检索结果-内蒙古大学图书馆

1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Aeri, Manisha Yadav, Satya Prakash Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin Nicosia10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Mersin10 Turkey Graphic Era Hill University Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

The basic goal of the IoT is to permit the online connection and communication of everyday physical objects like appliances, vehicles, and other gadgets. This paves the way for effortless and automated data collection and exchange, as well as interaction between the objects themselves and with humans. The Internet of Everything (IoE) is an expansion of the Internet of Things (IoT) that aims to maximize and improve human life by connecting and making the most of all available resources (humans, information, and technology). The transportation, healthcare, agricultural, energy, and manufacturing sectors are all examples. The IoIT aims to incorporate AI and ML within the IoT's interconnected network of physical items. These objects can then independently behave in response to the information they have gathered and the instructions they have been given. This has the potential to lead to smarter, more efficient systems that can react to new information and human input in real time. The Internet of Things, the Internet of Everything, and the Industrial Internet of Things all have the same overarching goal: to pave the way for the development of more efficient and intelligent systems and processes that can enhance a wide range of human endeavors. However, in order to make sure that these technologies are used in a responsible and ethical way, it will be necessary to carefully analyze their consequences and the issues they provide. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Bilateral-Head Region-Based Convolutional Neural Networks: A Unified Approach for Incremental Few-Shot Object Detection

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4376-4390页

作者： Li, Yiting Zhu, Haiyue Tian, Sichao Ma, Jun Xiang, Cheng Vadakkepat, Prahlad National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore Singapore Institute of Manufacturing Technology Agency for Science Technology and Research 138634 Singapore Peking Union Medical College Institute of Medicinal Plant Development Chinese Academy of Medical Sciences Beijing100193 China Robotics and Autonomous Systems Thrust Guangzhou511453 China The Hong Kong University of Science and Technology Division of Emerging Interdisciplinary Areas Hong Kong SAR Hong Kong Hkust Shenzhen-Hong Kong Collaborative Innovation Research Institute Shenzhen Futian518045 China

Practical object detection systems are highly desired to be open-ended for learning on frequently evolved datasets. Moreover, learning with little supervision further adds flexibility for real-world applications such as autonomous driving and robotics, where large-scale datasets could be prohibitive or expensive to obtain. However, continual adaption with small training examples often results in catastrophic forgetting and dramatic overfitting. To address such issues, a compositional learning system is proposed to enable effective incremental object detection from nonstationary and few-shot data streams. First of all, a novel bilateral-head framework is proposed to decouple the representation learning of base (pretrained) and novel (few-shot) classes into separate embedding spaces, which takes care of novel concept integration and base knowledge retention simultaneously. Moreover, to enhance learning stability, a robust parameter updating rule, i.e., recall and progress mechanism, is carried out to constrain the optimization trajectory of sequential model adaption. Beyond that, to enforce intertask class discrimination with little memory burden, we present a between-class regularization method that expands the decision space of few-shot classes for constructing unbiased feature representation. Final, we deeply investigate the incomplete annotation issue considering the realistic scenario of incremental few-shot object detection (iFSOD) and propose a semisupervised object labeling mechanism to accurately recover the missing annotations for previously encountered classes, which further enhances the robustness of the target detector to counteract catastrophic forgetting. Extensive experiments conducted on both Pascal visual object classes dataset (VOC) and microsoft common objects in context dataset (MS-COCO) datasets demonstrate the effectiveness of our method. © 2020 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

AI-Powered Drone to Address Smart City Security Issues 37th

AI-Powered Drone to Address Smart City Security Issues

引用

37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： Salama, Ramiz Al-Turjman, Fadi Culmone, Rosario Department of Computer Engineering Research Center for AI and IoT AI and Robotics Institute Near East University Nicosia Mersin 10 Nicosia Turkey Artificial Intelligence Engineering Department AI and Robotics Institute Near East University Mersin 10 Nicosia Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Mersin 10 Kyrenia Turkey Computer Science Division School of Science and Technology University of Camerino Camerino62032 Italy

