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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Dinh, Hiep X. Balcytis, Armandas Ozawa, Tomoki Ota, Yasutomo Baba, Toshihiko Iwamoto, Satoshi Mitchell, Arnan Nguyen, Thach G. Rmit University Integrated Photonics and Applications Centre MelbourneVIC3000 Australia Advanced Institute for Materials Research Tohoku University Sendai980-8577 Japan Keio University Department of Applied Physics and Physico-Informatics Yokohama223-8522 Japan Yokohama National University Department of Electrical and Computer Engineering Yokohama240-8501 Japan The University of Tokyo Research Center for Advanced Science and Technology Tokyo153-8904 Japan

We report synthetic frequency dimension Su-Schrieffer-Heeger model and its band structure observation using coupled ring cavities on an integrated photonic chip. Intra-cell and inter-cell couplings between hybridized ... 详细信息

ISBN: (纸本)9798350372076

关键词： Photonic integrated circuits

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HybridHash: Hybrid Convolutional and Self-Attention Deep Hashing for Image Retrieval

arXiv

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arXiv 2024年

作者： He, Chao Wei, Hongxi School of Computer Science Inner Mongolia University Provincial Key Laboratory of Mongolian Information Processing Technology National and Local Joint Engineering Research Center of Mongolian Information Processing Hohhot China

Deep image hashing aims to map input images into simple binary hash codes via deep neural networks and thus enable effective large-scale image retrieval. Recently, hybrid networks that combine convolution and Transformer have achieved superior performance on various computer tasks and have attracted extensive attention from researchers. Nevertheless, the potential benefits of such hybrid networks in image retrieval still need to be verified. To this end, we propose a hybrid convolutional and self-attention deep hashing method known as HybridHash. Specifically, we propose a backbone network with stage-wise architecture in which the block aggregation function is introduced to achieve the effect of local self-attention and reduce the computational complexity. The interaction module has been elaborately designed to promote the communication of information between image blocks and to enhance the visual representations. We have conducted comprehensive experiments on three widely used datasets: CIFAR-10, NUS-WIDE and IMAGENET. The experimental results demonstrate that the method proposed in this paper has superior performance with respect to state-of-the-art deep hashing methods. Source code is available https://***/shuaichaochao/HybridHash. Copyright © 2024, The Authors. All rights reserved.

关键词： Image retrieval

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Motion Sensor Alarm with TI LaunchPad and ESP8266 NuttyFi Implementation 11

Motion Sensor Alarm with TI LaunchPad and ESP8266 NuttyFi Im...

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Mustafa, Omar Ibrahim Rasol, Mustafa Asaad Abdalrazzaq, Alaa Salim Hussain, Aqeel Imneef, Zainab Mohammed Chohan, Jasgurpreet Singh Electrical Engineering Technical College Middle Technical University Department of Computer Techniques Engineering Baghdad Iraq College of Dentistry National University of Science and Technology DhiQar Iraq Al-Noor University College Department of Dentistry Bartella Iraq Medical Technical College Al-FarahidiUniversity Iraq Al-Zahrawi University College Department of Dentistry Karbala Iraq University Center for Research and Development Chandigarh University Punjab Mohali14013 India

ISBN: (纸本)9798350350357

Recent times have overseen exceedingly high crime rates, and the appalling situation demands additional personal security measures. In light of the new advancements in technology, the demand for wireless systems has witnessed tremendous affinity, with major domains rapidly attempting to adopt the technique into their custom applications. Security is one such domain where wireless technology has thescope to achieve numerous practical applications. In one such instance, this study deploys the WiFi protocol over an intruder detection system using a TI LaunchPadMSP430. The TI launchpad is connected to the NuttyFi board which provides it with the internet connectivity required to put it online. The motion sensor acts as the input device that triggers the alarm which triggers output devices for intruder warning, in this case, a buzzerin parallel. The system also updates the alert in real-time online over the Blynk web server. This article combines embedded programming, wireless communication, hardware components, and sensing to build an intruder alert system. Using a page from technological baskets like IoT, RF, andembedded systems, the system fulfils a crucial requirement of the current society. Cross-platform usage boosts the utility of this system, putting it in the hands of millions of users. © 2024 IEEE.

