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SAR Target Recognition Based on Decoupling and Reconstruction Learning Using Complex-Valued Convolutional Neural Networks 8

SAR Target Recognition Based on Decoupling and Reconstructio...

引用

8th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2023

作者： Qin, Jiang Zou, Bin Zhang, Lamei Ma, Zihao Dept. of Information Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350393590

Recent years, the deep convolutional neural networks (CNNs) based SAR target recognition methods are springing up. However, existing CNN-based SAR target recognition methods are limited by down-sampling caused information loss and feature redundancy, leading to learn shallow data correlations and bringing the performance collapse in practical applications of SAR target recognition. In this paper, a complex-valued decoupling and reconstruction learning (DRL-Net) based method is proposed to improve the SAR target recognition performance. DRL-Net learns the decoupling representation from the complex-valued images to make sure the learned latent feature is sparse and informative. The learned latent feature is then fed to reconstruction learning to keep the information completeness. Finally, the discriminative information is powered into the latent features to gain the semantic for SAR target recognition. Compared with baseline method, DRL-Net gains higher accuracy and faster convergence with the same number of samples. Additionally, DRL-Net exhibits a good potential for SAR target recognition with limited samples. ©2023 IEEE.

关键词： Semantics

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Efficiency Improvement Mechanism Analysis of Sidewall Passivation GaN based Micro-LEDs by Atomic Layer Deposition

Efficiency Improvement Mechanism Analysis of Sidewall Passiv...

引用

International Symposium, Seminar, and Exhibition, Display Week 2024

作者： Zhanghu, Mengyuan Liu, Yibo Liu, Zhaojun Dept. of Electric and Electronic Engineering Southern University of Science and Technology Shenzhen China Dept. of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

Sidewall passivation using atomic layer deposition (ALD) can efficiently improve external quantum efficiency (EQE). Such treatment increases EQE, a combination of internal quantum efficiency (IQE) and light extraction efficiency (LEE), primarily by curtailing surface recombination according to the ABC model. Determined by the ratio of radiative recombination rate to total recombination rate, the IQE of an LED holds a significant correlation with the diode's ideality factor in the Shockley model. In this paper, we analysis the mechanism of ALD sidewall passivation enhancing device performance in detail from the aspects of electrical performance improvement and optical performance improvement. © 2024, John Wiley and Sons Inc. All rights reserved.

关键词： Gallium nitride

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Classification of Chest X-Ray Images using Various Deep Learning Techniques to Identify Covid-19

Classification of Chest X-Ray Images using Various Deep Lear...

引用

2023 International Conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Ananthi, N. Anjana, S. Dhanu Nagarajan, P. Barath Raj, D. Easwari Engineering College Dept. of Information Technology Chennai India

ISBN: (纸本)9798350348910

The healthcare community is deeply concerned about the novel coronavirus (2019-nCoV) that is spreading throughout the world. Since its discovery in late December 2019, the number of cases transferred from Wuhan, China to other countries has increased, causing ongoing changes in the medical environment. With the rapid surge of confirmed cases worldwide, initial focus centered on a Wuhan food market as the outbreak's source. However, a recent overview of primary clinical cases published in The Lancet challenges this hypothesis. Among the diverse strategies employed to curb the virus, closely monitoring its progression through international genomic sequencing has emerged as a crucial measure. Controlling the virus's spread stands as an immensely challenging task, underscoring the necessity for highly accurate health surveillance to enable prompt responses. © 2023 IEEE.

关键词： Deep learning

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Adaptive Weather Routing for Advanced Ship Navigation: A Comprehensive Review 3

Adaptive Weather Routing for Advanced Ship Navigation: A Com...

引用

3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Venkatesan, Iyyappan Dharanish, M.B. Muthumari Lakshmi, S. Pavithra, S. Dept. of Computer Science and Engineering Chennai Institute of Technology Tamil Nadu Chennai600069 India

ISBN: (纸本)9798331527549

Maritime navigation offers a comprehensive approach to optimising ship navigation, in such a way that guarantees the safety and effectiveness of the journey through multiple techniques, like the adaptive weather routing technique, which uses the predictive model and the current weather conditions for efficient navigation. The review mainly emphasizes the basic principles and computational simulation for sustainable navigation in advancing the route defining algorithm. Discusses about the conventional route defining algorithms and dynamic route defining algorithm by adjusting for wind, waves, and currents. A comparison analysis shows how well different algorithms work in various weather conditions, and case studies show how they are used in the actual world, while new trends are being discussed, major problems also concern the need for accurate climate predictions, high-speed data processing, and an efficient response plan. The Advancements in artificial intelligence and composite path forecasting also address issues related to major needs, such as accurate weather forecasts, high-speed data processing, and effective reaction tactics. Through this insights of this review provides on future directions for adaptive weather routing research and development that the sustainable growth of intelligent naval navigation is supported. © 2025 IEEE.

