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SIFT-Guided Saliency-Based Augmentation for Weed Detection in Grassland Images: Fusing Classic computer Vision with Deep Learning 1

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14th International Conference on computer Vision Systems (ICVS)

作者： Schmidt, Patrick Guldenring, Ronja Nalpantidis, Lazaros Tech Univ Denmark Dept Elect & Photon Engn Lyngby Denmark

ISBN: (数字)9783031441370

ISBN: (纸本)9783031441363;9783031441370

Weed detection is a challenging case within object detection as the weed targets do not generally strike out from the background in terms of color. This paper investigates how the density of structural features can be used to assist the training process of a Deep-Learning-based object detector. SIFT keypoint density is used to create overlay masks to augment images, emphasizing low-density areas-typically corresponding to weed plants. Our method is shown to improve detection mAP. 5:.05:.95 on the YOLOR-CSP detector by up to 0.0215.

关键词： Image Augmentation Weed Detection YOLO

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Harmony in Hierarchy: Mixed-Initiative Music Composition Inspired by WFC 23rd

Harmony in Hierarchy: Mixed-Initiative Music Composition In...

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23rd IFIP TC 14 International Conference on Entertainment Computing, ICEC 2024

作者： Varga, Pál Patrik Bidarra, Rafael Delft University of Technology Delft Netherlands

ISBN: (纸本)9783031743528

Music has an important, but often subsidiary, role in most games and interactive experiences. Efforts to make generative music more accessible can potentially help numerous indie developers and designers. In this paper we explore the extension and application of the Wave Function Collapse (WFC) algorithm in the realm of music. Recognizing music’s inherent complex, layered structure, we investigate the feasibility of adapting WFC, a method broadly used in procedural content generation, to handle musical semantics in a mixed-initiative setting. Our approach introduces a novel generative method utilizing multiple canvases and constraints, each defined with specific musical significance. At each level, new constraints are specified that influence the generator at the next levels. This approach is particularly fitting to capture the layered structure and complex patterns inherent to music, and it encourages a mixed-initiative, iterative composition process. We also provide a prototype implementation of the proposed algorithm in ProceduraLiszt, a declarative music editor designed to offer composers a platform for exploring highly-controllable generative composition. The effectiveness and creativity-support facilitated by this experimental setup are under evaluation and will be detailed in a future publication. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： computer music

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Extracting Tuple-Based Service Demands with Large Language Models for Automated Service Composition 21st

Extracting Tuple-Based Service Demands with Large Language ...

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21st International Conference on Services Computing, SCC 2024, Held as Part of the Services Conference Federation, SCF 2024

作者： Hsu, Chih-Jung Luo, Yu-Xiang Mao, Yi-Chen Wang, Chien-Min Syu, Yang Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Information Science National Taipei University of Education Taipei Taiwan

ISBN: (纸本)9783031769993

Existing Automated Service Composition (ASC) approaches typically require inputs to be in a designated form. These, namely tuples, pose challenges due to the significant divergence from the most commonly used and straightforward formats for expressing software requirements. In our previous work, we developed a rule-based approach that necessitated substantial resources for analyzing the content of requirements and establishing appropriate rules. Given the recent successes in field research involving large language models (LLMs)-where significant achievements have been made in real-time automatic text generation tasks-we propose leveraging LLMs for ASC to extract critical tuple-based information. We have created a new dataset to simulate everyday service demands and have established clear guidelines regarding service demand types (e.g., input and output). Moreover, we have implemented an appropriate workflow that optimizes LLMs performance. Our experiments and results demonstrate that our proposed LLMs-based approach not only achieves extraordinary performance and reliability at a lower cost but also outperforms the complex rule-based solutions that were previously employed. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Modeling languages

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Cluster-Mined Negative Samples for Enhanced Unsupervised Sentence Representation Learning 27th

Cluster-Mined Negative Samples for Enhanced Unsupervised Sen...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Zhang, Yuhang Zhang, Wenjie Hua, Yang Wang, Zun Song, Xiaoning Wu, Xiao-Jun School of Artificial Intelligence and Computer Science Jiangnan University Wuxi214122 China Biotechnology Co. Ltd. Suzhou215000 China

ISBN: (纸本)9783031783944

Negative samples selection for contrastive learning is considerable in the field of sentence representation, especially for semantic textual similarity. Traditional in-batch negative sampling methods not only lack hard negative samples but also ignore potential false negative samples. Despite numerous methods trying to improve traditional sampling strategies, the challenge of consistently generating high-quality negative samples remains untackled. To address this pivotal issue, we propose the Cluster-Mined Negative Samples for Enhanced Unsupervised Sentence Representation Learning (CMNS) framework. Specifically, dynamic queues are utilized to store the K-means cluster samples, enabling the most appropriate selection of clusters to serve as negative samples. Additionally, we generate noise-based negative samples via stored clusters while simultaneously constraining potential false negative samples. Above all, CMNS employs clustering techniques to efficiently mine sufficient quantity of high-quality negative samples from unlabeled datasets. Extensive experiments illustrate that our approach not only overcomes the inherent limitations of traditional sampling methods but also improves the performance of sentence representations in downstream tasks, demonstrating measurable advancements over current methodologies. (codes and models are available at https://***/hamrain/CMNS). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