关键词： Intrusion detection

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Exploring CLIP’s Dense Knowledge for Weakly Supervised Semantic Segmentation

arXiv

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arXiv 2025年

作者： Yang, Zhiwei Meng, Yucong Fu, Kexue Tang, Feilong Wang, Shuo Song, Zhijian Academy for Engineering and Technology Fudan University Shanghai200433 China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention China Digital Medical Research Center School of Basic Medical Sciences Fudan University China Shandong Computer Science Center National Supercomputer Center in Jinan China

Weakly Supervised Semantic Segmentation (WSSS) with image-level labels aims to achieve pixel-level predictions using Class Activation Maps (CAMs). Recently, Contrastive Language-Image Pre-training (CLIP) has been introduced in WSSS. However, recent methods primarily focus on image-text alignment for CAM generation, while CLIP’s potential in patch-text alignment remains unexplored. In this work, we propose ExCEL to explore CLIP’s dense knowledge via a novel patch-text alignment paradigm for WSSS. Specifically, we propose Text Semantic Enrichment (TSE) and Visual Calibration (VC) modules to improve the dense alignment across both text and vision modalities. To make text embeddings semantically informative, our TSE module applies Large Language Models (LLMs) to build a dataset-wide knowledge base and enriches the text representations with an implicit attribute-hunting process. To mine fine-grained knowledge from visual features, our VC module first proposes Static Visual Calibration (SVC) to propagate fine-grained knowledge in a non-parametric manner. Then Learnable Visual Calibration (LVC) is further proposed to dynamically shift the frozen features towards distributions with diverse semantics. With these enhancements, ExCEL not only retains CLIP’s training-free advantages but also significantly outperforms other state-of-the-art methods with much less training cost on PASCAL VOC and MS COCO. Code is available at https://***/zwyang6/ExCEL. Copyright © 2025, The Authors. All rights reserved.

关键词： Semantic Segmentation

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23 KHz linewidth 1064 nm SOA based fiber laser by using parallel type subring cavities

引用

Laser Physics 2024年第6期34卷 065101-065101页

作者： Liaw, Shien-Kuei Marlina, Lina Wang, Zi Chen, Shu-Miao Lee, Bo-Heng Tsai, Hsiou-Hsin Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Heterogeneously-integrated Silicon Photonic Integration Center National Taiwan University of Science and Technology Taipei10607 Taiwan Graduate Institute of Electro-Optical Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Green Energy and Environment Research Laboratories Industrial Technology Research Institute Tainan71150 Taiwan Department of Dermatology School of Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan

This study presents a high-quality fiber ring laser created by integrating a semiconductor optical amplifier to generate amplified spontaneous emission with a four-subring resonator and utilizing the nonlinear polarization rotator effect. When the driven current of 400 mA, the laser exhibited a maximum power deviation of 0.204 dB and a wavelength deviation of 0.012 nm during a one-hour testing period. Furthermore, utilizing a delayed self-heterodyne measurement system, we measured the linewidth of the self-made fiber laser to be 23 kHz. © 2024 Astro Ltd.

关键词： Ring lasers

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WheatNet: Attentional Path Aggregation Feature Pyramid Network for Precise Detection and Counting of Dense and Arbitrary-Oriented Wheat Spikes

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2024年第2期2卷 606-616页

作者： Jiao, Lin Liu, Qihuang Liu, Haiyun Chen, Peng Wang, Rujing Liu, Kang Dong, Shifeng Anhui University School of Internet Hefei230031 China Chinese Academy of Sciences National Engineering Research Center for Agro-Ecological Big Data Analysis and Application Hefei230031 China Chinese Academy of Sciences Institute of Intelligent Machines Hefei Institutes of Physical Science Hefei230031 China University of Science and Technology of China Hefei230031 China Anhui University National Engineering Research Center for Agro-Ecological Big Data Analysis and Application Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Internet Hefei230601 China Anhui University Institutes of Physical Science and Information Technology Hefei230601 China Chinese Academy of Science Institute of Intelligent Machines Hefei Institutes of Physical Science Hefei230031 China University of Sheffield Department of Computer Science SheffieldS10 2TN United Kingdom Institute of Dataspace Hefei230093 China

