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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

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Target detection based on multi-scale feature fusion and cross-channel interactive attention mechanism 3

Target detection based on multi-scale feature fusion and cro...

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2023 3rd international conference on Artificial intelligence and Industrial technology Applications, AIITA 2023

作者： Zhao, Chenyang Song, Yong Yang, Xin Zhou, Ya Yang, Jinqi School of Optics and Photonics Beijing Institute of Technology Beijing China

Aiming at the problems of complex background, target scale change and small target in aerial image detection, we propose a YOLOv5 target detection algorithm based on multi-scale feature fusion and cross-channel interactive attention mechanism. Including: M-PPM (Multi-scale pyramid pooling module) is designed as a replacement for the SPP (Spatial Pyramid Pooling) structure in YOLOv5, so as to make full use of different scale features to fuse global feature information;CCA (Cross-channel interactive attention mechanism) is designed to realize cross-channel information interaction and utilization, and enhance the network's capability to generalize and fusion efficiency of small target features. Bi-directional Feature Pyramid Network (BiFPN) is utilized to solve scale difference problem in multi-target detection. The proposed algorithm's experimental results is 2.3 % and 1.8 % higher than YOLOv5 on the VisDrone and UAVDT aerial data sets, respectively. © Published under licence by IOP Publishing Ltd.

关键词： Antennas

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Research on Road Traversability detection Using Edge Computing and Deep Learning 3rd

Research on Road Traversability Detection Using Edge Computi...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

作者： Yu, Yang Shen, Xiang Shi, YanJun Wang, YiQuan Zhao, XiJun China North Artificial Intelligence and Innovation Research Institute Beijing China NORINCO Unmanned Vehicle Research and Development Center China North Vehicle Research Institute Beijing China School of Mechanical Engineering Dalian University of Technology Dalian China Collective Intelligence and Collaboration Laboratory Beijing China

ISBN: (纸本)9789819711024

Oriented to the challenges of unstructured environments such as fuzzy road features, variable road types, lack of clear road boundaries, and high real-time maneuvering requirements of unmanned platforms, a passable area detection method based on edge computing and deep learning is proposed. The unmanned platform collects unstructured environmental data, trains the dual-channel convolutional neural network BiSeNetV2, and utilizes offline compilation and online inference to transplant the algorithmic model into the edge computing module, realizing real-time passable area detection on the unmanned platform. Through verification, the method can be adapted to a variety of complex unstructured environments, such as unpaved roads, paved roads, snow, etc., and provides favorable passable area detection results, with a detection accuracy of 84.75% and an average detection time of 89.08 ms, which can provide real-time guidance information for unmanned platform scene modeling, autonomous path planning, and remote-control driving, etc., and contribute to the stable passage of unmanned platforms in unstructured environments. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Edge computing

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Cross-modal multi-scale feature fusion-based RGB-T saliency object detection method 3

Cross-modal multi-scale feature fusion-based RGB-T saliency ...

引用

2023 3rd international conference on Artificial intelligence and Industrial technology Applications, AIITA 2023

作者： Zhang, Guangyu Niu, Lianqiang School of Software College Shenyang University of Technology China

To cope with the challenge of significant target detection in complex scenes, this study proposes an RGB-T significant target detection method called CMFF. The method utilizes the complete potential of RGB and thermal infrared modal images and employs a codec structure and cross-modal multiscale feature fusion techniques. In the coding stage, two VGG16 backbone networks are used for multi-level feature extraction and CBAM attention module feature enhancement, and the enhanced features are fused using a stepwise fusion approach. Meanwhile, the weights of the two modalities are assigned using the L1-parametric fusion strategy to enhance the complementarity between them. In the decoding stage, global features are extracted from the high-level fused features by introducing the pyramid pooling module (PPM), and the low-level fused features are fused with multi-scale features in the up-sampling and encoding stages to enrich the global and local information of the feature map. Finally, this study conducted comparison experiments on the publicly available VT5000 dataset, and the method achieved an F-measure value of 0.863 and a mean absolute error (MAE) of 0.062, which significantly improved the overall detection performance relative to the six existing methods. © Published under licence by IOP Publishing Ltd.

