检索结果-内蒙古大学图书馆

Safe Return Home Solution Using a Smart Drone Scout

Journal of Institute of Control, Robotics and Systems 2024年第9期30卷 937-944页

作者： Heo, Hyeonjeong Lee, Hojun Lee, Kyuman Department of Robot and Smart System Engineering Kyungpook National University Korea Republic of School of Computer Science and Engineering Kyungpook National University Korea Republic of School of Space Engineering Sciences Kyungpook National University Korea Republic of

The women's safe return home service is short on operating hours and manpower. To address this social issue, this paper proposes an unmanned solution using a smart drone. When a user calls this system, it generates an initial safe path based on data from electronic tag wearers (i.e., obstacles) and map information. As the obstacles move, the safe path is re-planned to avoid them. The smart drone tracks and monitors the users returning home along the planned safe path at a certain distance and angle in real time. Since the raw GPS data from the user's app are unreliable, these are corrected to map-matching points for the drone to determine the points to track. Moreover, the smart drone identifies corners to avoid losing the monitored field of view at corners and adjusts its tracking accordingly. Flight test results validate the overall functionality and performance of the proposed solution, i.e., the proposed system improves user safety by effectively minimizing contact with electronic tag wearers while maintaining a certain distance and angle from the user by controlling the direction and speed of the drone. © ICROS 2024.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Generating Better Responses from User Feedback via Reinforcement Learning and Commonsense Inference 12th

Generating Better Responses from User Feedback via Reinfor...

引用

12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023

作者： Cai, Mingxiu Wang, Daling Feng, Shi Zhang, Yifei School of Computer Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9783031446986

Dialogue generation task is one of the popular research topics in the field of natural language processing. However, how to improve the quality of model generated responses with the user feedback in the dialogue generation task is still one of the difficulties in the research. In this paper, we propose a dialogue generation method based on user feedback by modeling the likeability of user feedback and optimizing the model by using Reinforcement Learning from Human Feedback (RLHF) techniques to generate more likeable responses to users. We also introduce commonsense inference to help the model better understand the knowledge context and user intent. Finally, we used contrastive search in the decoding stage to make the generated responses more diverse. To verify the effectiveness of the model, we conducted some experiments and compared our model with the baseline models. The experiment results show that our approach outperforms the baseline models in terms of automatic evaluation. The final evaluation results show that our model ranks 2nd in the NLPCC 2023 Shared Task 9 Track 2. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Node Coverage and Connectivity Optimization in Heterogeneous Wireless Sensor Networks Using Improved Flower Pollination Algorithm 4

Node Coverage and Connectivity Optimization in Heterogeneous...

引用

4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Mahankali, Saritha Kesavan, R. Kalaiselvan, S.A. Saveetha School of Engineering Simats Department of Computer Science & Engineering Chennai India Vardhaman College of Engineering Department of Computer Science & Engineering Telangana India Rajalakshmi Engineering Department of Artificial Intelligence & Machine Learning Chennai India

ISBN: (纸本)9798331529635

Wireless sensor networks (WSNs) rely on energy-conserving routing protocols due to the limited power and communication capabilities. The LEACH protocol has seen extensive usage despite its homogeneous network foundation, leads inadequate signal coverage. To solve the issue, this research proposes an improved flower pollination algorithm (IFPA) improves flower pollination algorithm (FPA) addresses issues with slow convergence and local optima. This research presents an enhanced clustering technique that may be utilized in heterogeneous sensor networks. Its main feature is the ability to adjust the status of data transmission. Once the observed information intensity above the predefined threshold, the data transmission connection is initiated and data is sent to the sink by the cluster heads, which filter the perceived information. Otherwise, cluster nodes keep track of the data and wait for the next batch of nodes to provide data. The good news is that the simulation results show a network lifespan that is several times longer than the LEACH protocol. The IFPA method stands out because it increases coverage rates while drastically decreasing the cost of deploying networks. As a result, the suggested method might find many uses, helping to lower costs and improve the performance of wireless sensor networks. © 2024 IEEE.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

Zero-Shot Event-Intensity Asymmetric Stereo via Visual Prompting from Image Domain 38

Zero-Shot Event-Intensity Asymmetric Stereo via Visual Promp...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Lou, Hanyue Liang, Jinxiu Teng, Minggui Fan, Bin Xu, Yong Shi, Boxin State Key Laboratory of Multimedia Information Processing School of Computer Science Peking University China National Engineering Research Center of Visual Technology School of Computer Science Peking University China National Key Laboratory of General AI School of Intelligence Science and Technology Peking University China School of Computer Science and Engineering South China University of Technology China