Achieving the precise and real-time detection of wheat spikes play a crucial role in wheat growth monitoring for precision agriculture community. Machine-learning methods are commonly introduced to automatically detect and count the wheat spikes, which need carefully selected hand-crafted feature descriptors, leading to time-consuming and poor performance. The deep learning has become a promising technology for the accurate detection wheat spikes, owing to its powerful ability of feature extraction. However, the obtained wheat spike images from UAV still have serious overlap, dense distribution, various orientations, and large aspect ratios, leading to poor performance of recent wheat spike detection method. To address the demand of precise and fast detection and counting of wheat spike with dense distribution and arbitrary-orientation, a novel deep learning-based method, WheatNet, has been proposed. The attention mechanism has been introduced the process of feature fusing to highlight the important features of wheat spike as well as inhibit the useless information. Additionally, to optimize the parameters of the network, a loss function with soft dynamic label assignment is adopted to reduce the number of low-quality matches, which provides significant performance gains over other wheat spike detectors. Furthermore, to achieve the precise detection of wheat spike with multi-orientations, a large-scale oriented wheat spike dataset has been constructed, named RoWheat, including 900 images and 50419 annotations with dense distribution and various orientation. Experimental studies demonstrate that the proposed WheatNet achieves a recall of 99.7% and mAP of 91.8%, showing its promising performance gain compared to other state-of-the-art methods. © 2023 IEEE.

关键词： Image annotation

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Towards Cost-Optimal Policies for DAGs to Utilize IaaS Clouds with Online Learning

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IEEE Transactions on Services Computing 2025年

作者： Wu, Xiaohu Yu, Han Casale, Giuliano Gao, Guanyu Beijing University of Posts and Telecommunications National Engineering Research Center of Mobile Network Technologies Beijing China Nanyang Technological University WeBank-NTU Joint Research Centre on Fintech Singapore Singapore Nanyang Technological University School of Computer Science and Engineering Singapore Singapore Imperial College London Department of Computing London United Kingdom Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China

Premier cloud service providers (CSPs) offer on-demand and spot instances (i.e., virtual machines) with time-varying features in availability and price. While interacting with a CSP, what concerns users is the process of cost-effectively utilizing these instances, possibly in addition to self-owned instances. A job in data-intensive applications is represented by a directed acyclic graph (DAG) whose nodes represent tasks and the DAG can further be transformed into a chain of tasks. The key to achieving cost efficiency is determining the allocation of a specific deadline to each task, as well as the allocation of different types of instances to the task. In this paper, we make some mild assumptions on the usage of various instances and give an analytical understanding of the expected behaviors while utilizing instances. Based on this, we propose informed heuristic policies to determine the allocation of deadlines and instances. The policies are parametric to support the usage of online learning to infer the optimal values against the dynamics of cloud markets. Finally, intuitive greedy policies are used as baselines to validate the effectiveness of the proposed analytical solutions. The cost improvement is up to 23.58% when spot and on-demand instances are considered and up to 50.08% when self-owned instances are also considered. © 2008-2012 IEEE.

关键词： Cloud platforms

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Med-DANet V2: A Flexible Dynamic Architecture for Efficient Medical Volumetric Segmentation

Med-DANet V2: A Flexible Dynamic Architecture for Efficient ...

引用

IEEE Workshop on Applications of computer Vision (WACV)

作者： Haoran Shen Yifu Zhang Wenxuan Wang Chen Chen Jing Liu Shanshan Song Jiangyun Li School of Automation and Electrical Engineering University of Science and Technology Beijing Center for Research in Computer Vision University of Central Florida National Lab of Pattern Recognition Institute of Automation Chinese Academy of Sciences

Recent works have shown that the computational efficiency of 3D medical image (e.g. CT and MRI) segmentation can be impressively improved by dynamic inference based on slice-wise complexity. As a pioneering work, a dynamic architecture network for medical volumetric segmentation (i.e. Med-DANet [44]) has achieved a favorable accuracy and efficiency trade-off by dynamically selecting a suitable 2D candidate model from the pre-defined model bank for different slices. However, the issues of incomplete data analysis, high training costs, and the two-stage pipeline in Med-DANet require further improvement. To this end, this paper further explores a unified formulation of the dynamic inference framework from the perspective of both the data itself and the model structure. For each slice of the input volume, our proposed method dynamically selects an important foreground region for segmentation based on the policy generated by our Decision Network and Crop Position Network. Besides, we propose to insert a stage-wise quantization selector to the employed segmentation model (e.g. U-Net) for dynamic architecture adapting. Extensive experiments on BraTS 2019 and 2020 show that our method achieves comparable or better performance than previous state-of-the-art methods with much less model complexity. Compared with previous methods Med-DANet and TransBTS with dynamic and static architecture respectively, our framework improves the model efficiency by up to nearly 4.1 and 17.3 times with comparable segmentation results on BraTS 2019. Code will be available at https://***/Rubics-Xuan/Med-DANet.