关键词： Weather forecasting

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The Development of an Autonomous Robotic Scanning System with the Laser Rangefinder

The Development of an Autonomous Robotic Scanning System wit...

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Ko, Hung-Chin Chen, Syuan-Yi He, Jyun-Hong Chiang, Hsin-Han National Taiwan Normal University Dept. Electrical Engineering Taipei Taiwan National Taipei University of Technology Dept. Computer Science and Information Engineering Taipei City Taiwan National Taipei University of Technology Dept. Vehicle Engineering Taipei Taiwan

ISBN: (纸本)9798350324174

Due to the rise of Industry 4.0, many industries have begun to replace traditional human labor with automated equipment to achieve greater productivity and more accurate inspection results. Due to its advantages of high stability, high accuracy, and low repetition error, many manufacturing industries have chosen to use robotic arms to replace human labor in production and inspection tasks to obtain faster and more accurate work results. Based on the above advantages, this experiment combines a seven-axis robot arm with 2D LiDAR to scan the object to be inspected, and the algorithm is used to analyze, calculate and plan the inspection path of the arm so that the robot arm can automatically scan the surface of the object to be inspected in an equal speed, smooth, and reproducible way. © 2023 IEEE.

关键词： Inspection

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Sparse Channel Estimation in Massive MIMO Systems Using Compressed Sensing and Neural Networks

Sparse Channel Estimation in Massive MIMO Systems Using Comp...

引用

2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India

ISBN: (纸本)9798350379525

In this paper, based on compressed sensing and neural networks, we present an intelligent sparse channel estimation technique for Massive MIMO systems. We show that our approach improves considerably the estimation accuracy in terms of Mean Squared Error (MSE) and Normalized Mean Squared Error (NMSE) with respect to classical methods. We demonstrate [Figure: ] that our approach is computationally more efficient, requires less time and resources (memory/disk) compared to the existing literature but for a robustness of performance across distal or low Signal-to-Noise Ratios (SNRs). We also confirm our method exhibits fast convergence and efficiently accommodates a variety of sparsity levels. By visualizing it using heatmaps and ROC curves we show that this method is able to effectively differentiate between signal and noise, asserting our approach as a powerful tool for the contemporary set of problems present in wireless communications. © 2024 IEEE.

关键词： Signal to noise ratio

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Artificial Intelligence to Enhance the Security of Internet of Things: A Comprehensive Review 3

Artificial Intelligence to Enhance the Security of Internet ...

引用

3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Dheekshaa, V.M. Harsha, V. Sindhu, M. Pavithra, S. Dept. of Computer Science and Engineering Chennai Institute of Technology Tamil Nadu Chennai600069 India

ISBN: (纸本)9798331527549

The Internet of Things is the term we call when devices are connected to the network and work together to provide a better experience for users, facilitate better decision-making, and improve operations. As with any invention, this one also has its disadvantages. IoT devices have complex structures and low processing capacities. There are serious security risks in designing IoT like poor authentication, data leakage, and DDoS attacks. In this review paper, how AI can secure IoT is discussed. A few AI-driven strategies that help mask all these weaknesses are also discussed regarding intrusion detection systems (IDS), behavioural analytics, anomaly detection, and real-time threat monitoring. It presents a four-layered IoT architecture consisting of perception, network, support, and application layers. The use of the IoT systems will become more flexible and efficient in data security and collection, secure and encrypted communication, and predictive security analytics. AI will play the same role in improving the threat perception, real-time identification, and response, as this will make it indispensable to ensure the IoT environment security. This work emphasizes the urgent need for solid AI-powered, multilayered adaptive security frameworks to match the evolving demands of cybersecurity. © 2025 IEEE.