Event-intensity asymmetric stereo systems have emerged as a promising approach for robust 3D perception in dynamic and challenging environments by integrating event cameras with frame-based sensors in different views. However, existing methods often suffer from overfitting and poor generalization due to limited dataset sizes and lack of scene diversity in the event domain. To address these issues, we propose a zero-shot framework that utilizes monocular depth estimation and stereo matching models pretrained on diverse image datasets. Our approach introduces a visual prompting technique to align the representations of frames and events, allowing the use of off-the-shelf stereo models without additional training. Furthermore, we introduce a monocular cue-guided disparity refinement module to improve robustness across static and dynamic regions by incorporating monocular depth information from foundation models. Extensive experiments on real-world datasets demonstrate the superior zero-shot evaluation performance and enhanced generalization ability of our method compared to existing approaches. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Abstractive Multi-Document Summarization: Exploiting Maximal Marginal Relevance and Pretrained Models 14

Abstractive Multi-Document Summarization: Exploiting Maximal...

引用

14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Zeyad, Abdulrahman Mohsen Ahmed Biradar, Arun Reva University School of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350335095

The increasing demand for effective multi-document summarization (MDS) due to the rapid expansion of information availability has triggered this investigation. Focused on the fusion of Maximal Marginal Relevance (MMR) with pretrained models, we circumvented the often-cumbersome fine-tuning process, and introduced a novel methodology. We applied this to various text datasets like Multi-News and WCEP, and it resulted in significant improvement of ROUGE scores, illustrating promising results. For example, the ROUGE-1 score of our method on the Multi-News dataset was 46.23, and the ROUGE-1 score on the WCEP dataset was *** this discussion, the research implications, including better n-gram optimization and model selection strategies, were brought forward. This study had substantial implications for natural language processing, propelling us toward more advanced text summarization applications, presenting potential avenues for future research, such as refining the role of n-grams in summaries and optimizing model selection processes. © 2023 IEEE.

关键词： Text processing

来源：评论

学校读者我要写书评

暂无评论

Performance of Null Handling in Array Databases

Performance of Null Handling in Array Databases

引用

2023 IEEE International Conference on Big Data, BigData 2023

作者： Misev, Dimitar Rodionychev, Mikhail Baumann, Peter Constructor University School of Computer Science & Engineering Bremen Germany

ISBN: (纸本)9798350324457

Array databases specialize in storage, management, and query processing on massive multidimensional array data such as satellite image time-series, weather forecast models, IoT sensor measurements, medical imaging data, etc. Some of the values in this data may be 'null' for a variety of reasons, such as unknown, known false, etc. The DBMS must handle null values correctly and efficiently. As of today, the effects of different data structures for representing null values on query processing in array databases have not been systematically studied. As a consequence, it is not clear what the optimal way for handling null values is. In this paper, we measure how four different methods for encoding null values perform across most common categories of array operations. The result is a comprehensive overview, publicly available in open source, providing relevant insights into the performance characteristics of these data structures allowing to discern which among them offers the most optimal approach for representing null values in an array processing context. © 2023 IEEE.

关键词： array databases null values performance benchmark

来源：评论

学校读者我要写书评

暂无评论

SSM: Semantic Selection and Multi-view Alignment for Image-Text Retrieval 9th

SSM: Semantic Selection and Multi-view Alignment for Image...

引用

19th International Conference on Advanced Data Mining and Applications, ADMA 2023

作者： Yu, Beiming Yang, Zhenfei Yi, Xiushuang Wang, Yu Bao, Zhangjun School of Computer Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9783031466731

Image-text retrieval has been a crucial and fundamental task in multi-modal field. Benefiting from the superiority of Transformer encoder in modeling multimodal information, the Transformer-based alignment model has become the mainstream of image-text retrieval. However, current Transformer-based alignment models suffer from two major limitations: (1) The redundancy of modal features and the complexity of correlations between modalities restrict the performance of the model. (2) Current researches are typically limited to a single viewpoint during the modal alignment. To address these issues, in this paper we propose a image-text retrieval model SSM based on Semantic Selection and Multi-view alignment. Specifically, we introduce a gated attention unit to filter unnecessary information, and design an adaptive weighted similarity calculation method to dynamically adjust the importance of different features during the alignment process. On the other hand, we design a multi-view cross-modal alignment method that considers different granularity and different level of information to provide complementary benefits in representation learning. We compare SSM with other advanced image-text retrieval models in MS-COCO and Flickr30K datasets, and the results show that the SSM model has competitive performance without much interaction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Approach to Multi Model Speech Emotion Recognition System 3

Comprehensive Approach to Multi Model Speech Emotion Recogni...