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Conversational Product Recommendation using LLM

Conversational Product Recommendation using LLM

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Ting-Jui Chang Lydia Hsiao-Mei Lin Richard Tzong-Han Tsai Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan Department of Interaction Design National Taipei University of Technology Taipei Taiwan Research Center for Humanities and Social Sciences Academia Sinica Taipei Taiwan

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

It is expected to deploy chatbots as sales assistants on e-commerce platforms soon. In recent years, the capabilities demonstrated by large language models (LLMs) indicate their suitability for this role. However, a dialogue process is not fully established. Most existing works concentrate on searching for ideal products, such as Retrieval-Augmented Generation (RAG) and product search. Many proposed methods rely on product reviews. However, in the case of some e-commerce platform products, valuable reviews are often lacking, rendering these approaches impractical. Thus, we studied how to assist users and select a set of candidate products. Accordingly, we simulated sales conversations based on the product features provided by the seller, using LLM and reliable content while addressing the cold-start problem. Specifically, we used product features to generate customer persona for user simulation. LLM was used to play the role of sales assistant in giving recommendations. The experimental results showed that practical conversation was created between customers and chatbots in Traditional Chinese. The code and results are available at: https://***/terryobe-ncu/CPR_LLM

关键词： Reviews Large language models Oral communication Chatbots Rendering (computer graphics) Question generation Safety

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A New Median Filter Circuit Design Based on Atomic Silicon Quantum-Dot for Digital Image Processing and IoT Applications

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IEEE Internet of Things Journal 2025年

作者： Ahmadpour, Seyed-Sajad Avval, Danial Bakhshayeshi Navimipour, Nima Jafari Rasmi, Hadi Heidari, Arash Kassa, Sankit Misra, Neeraj Kumar Navin, Ahmad Habibizad Mosleh, Mohammad Hosseinzadeh, Mehdi Patidar, Mukesh Kadir Has University Department of Computer Engineering Istanbul Turkey Sakarya University Department of Information Systems Engineering Sakarya Turkey Department of Computer Engineering Kadir Has University Istanbul Turkey Future Technology Research Center National Yunlin University of Science and Technology Douliou Yunlin64002 Taiwan Western Caspian University Research Center of High Technologies and Innovative Engineering Baku Azerbaijan Islamic Azad University Department of Computer Engineering Dez.C. Dezful Iran İstanbul Atlas University Faculty of Engineering and Natural Science Department of Computer Engineering Istanbul Turkey Symbiosis International Deemed University Symbiois Institute of Technology Pune India VIT-AP University School of Electronics Engineering Andhra Pradesh Amaravathi522237 India Islamic Azad University Department of Computer Engineering Tabriz Branch Tabriz*** Iran Islamic Azad University Department of Computer Engineering Dezful Branch Dezful Iran Duy Tan University Institute of Research and Development Da Nang Viet Nam Indore Institute of Science and Technology Department of Electronics and Communication Engineering Madhya Pradesh Indore453111 India

Digital Image Processing (DIP) is the ability to manipulate digital photographs via algorithms for pattern detection, segmentation, enhancement, and noise reduction. In addition, the Internet of Things (IoT) acts as the eye and system for all DIP in various applications. It can possess a camera or another image sensor in order to capture real-time data from its environment. All vital data is processed by image processing in such a way that it recognizes the object, detects an anomaly, and automatically decides in real-time. In addition, in an IoT system, the median filter is the technique used for noise reduction by substituting the value of the pixel with the central value of the surrounding pixels. It provides speed and efficiency for quick analysis in all IoT systems. However, the images can get corrupted, especially in resource-constrained IoT devices with small cameras, because of random glitches. Moreover, using new quantum technology like atomic-scale silicon dangling bond (DB) logic circuits, which have advanced in fabrication and become a strong contender for field-coupled nano-computing, can solve previous problems in IoT systems. In this paper, we propose a unique quantum CSM based on two new proposed Mux and De-mux. The proposed CSM can be used for computational circuits like median filter circuits (MFC) in a wide range of digital circuits, specifically IoT devices. The proposed design is verified and validated using the powerful SiQAD tool. When comparing CSM to the newest designs, the suggested quantum circuit uses 85% less energy and takes up 61% less area. © 2014 IEEE.

关键词： Dangling bonds

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