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Implicit Feature Augmentation for Cloth-Changing Person Re-identification 18th

Implicit Feature Augmentation for Cloth-Changing Person Re-...

引用

18th Chinese Conference on Biometric Recognition, CCBR 2024

作者： Bao, Yongtang Zheng, Hao Shan, Caifeng Zhang, Peng Shandong University of Science and Technology Qingdao China Nanjing University Nanjing China

ISBN: (纸本)9789819610709

Cloth-changing person re-identification (CC-ReID) aims to match the target pedestrian who might change clothes across different cameras. Despite significant progress in CC-ReID, the task remains challenging due to the scarce cloth-changing samples in existing datasets. To address this, we proposed an Implicit Feature Augmentation Network (IFANet) to mimic data diversity in latent feature space. Particularly, our IFANet consists of three main modules. The global conversion module transfers features based on various fine-grained information, such as texture. The part augmentation module decomposes the features into identity-related and identity-free components and recombines them. Additionally, the identity distribution module is designed to constraint the correct classification of those ambiguous features. Extensive experiments on two widely-used CC-ReID datasets demonstrate the effectiveness of our method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Feature extraction

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The Expansion of Neuroaesthetic Models to Accommodate Diverse Multisensory Experiences in the Era of Digital Materiality 23rd

The Expansion of Neuroaesthetic Models to Accommodate Divers...

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

作者： Zheng, Zhong Gao, Yuchan Lin, Runqing Lu, Qi Huang, Guanghui Faculty of Humanities and Arts Macau University of Science and Technology Avenida Wai Long Taipa999078 China School of Fine Arts and Design Zhuhai University of Science and Technology Zhuhai China Zhuhai M.U.S.T. Science and Technology Research Institute Guangdong Zhuhai China

ISBN: (纸本)9783031743528

In the era of digital materiality, human aesthetic objects have transitioned from materiality natural to the virtual reality of the digital cloud. The plasticity of the aesthetic brain and aesthetic assessment have also exhibited the emergence of "new aesthetic pleasures" as anticipated by Semir Zeki, the proponent of neuroaesthetics. Meanwhile, neuroaesthetics has shifted from exploring the brain's processing mechanisms to the creativity and multisensory experience. Artificial intelligence and the theory of mind point towards the aesthetic judgment of "purposiveness without purpose" in beauty and creativity. This article compares the processing fluency model and the pleasure-interest of aesthetic model (PIA) within neuroaesthetics. Based on these findings, a third model suitable for the digital materiality era is proposed: the Immersive Aesthetic and Sensory Experience (IASE) model. This model employs neuroaesthetic methods to discuss the enhancement of aesthetic peaks through the brain's default mode network (DMN) and deep immersion states, as well as the impact of the MPFC and PCC, key nodes in two default networks on aesthetic thresholds. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Virtual reality

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Evaluation of Operating Comfort of Biological Microscopes 26th

Evaluation of Operating Comfort of Biological Microscopes

引用

26th International Conference on Human-computer Interaction, HCII 2024

作者： Wang, Yong Zhang, Tianmei Tan, Jiubin School of Architecture and Design Harbin Institute of Technology Harbin150001 China School of Instrumentation Science and Engineering Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9783031768088

The operating comfort of biological microscopes is directly related to the operators’ health and the accuracy of observation results. In this paper, the neck and arm comfort of biological microscope operators was researched. Firstly, the evaluation experiments included two parts: one was the evaluation of operating comfort for the neck and shoulder, the other was for the arm. The surface electromyography (sEMG) data of the measured muscles such as the splenius capitis, sternocleidomastoid, trapezius, flexor carpi and brachioradialis were acquired within the range of 0–40° neck angle and 90–150° elbow angle. In addition, the rating of perceived exertion (RPE) of operators was taken as the subjective evaluation results for different operating postures. Secondly, the root mean square (RMS) data of different subjects’ sEMG were normalized to the corresponding RMS of 20%MVC. It can be seen that the load of the splenius capitis, sternocleidomastoid and trapezius all increased with the increase of the head bow angle, and the load of measured muscles reached the maximum in 35–45°. And when the angle between the forearm and the upper arm was 115–125°, the load on the flexor carpi radialis, brachioradialis and trapezius was minimal. Finally, the ANOVA statistical analysis was proceeded to the RMS data of the measured muscles. It was found that the load of the splenius capitis and sternocleidomastoid was positively correlated with the bow angle, and the load range was 4%–30%MVC. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Muscle