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Brief Announcement: Understanding Self-stabilizing Node-Capacitated Overlay Networks Through Simulation 1

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25th International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS 2023

作者： Afeaneku, Winfred Berns, Andrew Kuchenberg, Weston Leisinger, Sara Liu, Cedric Department of Computer Science University of Northern Iowa Cedar FallsIA United States Cedar Falls High School Cedar FallsIA United States

ISBN: (数字)9783031442742

ISBN: (纸本)9783031442735

Overlay networks, where connections are made over logical links composed of zero or more physical links, are a popular paradigm in modern distributed computing. The use of logical links allows the creation of a variety of network topologies with desirable properties such as low degree and low diameter, regardless of the (usually) fixed physical topology. Many of these overlay networks operate in unfriendly environments where transient faults are commonplace. Self-stabilizing overlay networks present one way to manage these faults. In particular, self-stabilizing overlay networks can guarantee that the desired network topology is created when starting from any weakly-connected initial state. To date, work on self-stabilizing overlay networks has assumed the network has either unbounded bandwidth, or that the bandwidth constraints are placed on the communication links themselves. In practice, however, the bandwidth constraints are actually capacities on the nodes: adding and deleting logical links does not change the fixed physical links being used. In this work, we describe the node-capacitated model for self-stabilizing overlay networks. To better understand this new model, we created a simulation and ran it numerous times while adjusting various parameters. We discuss this simulation and several experiments. Finally, we propose future directions for self-stabilizing node-capacitated overlay networks. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Overlay networks

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Bridging the Gap: Infusing Natural science Classes with computer science Concepts and Skills 16th

Bridging the Gap: Infusing Natural Science Classes with Comp...

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16th International Conference on Informatics in Schools - Situation, Evolution, and Perspectives (ISSEP)

作者： Yanakieva, Elena Bieniusa, Annette Becka, Thomas Moser, Brian B. Jerger, Dominik Thyssen, Christoph Univ Kaiserslautern Landau Kaiserslautern Germany German Res Ctr Artificial Intelligence DFKI Kaiserslautern Germany Eduard Spranger Gymnasium Landau Germany

ISBN: (纸本)9783031448997;9783031449000

As we venture further into an ever-evolving digital society, it has become imperative for schools to adapt and equip future generations with the required skills. Computational Thinking (CT), specifically its algorithmic thinking aspect, plays a significant role in computer science and other sciences, such as biology, chemistry, and physics. It encourages students to reason at multiple levels of abstraction. This ability is particularly useful in natural science, as scientific experiments require critical skills like conceptualization, problem decomposition, and solving or designing structured systems. However, due to organizational and curricular restrictions, these concepts and skills are typically taught separately, leaving it to the learners to connect and apply the acquired skills in the respective context. To bridge this gap, we designed a two-day workshop that embeds CT in a physics and sustainability context, namely energy-efficient housing. In this workshop, we employ the Calliope Mini, a micro-controller explicitly designed for educational purposes, to teach essential algorithmic thinking and data processing. We carried out the workshop twice in a primary school in Germany, each with 20 children in 4th grade (ages 9-10). In this experience report, we present the multi-disciplinary workshop idea and discuss the outcome and observations from its execution. Overall, our study demonstrates the potential of such a workshop design as a practical tool for teaching CT concepts to children. Finally, we critically examine the challenges of this approach and highlight the importance of proper technical and educational prerequisites for a successful implementation.

关键词： Computational Thinking STEM algorithmic thinking multi-disciplinary teaching

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Visual Sensor Layout Optimization of a Robotic Mobile Adhesive Removal System for Wind Turbine Blade Based on Simulation 1

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16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Peng, Bo Zheng, Feifan Zhang, Fan Ming, Shilin Li, Yan Deng, Xutao Gong, Zeyu Tao, Bo DEC Academy of Science and Technology Co Ltd. Chengdu611731 China Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

In the manufacturing process of wind turbine blades, residual adhesive may overflow after the mold closing of the blades. The overflowing residual adhesive may cause damage to the inside of the wind turbine blades when the blades are in motion during operation. To address this, an adhesive removal robot capable of identifying and removing residual adhesive was designed. The robot is equipped with a vision system that enables adhesive recognition and guides the adhesive removal mechanism. Given the lack of precedents and the complexity of the robot's functions, it was necessary to streamline the development process and optimize the design scheme of the vision system to reduce costs and shorten development cycles. Therefore, a simulation environment using Gazebo was constructed to evaluate different design schemes for safety and effectiveness, and finally the optimization of the sensor layout scheme was realized. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Adhesives

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A Tactical Planning Process in computer-Generated Forces Team Behavior Within Air Combat Simulations: Concept and First Implementations 10th

A Tactical Planning Process in Computer-Generated Forces Tea...