关键词： Feature extraction

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2023 IEEE international Mediterranean conference on Communications and Networking, MeditCom 2023

2023 IEEE International Mediterranean Conference on Communic...

引用

3rd IEEE international Mediterranean conference on Communications and Networking, MeditCom 2023

ISBN: (纸本)9798350333732

The proceedings contain 68 papers. The topics discussed include: investigating privacy and security concerns in a running eHealth information system;precoding for quadrature spatial modulation for robustness against channel correlations;smart manufacturing maintenance through LoRaWAN-based ecosystem;backhaul multihop relaying through UAVs under angular fluctuation: a performance study;resource allocation for OTFS-based ISAC systems;power allocation for device-to-device interference channel using truncated graph transformers;multi scale histogram-based intrusion detection system for the MIL-STD-1553 protocol;tuning of ray-based channel model for 5G indoor industrial scenarios;development and verification of dual-functional Cubesat communication system using COTS transceiver;and hardware-friendly power amplifier linearization in next-generation broadcasting systems.

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An Evaluation and Implementation of the Effectiveness of Cloud Security as a Service in IoT Security 3

An Evaluation and Implementation of the Effectiveness of Clo...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Benila, A. Shinde, Swapnil K. Shakya, Anurag Kumar, Jambi Ratna Raja Mondal, Dipannita Hemelatha, S. Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Mangalayatan University Department of Commerce Aligarh India Genba Sopanrao Moze College of Engineering Department of Computer Engineering Maharashtra Pune India Dr. D.Y.Patil College of Engineering and Innovation Artificial Intelligence and Data Science Department Talegaon India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore India

ISBN: (纸本)9798350319125

The net of factors (IoT) has seen a speedy growth in current years, with more devices being linked to the internet daily. Those devices range from family home equipment to business systems, and their lavish use has made them appealing targets for cyber assaults. It poses a tremendous task for safety experts, as more than conventional safety features are frequently needed to guard IoT gadgets. To cope with this issue, many agencies are turning to Cloud protection as a carrier (Case) solution to beautify their IoT security. CSaaS is a cloud-primarily based protection solution that provides more than a few protection services, with chance detection, facts encryption, and the right of entry to manipulate IoT gadgets from cyber threats. It offers a scalable and value-powerful way to relax big numbers of IoT gadgets and can doubtlessly overcome the constraints of traditional security features. But, the effectiveness of Cases in IoT protection continues to be a topic of discussion. This paper aims to assess and implement the effectiveness of Cases in IoT security. It's going to begin by way of imparting an outline of the contemporary nation of IoT security and the challenges confronted in securing those devices. It will then discuss the concept of Cases and its capability benefits for IoT security. The paper may also evaluate current literature on Cases and their applicability to IoT protection © 2023 IEEE.

关键词： applicability doubtlessly imparting literature securing

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Tumor detection and Analysis from Brain MRI Images Using Deep Learning 3rd

Tumor Detection and Analysis from Brain MRI Images Using Dee...

引用

3rd international conference on Machine Vision and Augmented intelligence, MAI 2023

作者： Singh, Shweta Srivastava, Rajeev Department of Computer Science and Engineering Indian Institute of Technology BHU Varanasi Uttar Pradesh Varanasi India

ISBN: (纸本)9789819743582

Establishment of appropriate diagnosis plan for brain tumors is imperative and influences patient survival rate ultimately. Misdiagnosis of some brain tumors though hinders response to treatment and decreases success rate. Traditional ways of discerning brain tumors based on images taken via an MRI machine can be slow and full of mistakes, particularly when processing huge datasets and various shapes of tumor. It is proposed in this study that through such an innovative machine-learning and image processing hybrid technique, brain tumor detection can be enhanced. More precisely, we undertook bilateral filtering and normalization to improve quality of MR images, so as to decrease human errors in tumors’ identification. Therefore, the ResNet-50 model was employed to my significant patterns of data from the preprocessed dataset for further investigation. We did a comparative evaluation of different algorithms for getting the best classifier. Hence, based on the data, one can say with 91.40% accuracy that SVC outperformed all other models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Lite-ODNet: A Lightweight Object detection Network 3

Lite-ODNet: A Lightweight Object Detection Network

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3rd international conference on Artificial intelligence, Human-Computer Interaction and Robotics, AIHCIR 2024

作者： Peng, Wenbang Zhang, Li Zhao, Liaoying Li, Xiaorun School of Computing Science and Technology Hangzhou Dianzi University Hangzhou China Department of Electrical Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9798331534035

Most existing object detection models generally have a large number of parameters and high hardware requirements. How to balance high detection accuracy with low computational demand? The study presents Lite-ODNet, a Lightweight Object detection Network, for efficient object detection. More precisely, it presents a network that delivers excellent detection performance while utilizing fewer hardware resources. Lite-ODNet is composed of a designed Enhanced ShuffleNetV2 (E-ShuffleNetV2), an Efficient Feature Pyramid Network (EffiFPN) with structural re-parameterization and a Simplified Head (S-Head). The model is validated after being tested on VOC07+12, VisDrone2019, and WiderPerson datasets. The findings demonstrate that the proposed method outperforms current leading algorithms, achieving the highest performance in terms of #Param., mAP, FLOPs, and FPS. Finally, this proposed method also reaches an equivalent performance to existing methods in the challenging small objects detection task. © 2024 IEEE.

