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Autoencoder-based Local Descriptor for Target Recognition in Infrared images 7

Autoencoder-based Local Descriptor for Target Recognition in...

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7th international conference on image and signal Processing and their Applications, ISPA 2022

作者： Nebili, Billel Khellal, Atmane Nemra, Abdelkrim Abdselam Bououden, Ikbal Belhafsi, Abdeldjalil Bordj El Bahri Algiers Algeria

ISBN: (纸本)9781665480420

Target recognition systems consist of two stages: feature extraction and classification. To improve the performance of these systems, we require high-quality features. The features extracted from RGB images are generally rich in information, which is not the case for infrared images. The processing of this later is challenging, mainly due to their properties of low contrast, competitive background and lack of edges. Traditional hand-crafted feature extractors are limited by these challenges. In this work, an autoencoder-based local descriptor is explored for target recognition in infrared images. Firstly, we generate the local descriptors using a convolutional autoencoder. Next, a global representation is built from these local descriptors, based on the bag of visual words model. Finally, we fed the global descriptor to a classifier. The evaluation of this approach is carried out on two thermal datasets: FLIR thermal starter dataset and VAIS dataset. © 2022 IEEE.

关键词： Learning systems

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Optical tunable differentiator based on microring resonator assisted by low-loss superlattice phase change material 2

Optical tunable differentiator based on microring resonator ...

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2nd international conference on Optical Communication and Optical Information Processing, OCOIP 2024

作者： Wu, Ziqi Dong, Yida Zhong, Wentao Shen, Mei Lei, Lei Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province Shenzhen518060 China 518060 China College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Academy for Advanced Interdisciplinary Studies Department of Materials Science and Engineering Southern University of Science and Technology Shenzhen518000 China

ISBN: (数字)9781510688995

ISBN: (纸本)9781510688988

This paper presents a novel microring resonator (MRR)-based all-optical tunable temporal differentiator. By modulating the crystallinity of the ZnS-SiO2/Ge2Sb2Te5 (GST-SL) phase change material (PCM), the coupling regime of the MRR can be precisely adjusted, achieving a differentiation order (α) range of 0.7-1.3. Experimental validation with non-return-to-zero (NRZ) and return-to-zero (RZ) signal types demonstrates a strong alignment with theoretical models, maintaining an error margin below 7.3%, which confirms the device's high adjustability and stability. The proposed tuning mechanism enables low-energy, high-speed optical control of MRR states, contributing to optimized chip area and power consumption. Supported by the unique characteristics of the superlattice structure, this all-optical tunable differentiator offers promising potential for large-scale AI-driven photonic integrated circuits, particularly in applications such as optical analog computing, optical image processing, and optical neural networks. © 2025 SPIE.

关键词： Photonic integrated circuits

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Trajectory Prediction in Autonomous Driving with Vision-based Deep Neural Networks

Trajectory Prediction in Autonomous Driving with Vision-base...

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international IEEE conference on signal-image Technologies and internet-based System

作者： Vinay Singh Simran Jot Kaur Shyam Shanckin Department of Computer Science and Engineering Thapar Institute of Engineering and Technology Patiala India Department of Computer Science and Engineering Hindustan Institute of Technology and Science Chennai India

Vision-based deep neural networks are crucial components for autonomous driving in terms of visual understanding and decision making. These models need to be temporally consistent and visually interpretable. Most recent works focus on using static images for understanding visual semantics, ignoring the temporal consistency of driving conditions; or adopt end to-end architectures for learning the pilot networks, providing limited interpretability. In this paper, we raise the question of can we predict other traffic participant’s future trajectory given previous egomotion visual input? The proposed system stems from the issue of human driver reaction time in the autonomous driving context. Our dual-staged model firstly applies modern convolutional object detectors for spotting traffic participants (i.e., cars in this paper) and robustly tracks the targets of interest. Then, a novel SEG-LSTM network is incorporated to fuse the multiple-streams from past frames and then predict targets’ future trajectories. We demonstrate the feasibility of predicting future trajectories of vehicles for assisting mediated perception. We also show the effectiveness of combining various levels of abstractions (e.g., scene semantics, detection bounding boxes) further boost the prediction accuracy across diverse traffic conditions.

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Hybrid Blockchain and IPFS for Secure Industry 4.0 Framework of IoT-based Skin Monitoring System 9

Hybrid Blockchain and IPFS for Secure Industry 4.0 Framework...

