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MamTrack: Vision-Language Tracking with Mamba Fusion 24

MamTrack: Vision-Language Tracking with Mamba Fusion

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8th international conference on computer Science and Artificial Intelligence, CSAI 2024

作者： Chen, Donghua Zhang, Hong Song, Jianbo Feng, Yachun Yang, Yifan Image Processing Center Beihang University Beijing China School of Mechanical Engineering & Automation Beihang University Beijing China Institute of Artificial Intelligence Beihang University Beijing China

ISBN: (纸本)9798400718182

Vision-language tracking models aim to improve target tracking performance by fusing visual features and language description of the target, making it more useful and robust for a wider range of applications. Transformer excel at learning global information but are hindered by their quadratic complexity. The recently proposed State Space Model (SSM), Mamba, offers a promising solution to this issue by enabling global awareness with linear complexity. We consider the vision-language tracking task as a sequence generation task of multimodal tokens and propose an efficient vision-language tracking method, MamTrack. We extend the Mamba block and design an adaptive fusion strategy for Mamba’s different scanning directions to reduce channel redundancy. We introduce the CLIP language model to update text descriptions in real-time, enhancing the robustness of language descriptions in the tracking task. We compare our method with other state-of-the-art approaches on the TNL2K, LaSOT, and OTB99-Lang datasets, where our method achieves leading performance. © 2024 Copyright held by the owner/author(s).

关键词： Visual languages

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A Customizable Virtual Assistant Enhanced with Vision and Speech Capabilities 12th

A Customizable Virtual Assistant Enhanced with Vision and Sp...

引用

12th international conference on Recent Trends in Computing, ICRTC 2024

作者： Christy Jeba Malar, A. Deva Priya, M. Naveen Kumaran, R. Sanjay Abhishek, J. Bhuvana, S. Karthick, S. Department of Information Technology Sri Krishna College of Technology Tamilnadu Coimbatore India Department of Computer Science and Engineering Karpagam College of Engineering Tamilnadu Coimbatore India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Department of Computer Science and Engineering SRM Institute of Science and Technology Uttar Pradesh Delhi–NCR Campus Ghaziabad India

ISBN: (纸本)9789819788354

Recent advancements in Smart Assistants (SAs) as well as home automation have captured the attention of both researchers and consumers. Virtual Assistants (VAs) that are speech-enabled are commonly referred to as smart speakers. They offer a wide range of network-based services. In some cases, they seamlessly link to smart environments, introducing innovative and efficient user interfaces. Nevertheless, these devices present their own set of challenges and limitations. The distinctive features of this technology, particularly its hand-free operation handled by voice and implementation of voice-user interface create a unique landscape. Existing technology adoption models, however, fall short in offering a comprehensive explanation for the adoption of this innovative technology. To gain deeper insights into the motivation behind approving and using in-home voice assistants, this work shifts its focus towards examining voice interactions. Utilization of speech recognition for converting speech into text enables constructing an attractive personalized assistant. This development facilitates seamless tasks such as sending emails without manual typing, conducting Google searches without opening the browser, and accomplishing various daily activities including playing music or launching a preferred IDE, all with a single voice command. To assess its performance, the system is seamlessly integrated with home automation (open-source) environment and operated continuously for some days. During this period, users are encouraged to interact with it, and the results demonstrate increased accuracy, reliability and appeal. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Speech recognition

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Distributed Energy Trading Mechanism Based on Supply-Demand Ratio Pricing and Fair Clearing

Distributed Energy Trading Mechanism Based on Supply-Demand ...