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Vietnamese Scene Text Detection via Edge Information and Text Region Feature Enhancement 27th

Vietnamese Scene Text Detection via Edge Information and T...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Jiang, Liyu Shi, Shaoliang Huang, Wenhui Xu, Zhengli Cu, Vinh Loc Wen, Yimin Guilin University of Electronic Technology Guilin China China Academy of Science & Technology Development GuangXi Branch Nanning China Can Tho University Can Tho Viet Nam

ISBN: (纸本)9783031784972

Scene text detection plays a crucial role in the development of computer vision. However, current scene text detection algorithms mainly focus on Chinese and English, while Vietnamese scene text detection still remains a challenging task. The current algorithms to detect Vietnamese scene text frequently result in the incapacity of detecting Vietnamese diacritics and wrongly detecting background as text. To address these challenges, in this paper, a Vietnamese scene text detection algorithm is proposed to concentrate on diacritics and effectively reduce background interference. Specifically, an Edge Information Enhancement Module (EIEM) is first proposed to enhance the edge features of Vietnamese characters by combining a gradient filter with an attention mechanism. Secondly, a Text Region Enhancement Module (TREM) is proposed to enhance the feature representation of text regions by capturing global contextual information and dependencies among Vietnamese characters, thereby enhancing the distinction between background and text. Experiments on the Vintext dataset illustrate that the proposed method performs better in Vietnamese scene text detection tasks compared with several contemporary scene text detection algorithms. The code of the proposed algorithm is available at https://***/mlmmwym/VSTD-EITRFE. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Diacritics Feature pyramids Scene text detection Vietnamese characters

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Structural Parameterization of Minus Domination 11th

Structural Parameterization of Minus Domination

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11th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2025

作者： Reddy, Sangam Balchandar Kare, Anjeneya Swami School of Computer and Information Sciences University of Hyderabad Hyderabad India

ISBN: (纸本)9783031834370

Given a graph G=(V,E), a minus dominating function f:V→{-1,0,1} is a labelling of vertices such that ∑v∈N[u]f(v)≥1, for each u∈V. The weight of f is the sum of f(u) over all the vertices u∈V. The objective of Minus Dominating Set problem is to compute a minus dominating function of minimum weight. The problem is known to be NP-complete even on split graphs and bipartite graphs. The parameterized complexity of the problem for the parameter treewidth is a long standing open question. In this paper, we answer this by proving that the problem is W[1]-hard for the parameter distance to disjoint paths, which is larger than treewidth and feedback vertex set number. Later, we show that no polynomial kernel exists for the parameter vertex cover number. For the parameter weight, we prove that the problem is W[2]-hard on bipartite graphs and W[1]-hard on circle graphs, respectively. In addition, we provide an FPT algorithm for the parameter feedback edge set number. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： NP-hard

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Optimizing Real Estate Recommendations with Elasticsearch and Machine Learning Techniques 25th

Optimizing Real Estate Recommendations with Elasticsearch a...

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25th International Conference on Web Information Systems Engineering, WISE 2024

作者： Sbiaa, Fatma Boufares, Nadia Kotel, Sonia Maalel, Ahmed RIADI Laboratories National School of Computer Sciences University of Manouba Manouba Tunisia Polytechnic School of Sousse Sousse Tunisia Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Sousse Tunisia

ISBN: (纸本)9789819605699

In the rapidly evolving real estate industry, providing highly accurate and personalized recommendations has become paramount. Precision in these recommendations is crucial to meet the unique needs of potential buyers and ensure that sellers effectively reach their target audiences. By offering tailored property suggestions, user experience is significantly improved, leading to greater satisfaction and engagement for both buyers and sellers. This paper presents an innovative recommendation system designed for real estate websites. It aims to enhance user satisfaction and engagement through targeted property suggestions. Our proposed system leverages Elasticsearch in combination with machine learning techniques to deliver precise recommendations. We detail the system architecture and its processes. Evaluations conducted on real-world datasets demonstrate better recommendation accuracy and user engagement compared to traditional methods. This combination leads to significant improvements in real estate performance and opens up opportunities for future research. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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A Fusion-Based Framework for Unsupervised Single Image Super-Resolution 1