关键词： Lightweight model Object detection ShuffleNetV2 Structural re-parameterization

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detection of Counterfeit Currency Notes Through Machine Learning Algorithms and Image Processing 3

Detection of Counterfeit Currency Notes Through Machine Lear...

引用

3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Shokeen, Vikrant Kumar, Sandeep Sharma, Amit Singh, Neha Prasad, Aman Sachdeva, Yugank Maharaja Surajmal Institute of Technology New Delhi India Ims Engineering College UP Ghaziabad India Maharaja Agrasen Institute of Technology New Delhi India

ISBN: (纸本)9798350342338

In the modern financial sector, identifying fake money is a constant struggle. In order to address this issue, this research introduces a novel technique that correctly and quickly detects fake certifications by fusing machine learning methods with image processing. The suggested method trains a machine learning model with information from photos of actual and fake banknotes so that it can recognize the distinctive characteristics and patterns that separate real and fake banknotes. Additionally, different image processing techniques are employed to enhance image quality, lessen noise, and boost the clarity of crucial features. The efficiency of the procedure and accuracy in identifying fake goods were tested using the results. The proliferation of counterfeit certifications can be stopped, safeguarding the economy and boosting public confidence in the system, with the help of machine learning algorithms and machine *** of fake credentials, safeguarding the economy and boosting public confidence in the system. © 2023 IEEE.

关键词： Counterfeit-currency Image Processing Machine learning

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Development and Application of College English Translation Teaching Software Based on Artificial intelligence 3rd

Development and Application of College English Translation T...

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3rd EAI international conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023

作者： Zhang, Xiaozhu Qin, Qiutao School of General Education Guangxi Vocational and Technical College Guangxi Nanning530226 China

ISBN: (纸本)9783031631351

This article introduces the development and application of a college English translation teaching software based on artificial intelligence technology. We mainly explored the role and advantages of artificial intelligence technology in college English translation teaching software. At the same time, this article also provides a detailed introduction to the design and development process of a college English translation teaching software. In college English translation teaching software, artificial intelligence technology is mainly used for text translation and voice translation. By utilizing artificial intelligence technology, a large number of English texts and spoken materials can be quickly translated. Meanwhile, compared to traditional artificial intelligence systems, the new type of artificial intelligence system is more intelligent and accurate, and the translation quality has also been greatly improved. In terms of software design and development, this article introduces the development process and technical implementation of college English translation teaching software. We have adopted the B/S architecture and programming languages such as Python to achieve modular design for multiple functions such as speech input, speech recognition, text translation, and speech translation. In addition, we have added functions such as Adaptive learning recommendation system and student learning monitoring system to the software, which makes students’ learning more efficient and personalized. Based on the above content, it can be concluded that the application of artificial intelligence technology in college English translation teaching software can greatly improve students’ learning efficiency and translation quality, injecting new vitality and impetus into the intelligence and modernization of English education and teaching. At the same time, the development process and technical implementation introduced in this article can provide useful inspiration and guidance for r

关键词： Speech recognition

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Plant growth detection based on binocular multispectral imaging 3

Plant growth detection based on binocular multispectral imag...

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3rd international Computing Imaging conference, CITA 2023

作者： Wenxiu, Wan Ziru, Yu Xinying, Peng Jianying, Zhou Xiangyang, Yu School of Physics State Key Laboratory of Optoelectronic Materials and Technologies Sun Yat-sen University Guangzhou510275 China School of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9781510671409

Three-dimensional vision contains richer information about objects than traditional two-dimensional images, to make it more desirable for many applications within measurement, inspection and localization. We design a binocular multispectral imaging system, composed of two multispectral cameras and external light source. Incorporates spectral information at the level of reconstruction algorithm to improve feature matching. The system is capable of observing the growth of plants such as chlorophyll through multi-spectral information, and the depth calculation based on the stereo vision algorithm can detect the growth height of plants. Therefore, this work will be favorable for crop growth observation and provide an efficient and accurate measurement method for 3D morphometry, making it of great importance for the development of biological, agricultural and production research fields. © 2023 SPIE.

关键词： Binoculars

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