引用

2025 international conference on Electrical automation and Artificial Intelligence, ICEAAI 2025

作者： Wang, Qian Liu, Yitong Xie, Yi Liu, Xingcheng University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada School of Computer Science and Engineering Sun Yat-sen University Guangzhou China School of Electronics and Information Technology Sun Yat-sen University Guangzhou China School of Information and Intelligent Engineering Guangzhou Xinhua University Guangzhou China

ISBN: (纸本)9798331506797

For distributed energy systems, an energy trading mechanism involving shared energy storage is proposed. This mechanism sets the internal transaction price according to the supply and demand of the system, and encourages the producers and consumers to adopt the optimal sharing strategy with the energy suppliers to maximize the system benefits and achieve the optimal social welfare. At the same time, the clearing algorithm based on the ideal profit realization rate is adopted to ensure fairness among participants and improve user satisfaction. The results show that the improved supply-demand pricing mechanism can effectively stimulate the enthusiasm of producers and consumers to participate in the market, and the shared energy storage trading mechanism can significantly improve the social welfare of the system. The clearing scheme based on the ideal profit realization rate can distribute profits according to the contribution degree of prosumers, and ensure the fairness of the system trading mechanism. © 2025 IEEE.

关键词： energy trading fair clearing peer to peer SDR shared energy storage

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A Simulation-Based Security Benchmarking Approach for Assessing Cooperative Driving automation (CDA) Applications 8th

A Simulation-Based Security Benchmarking Approach for Asses...

引用

8th international conference on Intelligent Transport Systems, INTSYS 2024

作者： Malik, Mateen Sangchoolie, Behrooz Karlsson, Johan Dependable Transport Systems RISE Research Institutes of Sweden Gothenburg Sweden Chalmers University of Technology Gothenburg Sweden

ISBN: (纸本)9783031863691

This paper presents our initial contributions toward defining security benchmarks for simulation-based assessment of Cooperative Driving automation (CDA) applications. A security benchmark is a process or procedure for assessing and validating a system’s ability to achieve its operational objectives in the presence of specific security attacks. This work lays the groundwork for developing security benchmarks that assess the robustness of CDA applications against jamming attacks. The driving scenario and the attack model are the core components of our proposed security benchmark. We used two scenarios braking and sinusoidal as a stimulus for evaluating the robustness of a platooning application modeled in a simulation framework called Plexe. The platooning application is equipped with a Cooperative Adaptive Cruise Control (CACC) controller. We injected barrage jamming attacks into the physical layer of the wireless communication system modeled by the IEEE 802.11p protocol. We demonstrate that jamming attacks can compromise safety, leading to emergency braking and collision incidents among platooning vehicles. Our findings also indicate that the severity of jamming attacks varies with the driving scenario, with the most severe impacts (i.e., collisions) occurring when the attack is injected during vehicle acceleration. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Adaptive cruise control

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A survey of IPv6 address scanning techniques 2

A survey of IPv6 address scanning techniques

引用

2nd international conference on Frontiers of Applied Optics and computer engineering, AOCE 2025

作者： Cheng, Xingqi Jing, Shan Jiao, Liang Zhao, Chuan Yang, Hongjuan School of Information Science and Engineering University of Jinan Jinan China National Computer Network Emergency Response Technical Team Coordination Center of China Shandong Branch China Quan Cheng Laboratory Jinan China

ISBN: (纸本)9781510689404

Current scanning techniques are capable of rapidly covering the entire IPv4 address space. However, for the almost endless address space of IPv6, it is impossible to use current scanning techniques to scan for hundreds of millions of years. In recent years, numerous researchers have developed various heuristic based IPv6 address scanning methods to address this issue. These methods effectively reduce the scope of addresses that need to be scanned by utilizing collected initial IPv6 addresses as starting points, and generating a list of potentially active IPv6 addresses to focus on for scanning. This paper systematically categorizes, organizes, and reviews these seed-address-based techniques, and it thoroughly examines the strengths and weaknesses of each algorithm. This paper selects addresses from the latest publicly available dataset, Hitlist, to serve as seed addresses. Through experiments, a comprehensive comparison of 11 address scanning techniques is conducted, and a tool for the automated evaluation of address scanning techniques is developed. © The Authors.