ISBN: (纸本)9783031286933

The idea of a dazzling metropolis has drawn interest from all across the world. New innovations like blockchain, IoT, artificial intelligence, robots, and many other things were added to it. Security is one of the top issues for people living in big cities, and everyone wants to feel completely secure when traveling around every single day. In this research, we will look into how CEOs in affluent cities use and value robots, especially in terms of security. To understand the robot security the board stream, some approaches and intricacies are used. Following that is a discussion of issues with urban security and the application of artificial intelligence to drones as a management tool. The use of cutting-edge technology, such as blockchain, to support smart urban community management is covered in the last part. The smart city idea and all of its benefits for local inspection are supported by robotic use. The idea of thriving urban areas is spreading around the world and is crucial in the context of developing economies. We examined how to leverage cutting-edge technologies in this project to make it feasible. Artificial intelligence, robotics breakthroughs, and blockchain technologies all have significant effects. This research highlights their significance to analysts and how they consider them when assessing prospects. This project will be very beneficial for analysts and experts in a relevant subject. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

A Sentiment Analysis Study of Twitter Users' Reactions to the COVID-19 Vaccine 14

A Sentiment Analysis Study of Twitter Users' Reactions to th...

引用

14th International Conference on Information and Communication Systems, ICICS 2023

作者： Alkhushayni, Suboh Alomari, Zakaria Al-Zaleq, Du'a Yarmouk University Faculty of Information Technology and Computer Science Dept. Information Systems Irbid Jordan New York Institute of Technology Dept. Computer Science VancouverBC Canada Al-Ahliyya Amman University Dept. Robotics and Artificial Intelligence Engineering Amman Jordan

ISBN: (纸本)9798350307870

This study investigates public attitudes towards the COVID-19 vaccine through Twitter data analysis. Using the Twitter API, tweets were collected, preprocessed, and labeled. Features were extracted using the Bag of Words representation, and sentiment analysis was conducted using Text Blob and Vader. Machine learning and deep learning models were trained and tested, revealing that deep learning models achieved the highest accuracy and F1 score. The research underscores the efficacy of machine learning and deep learning in analyzing COVID-19 vaccine-related tweets, shedding light on factors influencing vaccine resistance. These insights are crucial for pharmaceutical companies and public health officials, enabling them to address barriers to vaccine acceptance and enhance the societal benefits of widespread vaccination, contributing to the pandemic's resolution. © 2023 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

InteLiPlan: An Interactive Lightweight LLM-Based Planner for Domestic Robot Autonomy

arXiv

引用

arXiv 2024年

作者： Ly, Kim Tien Lu, Kai Havoutis, Ioannis Oxford Robotics Institute University of Oxford United Kingdom Department of Computer Science University of Oxford United Kingdom

We introduce an interactive LLM-based framework designed to enhance the autonomy and robustness of domestic robots, targeting embodied intelligence. Our approach reduces reliance on large-scale data and incorporates a robot-agnostic pipeline that embodies an LLM. Our framework, InteLiPlan, ensures that the LLM’s decision-making capabilities are effectively aligned with robotic functions, enhancing operational robustness and adaptability, while our human-in-the-loop mechanism allows for real-time human intervention when user instruction is required. We evaluate our method in both simulation and on the real Toyota Human Support Robot (HSR). Our method achieves a 93% success rate in the ‘fetch me’ task completion with failure recovery, highlighting its capability in both failure reasoning and task planning. InteLiPlan achieves comparable performance to state-of-the-art large-scale LLM-based robotics planners, while using only real-time onboard computing. More information about InteLiPlan can be found at the project website: https://***/InteLiPlan. Copyright © 2024, The Authors. All rights reserved.

关键词： Human robot interaction

来源：评论

学校读者我要写书评

暂无评论

Multispectral Registration Algorithm Based on Fusion of Infrared and Color Images 16

Multispectral Registration Algorithm Based on Fusion of Infr...

