检索结果-内蒙古大学图书馆

15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Virvou, Maria Tsihrintzis, George A. University of Piraeus Software Engineering Laboratory Department of Informatics Piraeus Greece Machine Learning Image Processing and Multimedia Applications Laboratory University of Piraeus Department of Informatics Piraeus Greece

ISBN: (纸本)9798350368833

Artificial Intelligence (AI) chatbots and social robots, when incorporated into educational settings, have the potential to significantly transform the learning experience, particularly by providing more personalised, one-on-one attention to students. However, deploying such technology in classrooms also presents challenges. These include unresolved issues related to human-AI interaction, pedagogy and theories, human oversight, data privacy, transparency, accuracy and trust. This paper explores the development of a comprehensive framework aimed at enhancing the efficiency, pedagogical effectiveness, and ethical use of AI-driven educational tools, focusing on social robots and chatbots. The framework addresses important factors such as interaction quality, requirements engineering strategies, and the alignment of AI functionalities with educational goals. It also examines ethical concerns, including data security, user transparency, and trustworthiness. By reviewing recent literature on social robots and chatbots and incorporating emerging ethical considerations alongside long-standing educational objectives, this research aims at establishing a holistic framework, FEPER, of best practices and requirements. The findings offer valuable insights for educators, policymakers, and developers aiming to create more dynamic, personalised, and ethical educational environments using AI technology. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Efficient Pavement Crack Detection in Drone images using Deep Neural Networks

Efficient Pavement Crack Detection in Drone Images using Dee...

引用

2023 International Conference on Electronics, Information, and Communication, ICEIC 2023

作者： Kim, Heegwang Sung, Junghoon Kim, Mingi Park, Chanyeong Paik, Joonki Chung-Ang University Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Seoul Korea Republic of Chung-Ang University Image Processing and Intelligent System Laboratory Graduate School of Artificial Intelligence Seoul Korea Republic of

ISBN: (纸本)9798350320213

Since the drone input images are usually filmed at very high altitudes and with various viewing angles, cracks appear in many different sizes and shapes. A commonly used crack detection dataset has a small size such as 480x320, and it is important that how well it detects the prominent continuous cracks. To detect pavement cracks, we proposed an efficient crack detection network. The proposed network achieved better performance than the conventional network. © 2023 IEEE.

关键词： crack detection sigmoid fusion module YOLOX

来源：评论

学校读者我要写书评

暂无评论

Pansharpening Methods Based on a Redundant Contourlet Transform

Pansharpening Methods Based on a Redundant Contourlet Transf...

引用

2023 International Conference on Earth Observation and Geo-Spatial Information, ICEOGI 2023

作者： Ourabia, Soumeya Baaziz, Nadia Smara, Youcef University Center of Tipaza -Morsli Abdelah-Institut of Sciences Laboratory of Image Processing and Radiation -USTHB Departement of Electronics Tipaza Algeria University of Quebec in Outaouais - Uqo Research Laboratory in Multimedia Information Department of Computer Science and Engineering GatineauQC Canada University of Sciences and Technology Houari Boumediene -USTHB Laboratory of Image Processing and Radiation Faculty of Electrical Engineering Algiers Algeria

ISBN: (纸本)9798350396720

The pansharpening of high-resolution panchromatic (Pan) image and low-resolution multispectral (MS) images represents an important task in the remote sensing field. It allows the joint exploitation of the information derived from both types of images. However, this may cause a distortion of spectral information or a lack in details and structures. The multiresolution analysis using wavelet transforms has proved its efficiency in the pansharpening domain, due to the representation of the image content over different resolution levels. In image fusion applications, we always need more detail information to be incorporated in the pansharpening procedure in order to produce enhanced results. However, the limitation of the wavelet transform to three types of oriented detail coefficients prevents this need from being met. To overcome this limitation, we propose to use the redundant contourlet transform (RCT) which extracts a richer multiscale directional information from the image. For this purpose, two RCT-based pansharpening methods are introduced and suitable data fusion procedures are described. We conducted several experiments on two different datasets acquired respectively by ALSAT-2A and IKONOS satellites. The visual results as well as quantitative results from evaluation metrics demonstrate the performance of the proposed methods. © 2023 IEEE.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Privacy Protection Solution: Enhancing Face Obscuring Techniques with Automated Identification, Mobile Integration, and Scalable Services

A Comprehensive Privacy Protection Solution: Enhancing Face ...