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10th International Conference on Modelling and Simulation for Autonomous Systems

作者： Reinisch, Fabian Strohal, Michael Stuetz, Peter Univ Bundeswehr Munich Inst Flight Syst Werner Heisenberg Weg 39 D-85577 Neubiberg Germany

ISBN: (纸本)9783031713965;9783031713972

Due to a rising number of entities and more advanced systems, modern air combat engagements are increasing in complexity. Therefore, to ensure success in pilot training and perform accurate threat evaluation using simulations, it is substantial to not only replicate and simulate the physical properties of the computer-Generated forces (CGFs) to an adequate degree but also to provide them with sufficiently realistic, coordinated and situation-adaptive behavior. Additionally, most air combat research assumes that all aircraft information is known, however, in real-world scenarios, multiple factors, such as sensor performance limitations, can lead to missing or incorrect information about the position, altitude, or velocity of adversary aircraft. In this paper, we propose a Tactical Planning Process as part of an overarching CGF Team Behavior Agent Function utilizing information such as threat risk and the enemy's intent from a Situation Analysis created with realistically available data. This process is partitioned into two stages, Team Planning and Maneuver Selection. Team Planning consists of deciding whether the mission itself should be commenced or aborted, selecting Tactics to counter the threats, as well as performing a Targeting in which threat aircraft are assigned to the individual CGFs. Further, in Maneuver Selection, the own current risks are assessed and used to continuously decide the current task for each CGF with respect to its target. Following, the maneuver command itself is being selected and sent to the simulated aircraft. This is done within an evaluation of the own chances and risks by, in a first step, identifying suitable tactical maneuver types, in a second step, narrow down their parameters, so that, in the final step, predicted risks from the Situation Analysis can be incorporated in the selection process as well. We employ Behavior Trees to guide the CGFs through these different tasks, while repeatedly assessing the developing risks to be ab

关键词： computer Generated Forces Behavior Modeling Tactical Planning Air Combat Pilot Training Threat Evaluation Behavior Trees

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Vayu Vishleshan: AQI Monitoring and Reduction Analysis 11th

Vayu Vishleshan: AQI Monitoring and Reduction Analysis

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11th International Conference on Big Data Analytics in Astronomy, science, and Engineering (BDA)

作者： Khare, Mayank Deep Sachdeva, Shelly Dubey, Divyam Rajpoot, Rohit Singh Kumar, Saurav Natl Inst Technol New Delhi India

ISBN: (纸本)9783031585012;9783031585029

In today's life, humans compromise with nature while evolving into a more advanced species. One of the main effects of that advancement is air pollution. Air pollution seriously threatens human health, the environment, and the general quality of life worldwide. A quantitative analysis of air quality was the purpose of developing the Air Quality Index (AQI), an indexing approach. The air quality index is computed usingmeasurements for particulatematter (PM), PM2.5, PM10, NO2, CO, CO2, NH3, and other contaminants. Agnihotra (Yagya) is a method of environmental purificationmentioned in the Hindu sculpture (TheBook Yagya Vimarsh, written by Dr. Ramprakash, talks about the air pollution reduction method). This paper discusses the Vayu Vishleshan framework for monitoring air quality in the presence of Agnihotra (Yagya). This study is divided into two processes. The first one is AQI monitoring, and the second is AQI reduction. AQI Monitoring covers sensing particulate matter (PM), PM2.5, PM10, NO2, and CO and performing analysis over theAQI data before, during, and following Agnihotra (Yagya). According to analysis, there is an approximate 6-7% decrease in CO levels and an approximate 10-12% decrease in PM levels following Agnihotra.

关键词： AQI Particulate matter (PM) Agnihotra Air Quality Index Vedic science

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An Empirical Study of Leveraging PLMs and LLMs for Long-Text Summarization 21st

An Empirical Study of Leveraging PLMs and LLMs for Long-T...

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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Jiang, Zhihua Yang, Junzhan Rao, Dongning Department of Computer Science Jinan University Guangzhou510632 China School of Computer Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9789819601189

Despite the impressive ability offered by pre-trained language models (PLMs) and large language models (LLMs), these models still face the challenges of the long-text summarization (LTS) task. On the one hand, due to the max input-length, PLMs adopt simple truncation or salience analysis for extracting part of sentences from the original input, leading to possible information loss. On the other hand, despite no limits on input length, the summaries generated by LLMs often introduce irrelevant information, leading to great gap between prediction and reference. To this end, this paper proposes a hybrid long-text summarization model, PLLM-TS (Leveraging PLMs and LLMs for Long-Text Summarization), which combines the advantages of both PLMs and LLMs. PLLM-TS is a pipeline composed of two modules. The first module is an extractive summarization model (e.g., BERTSum) enhanced with combined attention ideas. And the second module is a switching generative summarization model, dependent on the number of extracted sentences from the first module. Specifically, when the sentence number is bigger, we apply a PLM-based summarization model (e.g., Pegasus) to generate a summary from extracted sentences. By contrast, when the sentence number is smaller, we utilize a LLM-based summarization model (e.g., GPT-2) to rewrite extracted sentences into a shorter and more concise summary. We experiment with two public academic-paper datasets: arXiv and PubMed, showing the effectiveness and superiority of our method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Modeling languages

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