关键词： automation

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A Review on the Use of Smart Agriculture Systems to Protect Crops 3

A Review on the Use of Smart Agriculture Systems to Protect ...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Kumar, Gulshan Gourshettiwar, Palash Suman, Saurabh Kumar, Shravan Kumar, Dhiraj Raushan, Rahul Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha India Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Maharashtra Wardha India

ISBN: (纸本)9798331509675

Smart agriculture systems leverage the possibilities offered by cutting-edge technologies such as IoT, AI, and remote sensing to revolutionize conventional farming by enhancing resource utilization, production, and crop damage mitigation. Real-time monitoring of soil and crop health, predictive analytics, pest control, and precision irrigation measures are all enabled by these systems. They are able to address major Indian agriculture issues, consequently boosting yield and profitability and promoting environmental sustainability. The largescale deployment of intelligent agriculture systems will change the agriculture landscape in India and will assure long-term food security for an ever-growing population. Challenges include adequate research and future studies in order to better install and achieve smart agricultural systems to protect crops. Intelligent agriculture involves all advanced research, including science and innovations, in national development through space technologies to enhance soil quality, conserve water, and facilitate agriculture information. Space ventures will undergo improved modernization through the introduction of crop sprayers, precision gene editors, epigenetics, big data analytics, IoT, wind and photovoltaic smart energy, AI-enabled robotic applications, and wide-scale desalination technologies. Implementing digital farming systems in developing economies will help their sectors as 85 percent of the global population is set to live in developing countries by 2030. automation will prove to be necessary since food scarcity is on the rise along with resource wastage. Control strategies such as the IoT, aerial imagery, machine learning, and artificial intelligence will boost production and prevent soil degradation. These advanced technologies are also able to alleviate such issues as plant disease detection, pesticide management, and water application. The introduction of the Internet of Things in the agricultural research world has started

关键词： Smart agriculture

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Enhancing Energy Efficiency in IoT Networks with AI optimized LEACH Protocol and Digital Twin Simulation 1

Enhancing Energy Efficiency in IoT Networks with AI optimize...

引用

1st international conference on Advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Harinaiha, Adarsha Chaudhary, Pavan Faculty of Engineering and Technology Department of Mechanical Engineering Ramnagar District Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331518578

The convergence of the Internet of Things (IoT) via artificial intelligence (AI) will undoubtedly revolutionize networking. IoT is a technological paradigm shift facilitating the incorporation of many applications, including smart homes and wearable gadgets, via automation, wireless sensors, and embedded systems. Furthermore, the production of AI enhances this phenomenon by delivering data-driven insights, streamlining procedures, and creating new avenues for development. The extensive implementation of devices in Internet of Things (IoT) networks has raised worries over escalating energy usage. Utilizing environmentally friendly techniques is crucial to maintain network service for nodes that sense with limited power supplies. One approach that substantiates this assertion is LEACH, an acronym for Low Energy Adaptive Clustering Hierarchy. The objective of this form of communication is to optimize the transfer of information to base sites by successfully configuring clusters within networks and executing real-time adjustments across cluster nodes. This work enhances the effectiveness of IoT systems by using a virtual twin simulation to optimize the protocol known as LEACH. Employ artificial intelligence analysis and virtual network models to evaluate power consumption and efficiency. Cache nodes are essential in this architecture since they receive information from the cluster's head & transmit it through the main hub. Utilizing simulation tools and artificial intelligence, we can enhance the reliability and energy efficiency of IoT devices. The results indicate an 84% decrease in inactive nodes & a 1.67-fold rise in node energy use relative to traditional methods. The present study suggests a prospective future trajectory for LEACH-based, AI-augmented, low-power IoT infrastructure. © 2025 IEEE.

关键词： Energy utilization

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Boosting Software Quality: A Machine Learning Technique for Predicting Defects 6

Boosting Software Quality: A Machine Learning Technique for ...