引用

IEEE International Conference on Consumer Electronics (ICCE)

作者： Ilhwan Kim Hyeongseok Oh Sangwoo Yun Heunseung Lim Jaeseok Ryu Joonki Paik Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Image Processing and Intelligent System Laboratory Graduate School of Artificial Intelligence Chung-Ang University Seoul Korea

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

We propose a novel application aimed at protecting personal privacy. With the proliferation of various media platforms, issues related to personal portraits have emerged. To address these problems, previous applications propose methods for either Mosaic or replace it with another object. However, existing methods suffer from issues such as high time costs and unnatural rendering. To address these problems, we propose designing an automatic face identification and replacement system by combining face detection, super-resolution, and face replacement models. This approach aims to reduce processing time and enhance natural rendering. In addition to the technological advancements, we suggest expanding this system into a mobile service, allowing users to easily protect their privacy on the go. This mobile platform would provide a user-friendly interface and seamless integration with various social media and communication apps, making it accessible to a broader audience. Furthermore, we explore potential expansion opportunities, such as cloud-based processing for scalability and the development of APIs that other developers can integrate into their own applications, thereby broadening the service's reach and impact. We demonstrate that our approach is simpler and more natural compared to traditional handcrafted tasks by applying it to diverse scenarios.

关键词： Privacy Accuracy Scalability Superresolution Media Rendering (computer graphics) Face detection Protection Usability Faces

来源：评论

学校读者我要写书评

暂无评论

Enhancing Thermal Infrared Object Detection Using SimAM-Integrated YOLOX for Improved Feature Representation

Enhancing Thermal Infrared Object Detection Using SimAM-Inte...

引用

IEEE International Conference on Consumer Electronics (ICCE)

作者： Jaehong Yoon Heegwang Kim Chanyeong Park Junbo Jang Jiyoon Lee Joonki Paik Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Image Processing and Intelligent System Laboratory Graduate School of Artificial Intelligence Chung-Ang University Seoul Korea

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Object detection with thermal infrared images is vital for applications like autonomous driving in low-light and adverse environmental conditions. While TIRDet has improved thermal-only object detection through a Thermal-To-Visible (T2V) translation model, this module can suffer from information loss in certain scenarios. To address this, we propose enhancing the CSPDarknet53 backbone of YOLOX within TIRDet by incorporating SimAM, a parameter-free attention mechanism. SimAM enhances feature representation by inferring 3D attention weights based on an energy function inspired by neuroscience theories, without increasing model parameters. By strengthening feature extraction within the backbone, our approach compensates for the T2V module's information loss, thereby improving detection performance under challenging conditions. Experiments on the LLVIP and FLIR datasets demonstrate superior performance, underscoring the effectiveness of parameter-free attention mechanisms for advancing thermal object detection.

关键词： Solid modeling Translation Attention mechanisms Three-dimensional displays Neuroscience Object detection Feature extraction Text to video Autonomous vehicles Consumer electronics

来源：评论

学校读者我要写书评

暂无评论

ViSeNet: A Visual-Semantic Fusion Network for Enhancing Few-Shot Classification

ViSeNet: A Visual-Semantic Fusion Network for Enhancing Few-...