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9th international conference on Advanced Computing and Communication systems, ICACCS 2023

作者： Bhadula, Shuchi Sharma, Sachin Johri, Amar Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Saudi Electronic University College of Administrative and Financial Sciences Dammam Saudi Arabia

ISBN: (纸本)9798350397376

The blockchain concept is already gaining traction in the healthcare industry, with significant ramifications. According to reports, IoT-based healthcare technologies are shifting the healthcare industry's focus from hospitals to patients. A recent development uses shared data to communicate, identify, and treat people with skin diseases: Intelligent Skin Monitoring systems based on the internet of Things (IoT). It is possible to equip healthcare vehicles with skin and image sensors to measure the care given to those who live in rural locations or have limited access to medical institutions. Conversely, divulging sensitive information through a network threatens the security and privacy of medical and personal data. It's a huge difficulty to provide security and privacy without jeopardising the trust of a trustworthy third party. Another significant issue is the safe storage of vast amounts of medical data. These problems can be resolved by using IPFS in conjunction with blockchain technology. In order to securely share medical transactions and verify individuals with skin diseases in a distributed setting, the study suggests a hybrid blockchain and IPFS-based solution. The work presented here provides a safer framework for interacting with IPFS transactions. The goal is to develop a system that is low-cost, high-efficiency, and secure. © 2023 IEEE.

关键词： Smart contract

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Resource Allocation for Multi-cell Semantic Communication based on Deep Reinforcement Learning 23

Resource Allocation for Multi-cell Semantic Communication ba...

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23rd IEEE international conference on Communication technology, ICCT 2023

作者： Cheng, Guang Wang, Xiaoming Li, Dapeng Jiang, Rui Xu, Youyun School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9798350325959

Semantic communication is considered to be able to break through the limitations of Shannon's law and truly realizes the 6th generation mobile communication technology (6G). Most of the current semantic communication researches focus on signal detection, semantic extraction and recovery. The resource allocation in semantic communication system has not been completely considered. Meanwhile, with the development of communication system, the communication environment is increasingly complex, so that the high dynamic resource allocation problem is difficult to be solved by classical methods. Therefore, this paper formulates to solve multi-object, non-convex, dynamic resource allocation problems in multi-cell semantic communication systems through deep reinforcement learning. based on Transformer model, we realize the transformation from bit information transmission rate to semantic information transmission rate. At the same time, we introduce semantic throughput (STP) as a metric of system semantic transmission rate. Moreover, we use deep reinforcement learning to solve sub-channel allocation and power allocation problems in dynamic systems. Compared with the traditional resource allocation method, that of semantic communication in this paper has larger STP under the same semantic confidence. © 2023 IEEE.

关键词： deep reinforcement learning multi-cell systems resource allocation Semantic communication

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Quality Evaluation Algorithm of Human Video Motion image Segmentation based on Visual Perception

Quality Evaluation Algorithm of Human Video Motion Image Seg...

引用

international conference on Business Intelligence and Information technology, BIIT 2022

作者： Wang, Qingwei Wang, Xinyu Lv, Zhifeng Tan, Dahai Harbin Huade University Harbin150025 China

ISBN: (纸本)9789819934157

In view of the problems of the existing human video motion image segmentation quality (SQ) evaluation method with low evaluation accuracy and poor anti-interference during the evaluation process, a human video motion image SQ evaluation algorithm based on visual perception was proposed. Firstly, the model of edge contour feature detection and pixel reconstruction is constructed to realize multi-level feature decomposition and edge pixel features. Secondly, the visual feature reconstruction model is established, and the image is segmented by the method of spatial region reconstruction. The spatial region reconstruction in the segmentation process is realized through similarity information fusion, and the number of fuzzy features of the image is extracted. Finally, pixel space fusion matching technology is adopted to realize the visual perception of the image, obtain its sparse segmentation model, and realize the evaluation of the SQ of human body motion video images based on template matching. The results show that this method is more accurate in evaluating the SQ of human video motion images, and the output evaluation results have a higher signal-to-noise ratio and good image SQ detection performance. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image segmentation

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Secure Trust-based Attribute Access Control Mechanism Using FK-MFCMC and MOEHO-XGBOOST Techniques 6th

Secure Trust-Based Attribute Access Control Mechanism Using ...