关键词： Network intrusion

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Smart Toll Booth System Using Smart Contract 8

Smart Toll Booth System Using Smart Contract

引用

8th IEEE International Conference for Convergence in technology, I2CT 2023

作者： Patil, Sonali Kulkarni, Mrudula Desale, Shivam Adsul, Digvijay Choudhary, Kushal Pimpri Chinchwad of Engineering Dept. of Information Technology Pune India

ISBN: (纸本)9798350334012

The present toll collection system has a number of problems, including varying toll rates on different roadways, heavy traffic, etc. Long wait times, theft from toll plazas, and other issues are problems that the toll collection system, particularly in India, encounters. Only 300 automobiles may be serviced by these systems each hour, and if more cars arrive at that area than that, severe traffic Jams could happen. For toll collection, the present toll methods, including Radio Frequency Identification (RFID), still require a lot of time. To address the above mentioned issues, this study discusses a GPS-based toll collection system. Every time a vehicle switches from a highway to a service road, this system would track the coordinates of the moving object. As a result, the user can pay the toll without being pulled over anywhere along the freeway. This system will leverage blockchain technology to construct a decentralized and intelligent mechanism for toll collection and tracking records because it has recently become one of the most well-liked technologies and has the potential to change the field of intelligent transportation systems. The technology uses blockchain smart contracts for the maintenance of security and integrity of records. Thus, presenting a strategy for putting into place a seamless toll collection system with the most transparency possible. © 2023 IEEE.

关键词： Smart contract

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A PolInSAR Four Component Target Decomposition Method for Unambiguous Scattering Analysis Between Forests and Oriented Buildings 6

A PolInSAR Four Component Target Decomposition Method for Un...

引用

6th International Conference on information Communication and Signal Processing, ICICSP 2023

作者： Zhuang, Di Zhang, Lamei Zhu, Bing Harbin Institute of Technology Dept. of Information Engineering Harbin China

ISBN: (纸本)9798350339994

Polarimetric SAR target decomposition plays an important role in ground object interpretation because it can obtain scattering mechanism information. In traditional model-based target decomposition, the volume scattering overestimation of the rotated building area has been always addressed from the perspective of polarimetric response ($S$ matrix, $T$ matrix and $C$ matrix). However, the reduction of the volume scattering in the rotated building area comes at the cost of the complex scattering modeling and solution process, and may lead to an underestimation of the volume scattering in other areas. Therefore, the Polarimetric SAR Interferometry (PoIInSAR) coherence was introduced to assist target decomposition and a new decomposition idea and corresponding PolInSAR four component target decomposition method where the scattering ambiguity is removed from the perspective of non-polarimetric response were proposed in this paper. In the proposed method, the PolInSAR coherence was proposed to distinguish natural areas from built-up areas without scattering ambiguity inside. Then, two very simple sets of scattering models with unfixed model quantities and types were applied for target decomposition in two different areas. Three sets of PolInSAR data from were used for experiments. Results shown that compared with the Freeman-Durden decomposition method, the volume scattering obtained by the proposed method can be reduced by 430/0 in oriented building areas. Compared to the six and seven component decomposition methods, both the proposed method and these two methods can obtain a reasonable proportion of volume scattering in rotated building areas, but the proposed method can keep the volume scattering of the forest area from being underestimated. © 2023 IEEE.

关键词： Image processing Polarimetric image interpretation PolInSAR target decomposition scattering characterization analysis Synthetic aperture radar (SAR)

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Fish Detection using Dual Branch Image Enhanced Pipeline with YOLOv8 3

Fish Detection using Dual Branch Image Enhanced Pipeline wit...

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3rd International Conference on Machine Learning and Data engineering, ICMLDE 2024

作者： Kumar, Vivek Kumaran, P. Dept. of Computer Science Engineering National Institute of Technology-Puducherry Puducherry Karaikal609609 India

Fish species identification plays a crucial role in the aquaculture industry. Current methods such as using sensors, acoustic devices and density map regression, face multiple challenges related to costs, computational complexity and corrosion or malfunctioning of devices in underwater environment. To address these limitations we use YOLOv8(You Only Look Once) for the identification of fish species using visual perspective through the camera. The model is trained using a dataset of fish aquarium images to provide ground truth labels for training and evaluation purposes. Two species were observed in this research: Iridescent Shark Catfish (Pangasianodon hypophthalmus) and Goldfish (Carassius auratus). Our study achieved a notable breakthrough in identifying all the two species within a comprehensive dataset comprising 173 images. The top-performing model demonstrated exceptional accuracy on the test dataset with splitting ratios of 70-20-10 for training, validation, and testing, respectively. The custom model attained a mAP which is mean Average Precision, of 92% at an IoU threshold of 0.5, underscoring its impressive capabilities to detect across all classes. To remove the turbidity, a dual branch image enhancement pipeline is used with yolov8, which gives the best confidence score of 66% in detecting the fish species. © 2025 The Author(s).

关键词： Fisheries

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