manufacture and Industrial automation, ICAMIMIA 2023

作者： Jayadi, Akhmad Adhinata, Faisal Dharma Persada Sembiring, Jaka Setyo Adhi, Canggih Gelar Herman Selsily, Wendel Amiruddin, Ahmad Universitas Teknokrat Indonesian Faculty of Engineering and Computer Science Lampung Indonesia Institut Teknologi Telkom Purwokerto Faculty of Informatics Jawa Tengah Indonesia Universitas Bina Nusantara Faculty of Computer Science Semarang Indonesia Universitas Kristen Indonesia Maluku Faculty of Computer Science Maluku Indonesia

ISBN: (纸本)9798350309225

Antennas are essential components in communication systems, serving as both transmitters and receivers. Their efficient operation depends on precise alignment with the strongest signal source, facilitated by tracker antennas. A recent research study focused on enhancing the responsiveness of these tracker antennas. By manually inputting PID (Proportional-Integral-Derivative) values for direction control, the study achieved notable *** results demonstrated that by fine-tuning PID values, particularly setting Kp=5, Ki=0.21812, and Kd=12, and targeting an angle of 90°, the response time was reduced to 1.2 seconds with an overshoot of 28.8% and 1.6 seconds of oscillation. This optimized control mechanism significantly improved antenna direction accuracy, aligning it with the desired setpoint. Furthermore, the importance of antenna alignment and polarization matching in communication systems was emphasized. Ensuring alignment between the receiving antenna's polarization and the incoming wave polarization is crucial for maintaining a strong signal reception power level. This alignment enables accurate tracking of antenna positions, supporting real-time GPS data communication. Additionally, the study involving horizontal azimuth angle measurements with tracker antennas demonstrated their capability to transmit real-time data from multiple positions, achieving 360° horizontal azimuth angles, along with varying elevations. These precise measurements play a vital role in object monitoring and effective communication. © 2023 IEEE.

关键词： Global positioning system

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