引用

3rd IEEE International Conference on Intelligent Technologies, CONIT 2023

作者： Chethan, V. Bhaskar Reddy, P.V. REVA University School of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350338607

Human-Robot Interfaces have made it possible for robots to learn how to communicate with people and understand their feelings. Robotic dogs, for instance, should be able to comprehend not just verbal orders, but also other information, such as the emotional and physical state of its human commander, and adjust their behavior appropriately. The goal of this article is to learn how to recognize the feelings conveyed by a speaker's tone of speech. In today's world, detecting emotions has become an important task. When people speak in fearful, angry, or joyful emotions, their pitch range tends to be higher and broader, while their pitch range is lower when expressing these emotions. To learn both short-and long-term correlations in the log, a convolutional neural network (CNN) with four local feature-learning blocks and an LSTM layer can be utilised. This deep learning model is built using the Mel-spectrogram of the input audio recordings [1]. The audio characteristics MFCC, MEL, Chroma, and Tonnetz, as well as the Support Vector Machine and Multilayer Perception, were used in this study to identify different emotional states [4]. The audio files used by the algorithm are those found in the RAVDESS dataset, which is publicly available online. The system's effectiveness, which is the desired Outcome, will next be determined by analyzing the audio recordings' spectrograms in WAV format. [5]. © 2023 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Rapid Video Deduplication based on Global & Local Features using Convolution Neural Network 2

Rapid Video Deduplication based on Global & Local Features u...

引用

2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023

作者： Singh, Suraj Kavitha, J.C. School of Computer Science and Engineering REVA University Bengaluru India

ISBN: (纸本)9798350347982

Video deduplication faces significant difficulties because of the large video data explosion. In recent years, deduplication algorithms have made encouraging strides, particularly with the aid of binary hashing techniques. However, research on the general hash-based architecture and the effective similarity ranking technique for video deduplication has been sparse up to this point. The existing hashing techniques finds duplication of videos in the form of binary hash at file level i.e., entire video (Global feature comparison). The proposed research focuses on developing a versatile and quick video deduplication methodology which checks duplication of videos at frame level (Local feature Comparison). If the input video is not entirely duplicated (global feature extraction), the video is then divided into frames to check duplication at frame level. To achieve this, the power of Deep Learning is exploited, using CNN, and a distinct compressed representation for each frame is produced, there are a little over 1000 features extracted for every frame and stored locally. The performance of the proposed methodology is measured using the Euclidean distance measure, that calculates the distance between the pre-trained data and the query video. The goal of the proposed local feature extraction is to assess the number of duplicate frames over the entire video. The proposed approach achieves an accuracy of 95.6% in finding out the number of duplicate frames and it has been concluded that it performs the best when compared with other state-of-art algorithms. © 2023 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

IoT Based ECG Monitoring and Detection System Using Pan-Tompkins Algorithm and Ubidots Cloud

IoT Based ECG Monitoring and Detection System Using Pan-Tomp...

引用

2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Pasha, Afroz Nagaraja, S.R. Presidency University School of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350317060

The Internet of Things (IoT) has revolutionized the healthcare industry by enabling real-time monitoring of patient vital signs. Electrocardiogram (ECG) monitoring plays a crucial role in diagnosing cardiac abnormalities. In this research article, we propose an IoT-based ECG detection system that utilizes the Pan-Tompkins algorithm for accurate and reliable ECG signal processing. The system enables remote monitoring of ECG signals, facilitating early detection of cardiac anomalies and timely intervention. This article presents the design, implementation, and evaluation of the proposed IoT-based ECG detection system, highlighting its effectiveness and potential impact on healthcare. This paper illustrates the implementation of Internet of Things (IoT) technology in the healthcare domain, focusing on a proposed system for remotely monitoring the ECG of patients. The system's key components include the Arduino Uno, an ECG Sensor, and an IoT Cloud for real-time storage and visualization of ECG data. The primary goal of the system is to accurately measure the heart rate of distant patients and facilitate continuous monitoring of their ECG signals from a remote location. © 2023 IEEE.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：