引用

16th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discover, CyberC 2024

作者： Wan, Teng Du, Shaoyi Zhang, Qiang Qi, Ying Li, Ce Northwest Normal University The College of Computer Science and Engineering Lanzhou China Xi'an Jiaotong University The Institute of Artificial Intelligence and Robotics The College of Artificial Intelligence Xi'an China Lanzhou University of Technology The College of Electrical and Information Engineering Lanzhou China

ISBN: (纸本)9798331506896

Multispectral data fusion is a fundamental research in the fields of artificial intelligence and computer vision, which provides technical support and theoretical basis for remote sensing, autonomous driving, and medical imaging. In this paper, we present a robust registration algorithm to align RGB-D scans. In colored point clouds, limited by the principle of point cloud collection and generation, noise, and outliers are common and may cause registration failure. Therefore, the core of our method is to apply color information and kernel function to remove the influence of noise and outliers on the alignment accuracy. In the beginning, for the first time, we innovatively use the Cauchy kernel as the energy function of the point set registration to assign different weights to inliers, noise, and outliers to maximize their differentiation. Combined with the maximization optimization strategy, noise and outliers are removed to achieve robust registration. Secondly, since RGB-D data contain both shape and color information, the trimmed bidirectional color distance is applied to reduce the probability of noise and outliers being selected as the matching point pairs when establishing the correspondences. Moreover, the overall formulation is solved by the iterative optimization method. Experiments demonstrate that our algorithm is more robust and accurate than previous point set registration algorithms, especially when aligning point sets containing noise and outliers. © 2024 IEEE.

关键词： Image registration

来源：评论

学校读者我要写书评

暂无评论

Deep Depth Estimation from Thermal Image: Dataset, Benchmark, and Challenges

arXiv

引用

arXiv 2025年

作者： Shin, Ukcheol Park, Jinsun Robotics Institute School of Computer Science Carnegie Mellon University PittsburghPA United States School of Computer Science and Engineering Pusan National University Busan Korea Republic of

Achieving robust and accurate spatial perception under adverse weather and lighting conditions is crucial for the high-level autonomy of self-driving vehicles and robots. However, existing perception algorithms relying on the visible spectrum are highly affected by weather and lighting conditions. A long-wave infrared camera (i.e., thermal imaging camera) can be a potential solution to achieve high-level robustness. However, the absence of large-scale datasets and standardized benchmarks remains a significant bottleneck to progress in active research for robust visual perception from thermal images. To this end, this manuscript provides a large-scale Multi-Spectral Stereo (MS2) dataset that consists of stereo RGB, stereo NIR, stereo thermal, stereo LiDAR data, and GNSS/IMU information along with semi-dense depth ground truth. MS2 dataset includes 162K synchronized multimodal data pairs captured across diverse locations (e.g., urban city, residential area, campus, and high-way road) at different times (e.g., morning, daytime, and nighttime) and under various weather conditions (e.g., clear-sky, cloudy, and rainy). Secondly, we conduct a thorough evaluation of monocular and stereo depth estimation networks across RGB, NIR, and thermal modalities to establish standardized benchmark results on MS2 depth test sets (e.g., day, night, and rainy). Lastly, we provide in-depth analyses and discuss the challenges revealed by the benchmark results, such as the performance variability for each modality under adverse conditions, domain shift between different sensor modalities, and potential research direction for thermal perception. Our dataset and source code are publicly available at https://***/view/multi-spectral-stereo-dataset and https://***/UkcheolShin/SupDepth4Thermal. © 2025, CC BY-NC-SA.

关键词： Depth perception

来源：评论

学校读者我要写书评

暂无评论

Entropy-Guided Reinforced Open World Active 3D Object Detection Learning

Entropy-Guided Reinforced Open World Active 3D Object Detect...