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6th international conference on Soft Computing and signal Processing, ICSCSP 2023

作者： Vanitha, Padala Srikanth, Banda Department of ECE Malla Reddy College of Engineering and Technology Telangana State Hyderabad500100 India University College of Engineering Kakatiya University Telangana State Kothagudem507118 India

ISBN: (纸本)9789819984503

The internet of things (IoT) possesses various devices, which are switching data continuously and are acquired throughout via lossy networks. This promotes the necessity for a lightweight, flexible along with adaptive access control (AC) method to handle the insidious behavior of such global ecological units and also guarantees the reliability betwixt the trusted devices. To provide users with adaptive authentication centered on dynamic trust estimation, a secure trust along with attribute-based AC (ABAC) approach is invented in this research. First, Trust Evaluation (TE) is executed utilizing Fisher score Kernel-based Minkowski fuzzy C-Means Clustering (FK-MFCMC) centered on trusted data balance by means of instructive features being extricated. A successful association is kept up by TE betwixt the nodes installed in the network. And, it guarantees that the entire nodes work in a reliable form. Subsequently, to ingress the request, the TE makes a decision utilizing the multi-objective elephant herding optimization based on an extreme gradient boosting (MOEHO-XGBoost) methodology. In this methodology, the ABAC request is converted into a permission decision vector. Then, it is converted into a binary classification problem that checks whether to permit or reject access. On the whole, the proposed methodology attains higher trust accuracy and TE for several nodes in IoT together with obtains a higher security level in correlation with the prevailing novel methodologies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： internet of things

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SPACEBORNE SAR image SIMULATION based ON MULTI-POLARIZED SAR AIRBORNE DATA

SPACEBORNE SAR IMAGE SIMULATION BASED ON MULTI-POLARIZED SAR...

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IET international Radar conference 2023, IRC 2023

作者： Chen, Xi Chen, Renyuan Earth Observation Research and Development Center No. 38 Research Institute of China Electronic Technology Group Corporation No. 199 Xiangzhang Avenue High tech Development Zone Anhui Hefei China

ISBN: (纸本)9781839539954

SAR image simulation is a technology that simulates SAR image features or the working process of SAR systems on a computer platform to obtain simulated SAR images. It overcomes the high cost and long cycle of obtaining SAR images with different parameters in real SAR systems, and plays an important role in SAR system development and algorithm *** paper aims to solve the problems in existing technologies by providing a method for predicting multi-spaceborne polarimetric SAR images using airborne high-resolution SAR data. The correlation model between polarimetric distortion parameters, target polarimetric complex data information (including amplitude and phase), and the echoes of various polarimetric channels on board the satellite was reconstructed to generate and imaged the spaceborne SAR echoes. This simulation method was validated and evaluated through airborne and spaceborne SAR data. The results showed that the accuracy of typical scene similarity and polarimetric feature similarity estimation was better than 80%. © The Institution of Engineering & technology 2023.

关键词： Polarimeters

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PLC signal Level based Traffic Light System Using RPi: An Experimental Setup

PLC Signal Level Based Traffic Light System Using RPi: An Ex...

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Advancement in technology (ICONAT), international conference for

作者： Ashok Kumar Kumawat Dept. of Mechatronics Engineering Manipal University Jaipur Jaipur India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

It is necessary to regularly enhance the traffic light system’s control using the newest technology. The PLC-based systems that are now in use make it difficult to adopt modern technologies like artificial intelligence, machine learning, and the internet of things etc. This work aims to convert the logic level signal based on PLC to a logic level signal based on Raspberry Pi. A raspberry pi is used as the control unit in the development of an experimental four direction-based traffic light prototype. Two different types of logic level converters are used in this system to create signals that are compatible with both 24 V traffic light system and Raspberry Pi. Python programming on the Raspberry Pi is used to control the entire system.

关键词： Prototypes Machine learning Programming Vision sensors Control systems Sensor systems Real-time systems Logic internet of Things Python

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Design of water quality monitoring system based on NB-IoT technolog 3

Design of water quality monitoring system based on NB-IoT te...

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3rd international conference on Computer Vision, image and Deep Learning and international conference on Computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Wang, YanBing Lv, Fang Inner Mongolia University of Technology Department of Information Engineering Hohhot China

ISBN: (纸本)9781665459112

In order to solve the problems of complexity and low efficiency of traditional water quality monitoring methods, this paper designs a water quality monitoring system combining STM32F103 microcontroller and Huawei Cloud IoT platform based on narrowband internet of Things technology. This system can continuously collect the temperature, pH, TDS and ORP data of the automatically monitored waters of the target. The data can be automatically uploaded to the cloud platform in real time, and users can query real-time monitoring information on the HUAWEI CLOUD IoT platform, which overcomes the shortcomings of traditional water quality monitoring systems such as long data collection cycles and poor real-time performance, and has certain innovation and application value. © 2022 IEEE.

关键词： Search engines

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