引用

6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Akilan Daniel, E. Alwin Infant, P. Jainish, G.R. Panimalar Engineering College Chennai City Campus Chennai India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Loyola ICAM College of Engineering & Technology Chennai India

ISBN: (纸本)9798331522667

In order to increase automation, strengthen decision- making, and improve efficiency while reducing costs and maintaining precision, the development of intelligent machinery is becoming more and more dependent on the integration of data, embedded software, and modern technologies. Reliability of embedded software becomes essential for guaranteeing high system performance and an improved user experience as technology and hardware merge to build smart devices. This work explores methods to quantify software reliability, which measures the likelihood of residual failures in a system. The objective is to build a statistical relationship between quality parameters and product or process metrics through the analysis of software metrics produced from development data. These indicators aid in evaluating the software's dependability and performance, enabling developers to spot and fix possible problems early on. Using pattern recognition algorithms to pinpoint software's fault-prone areas is a crucial strategy for enhancing software reliability prediction. These algorithms enable developers to focus attention on software areas that have a higher likelihood of failure by identifying patterns in the product's code or structure that suggest increased risk. In summary, these methods focus on enhancing the reliability of intelligent machines by equipping developers with advanced tools to reduce defects, improve dependability, and ensure that smart systems perform optimally. This approach aligns with modern trends in using machine learning and data-driven models to tackle complex technological challenges. © 2025 IEEE.

关键词： Data reliability

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Automated Intracerebral Hemorrhage Detection in CT Images Using InceptionResNetV2 24

Automated Intracerebral Hemorrhage Detection in CT Images Us...

引用

8th international conference on Electronic Information Technology and computer engineering, EITCE 2024

作者： Liu, Ying Zhong, Suixi Hao, Mingjiao Huang, Junsheng School of Medicine Hainan Vocational University of Science and Technology Hainan Haikou China School of Information Engineering Hainan Vocational University of Science and Technology Hainan Haikou China

ISBN: (纸本)9798400710094

Intracerebral hemorrhage (ICH) is a common cerebrovascular disease with a high mortality rate, making accurate and timely identification crucial. This paper introduces a machine learning-based model for detecting ICH from brain CT images, aimed at improving the automation and accuracy of medical image diagnostics. The model leverages a InceptionResNetV2 as the feature extraction network, combined with global average pooling, dropout, and fully connected layers tailored for binary classification tasks. Experimental results show that the model achieves an accuracy of 0.9733 on the validation set and 0.9200 on the test set. The loss rates are 0.1644 and 0.1567, recall rates are 0.9864 and 0.9623, F1 scores are 0.9638 and 0.9273, and AUC values are 0.9972 and 0.9889 for the validation and test sets, respectively. These metrics indicate the model’s strong generalization capability. Additionally, a user interface was developed to predict the probability of ICH in brain CT images, providing an effective tool for automated detection. This tool holds promise in assisting clinicians with rapid and accurate diagnostic decisions. © 2024 Copyright held by the owner/author(s).

关键词： computerized tomography

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A Smart Irrigation System for Coconut Farming using IoT 3

A Smart Irrigation System for Coconut Farming using IoT

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Russia, S. Mohanapriya, B. Gowrishankar, V. Parimala Devi, M. Pradeep, K.K. Brindha, P. Velalar College of Engineering and Technology Department of Computer Science and Engineering India Velalar College of Engineering and Technology Department of Electronics and Communication Engineering Erode India Erode Sengunthar Engineering College Department of Electronics and Communication Engineering Erode India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509675

Coconut farming is an essential agricultural practice that contributes significantly to the global economy by providing valuable products such as coconut water, oil, and meat. However, the management of coconut plantations faces numerous challenges, including labor shortages, pest control, and the demand for precise irrigation and fertilization. This paper proposes an integrated smart farming system that leverages advanced sensor technologies and automation to address these challenges. The system employs precision irrigation and fertigation methods, facilitated by a centralized motor controller and solenoid valves, to deliver water and nutrients efficiently to the base of each coconut tree. A pH sensor monitors soil acidity or alkalinity, ensuring optimal nutrient availability and promoting sustainable farming practices by reducing chemical inputs. Additional features include a tree motion sensor and a tilt sensor for monitoring tree stability under adverse weather conditions. Soil moisture sensors, temperature, humidity, and light intensity sensors provide real-time data to enhance decision-making. Farmers can remotely monitor and control the system via a Node-RED dashboard, receiving alerts through platforms like Telegram. By integrating these technologies, the proposed system aims to optimize resource utilization, enhance crop yield, and reduce the environmental impact of coconut farming. © 2025 IEEE.

关键词： Soil moisture

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