引用

2024 China Automation Congress, CAC 2024

作者： Zhang, Haozhe Ma, Liyan Ying, Shihui Institute of Artificial Intelligence Shanghai University Shanghai200444 China School of Computer Engineering and Science School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai200444 China Department of Mathematics School of Science Shanghai University Shanghai200444 China

ISBN: (纸本)9798350368604

Traditional fully annotated closed set 3D object detection methods improve model performance but are impractical in real-world settings due to the emergence of new categories and the complexity of 3D annotations. Open-World Object Detection (OWOD) addresses these issues but relies heavily on manual labeling, which is costly. This paper focuses on open world active learning and proposes an entropy-guided reinforced open world active 3D object detection (EROA). EROA regards active learning as a reinforcement learning problem tailored for open driving scenarios. We use entropy as a reward metric for efficient reinforcement learning. We also leverage knowledge from the 2D domain using object-level large-scale vision-language models to enhance sample selection. Extensive experiments evidence that the proposed EROA meets the dynamic and cost-sensitive requirements of autonomous driving, enabling real-time detection of both known and unknown objects. © 2024 IEEE.

关键词： Active learning

来源：评论

学校读者我要写书评

暂无评论

AI Integrated Dialogic Alphabet Zone Board for Kids in Pre-childhood Education

AI Integrated Dialogic Alphabet Zone Board for Kids in Pre-c...

引用

International Conference on Electrical, computer and Communication Engineering (ECCE)

作者： Asif Mahmud Tahsin Faisal M. Akhtaruzzaman Jamal Uddin Tanvin Sachitra Halder Fahim Shahryer Department of Computer Science and Engineering Military Institute of Science and Technology Dhaka Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

The smart Dialogic Alphabet Zone Board (DAZ-Board) aims to address the issue of learning process for pre-childhood education among the children. It is importance to facilitate a healthy and effective environment for early childhood education in shaping a child’s cognitive development, language acquisition, and literacy skills. Traditional teaching methods often fail to engage young learners effectively, leading to limited understanding and retention. On the other hand, dependencies on mobile devices raise the physical and mental health issues. This study introduces an interactive, auditory, and multisensory game board providing a wonderful and healthy experiences in tailoring the developmental needs of children. The objective of this research is to design and develop an interactive alphabet board with necessary sensors, electronics, and controller modules. Moreover, designing a Machine Learning (ML) model for voice-based alphabet recognition is one of the important contributions of this research. Among the results of different ML models, Naïve Bayes Classifier outperforms the most with accuracy ≈ . %. The proposed system will facilitate the preschoolers to learn in modern and interactive way, while keeping away from being addicted to the mobile devices.

关键词： Pediatrics Visualization Accuracy Scalability Education Games Speech recognition Sensors Smart phones Systematic literature review

来源：评论

学校读者我要写书评

暂无评论

Robotic Anchoring System with Two Locomotion Modes for Preoperative Localization of Colorectal Cancer

Robotic Anchoring System with Two Locomotion Modes for Preop...

引用

2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Wang, Jiale Ren, Hao Yang, Liu Zhao, Haoxiang Zhang, Ruijia Shen, Yajing Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Kowloon Hong Kong City University of Hong Kong Department of Biomedical Engineering Kowloon Hong Kong Institute of Robotics and Automatic Information System Nankai University China

ISBN: (纸本)9781665481090

At present, colorectal cancer is one of the most prevalent cancers in the world. Colectomy serves as an effective treatment option for this disease. Preoperative localization plays a vital role in the colectomy procedure. However, traditional preoperative localization techniques have a greater risk of infection and lower accuracy. Moreover, it is difficult for the previous anchoring robots to adapt to the unstructured environment of the GI tract because of their limited movement abilities. To address these challenges, this work develops a robotic anchoring system with two locomotion modes which can anchor in the designated position. Driven by the external magnetic field, the robot can achieve slipping and flipping in the stomach. When the gradients of the field increase, the robot is triggered to deploy the anchoring mechanism in the intestine. Two in vitro experiments are conducted in the stomach and intestine phantoms. The first experiment demonstrates that the robot system can achieve both slipping and flipping in the stomach and its average position error is 2.96mm. The second experiment shows that the robot system can anchor in the designated position near the tumor and can resist a peristalsis force of 0.82N from the intestine wall. © 2024 IEEE.

关键词： Diseases

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：