引用

IEEE International Conference on Consumer Electronics (ICCE)

作者： Dongheon Lee Sangwoo Yun Joonki Paik Image Processing and Intelligent & System Laboratory Graduate School of Artificial Intelligence Chung-Ang University Seoul Korea Image Processing and Intelligent & System Laboratory Graduate School of Advanced & Imaging Science Multimedia and Film Chung-Ang University Seoul Korea

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Few-shot learning addresses the challenge of recognizing novel classes with only a few labeled examples, a critical issue in limited data scenarios. This paper proposes a multi-modal Visual and Semantic Network (ViSeNet), which enhances few-shot classification by mining linguistic features and fusing weighted vectors. ViSeNet generates enriched class prototypes by leveraging both visual and semantic information. The linguistic feature mining process utilizes image-to-text models to produce class-specific textual descriptions, which are then transformed into representative semantic embeddings. For visual feature extraction, we employ a pretrained Swin Transformer, while text embeddings are integrated for each class using weighted factors. By combining these modalities, ViSeNet constructs class prototypes that capture both visual and semantic characteristics. Experimental results on benchmark datasets, particularly CIFAR-FS, demonstrate that ViSeNet achieves performance comparable to state-of-the-art approaches.

关键词： Visualization Semantics Prototypes Linguistics Transformers Feature extraction Vectors Data mining Few shot learning Consumer electronics

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Privacy Protection Solution: Enhancing Face Obscuring Techniques with Automated Identification, Mobile Integration, and Scalable Services

A Comprehensive Privacy Protection Solution: Enhancing Face ...

引用

2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Kim, Ilhwan Oh, Hyeongseok Yun, Sangwoo Lim, Heunseung Ryu, Jaeseok Paik, Joonki Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of Image Processing and Intelligent System Laboratory Graduate School of Artificial Intelligence Chung-Ang University Seoul Korea Republic of

ISBN: (纸本)9798331521165

关键词： Rendering (computer graphics)

来源：评论

学校读者我要写书评

暂无评论

ViSeNet: A Visual-Semantic Fusion Network for Enhancing Few-Shot Classification

ViSeNet: A Visual-Semantic Fusion Network for Enhancing Few-...

引用

2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Lee, Dongheon Yun, Sangwoo J., Paik Image Processing and Intelligent & System Laboratory Graduate School of Artificial Intelligence Chung-Ang University Seoul Korea Republic of Image Processing and Intelligent & System Laboratory Graduate School of Advanced & Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of

ISBN: (纸本)9798331521165

关键词： Labeled data

来源：评论

学校读者我要写书评

暂无评论

Enhancing Thermal Infrared Object Detection Using SimAM-Integrated YOLOX for Improved Feature Representation

Enhancing Thermal Infrared Object Detection Using SimAM-Inte...

引用

2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Yoon, Jaehong Kim, Heegwang Park, Chanyeong Jang, Junbo Lee, Jiyoon Paik, Joonki Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of Image Processing and Intelligent System Laboratory Graduate School of Artificial Intelligence Chung-Ang University Seoul Korea Republic of

ISBN: (纸本)9798331521165

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Improved deeplab v3+ with metadata extraction for small object detection in intelligent visual surveillance systems

引用

IEIE Transactions on Smart processing and Computing 2021年第3期10卷 209-218页

作者： Oh, Heungmin Lee, Minjung Kim, Hyungtae Paik, Joonki Department of Image Engineering Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University / Seoul06974 Korea Republic of

A surveillance system deploys multiple cameras to monitor a wide area in real time to detect abnormal situations such as a crime scene, traffic accident, and natural disaster. An Increased number of cameras results in the same number of monitors, which makes human decisions or automatic decisions difficult. To solve the problem, a smart surveillance scheme has recently been proposed. The smart surveillance system automatically detects an object and provides an alarm to a surveillant. In this paper, we present a metadata extraction method for object-based video summary. The proposed method adopts deep learning-based object detection and background elimination to correctly estimate an object region. Finally, metadata extraction is performed on the estimated object information. The proposed metadata consists of the representative color, size, aspect ratio, and patch of an object. The proposed method can extract reliable metadata without motion features in both static and dynamic cameras. The proposed method can be applied to various object detection areas using complex metadata. Copyrights © 2021 The Institute of Electronics and Information Engineers

关键词： Object detection

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：