引用

7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023

作者： Mishra, Divya Dror, Itai Hadar, Ofer Choukroun, Daniel Maman, Shimrit Blumberg, Dan G. School of Electrical and Computer Engineering Beer-Sheva Israel Department of Mechanical Engineering Beer-Sheva Israel Homeland Security Institute Beer-Sheva Israel Department of Geography and Environmental Development Ben Gurion University of the Negev Beer-Sheva84105 Israel

ISBN: (数字)9783031346712

ISBN: (纸本)9783031346705

Image super-resolution has been a continuously demanding topic in the computer-vision community in recent decades and has witnessed impressive applications in increasing spatial resolution in every field like medicine, agriculture, remote sensing, defense security, and many more applications. Further, deep learning-based image super resolution methods have shown tremendous improvement in reconstruction performance. However, most of the recent state-of-the-art deep learning-based methods for image super-resolution assume an ideal degradation by the bicubic kernel on standard dataset approaches and perform poorly on real-world satellite images in practice, as real degradations are far away and more complex in nature than pre-defined assumed kernels. Motivated by this real-time challenge, our idea is to enhance the 600 m spatial-resolution image, which is extremely low, and implicitly defines image-specific features in an iterative way without defining any fixed explicit degradation for image super-resolution. Besides, we also did a comparative study based on a No-Reference Image Quality Assessment. The evaluation is done both qualitatively (vision based) and quantitatively without recurring to a reference image for quality assessment. The proposed framework outperforms by incorporating domain knowledge from recently implemented unsupervised single-image blind super-resolution techniques. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Iterative methods

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Automating the Clock Drawing Test with Deep Learning and Saliency Maps 23rd

Automating the Clock Drawing Test with Deep Learning and ...

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23rd EPIA Conference on Artificial Intelligence, EPIA 2024

作者： Mayne, Violet Rogers, Harry Sami, Saber la Iglesia, Beatriz de School of Computer Science University of Lincoln Lincoln United Kingdom School of Computing Sciences University of East Anglia Norwich United Kingdom

ISBN: (纸本)9783031734991

The Clock Drawing Test (CDT) is an important tool in the diagnosis of Cognitive Decline (CD). Using Deep Learning (DL), this test can be automated with a high degree of accuracy, more so where the medium of recording allows the use of temporal information on how the clock was drawn which may not be accessible to clinicians in traditional screening. The high-risk nature of this field makes understanding the reasoning for automated results imperative. A model’s reasoning can often be described using saliency maps, however, there are a number of different methods for generating such maps. Therefore, we propose a methodology to train a DL classifier for use in the CDT which incorporates temporal information and use saliency maps to explain classification predictions. We find that our classifier achieves scores above 98% with F1 for clocks and over 96% F1 on average across a test set of 18 different classes. Our methodology also shows that Integrated Gradients using SmoothGrad produce the best saliency map results visually and statistically. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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PolypSegDiff: Dynamic Multi-scale Conditional Diffusion Model for Polyp Segmentation 27th

PolypSegDiff: Dynamic Multi-scale Conditional Diffusion Mode...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Du, Xiaogang Jiao, Yipeng Lei, Tao Zhang, Xuejun Wang, Yingbo Nandi, Asoke K. Shaanxi Joint Laboratory of Artificial Intelligence Shaanxi University of Science and Technology Xi’an China School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou China Department of Electronic and Computer Engineering Brunel University London London United Kingdom

ISBN: (纸本)9783031801358

Diffusion models have demonstrated impressive potential in semantic segmentation tasks. However, these models cannot accurately segment hidden polyps with complex structures owing to the absence of multi-scale conditional features for guiding the reverse process of diffusion models. To address this issue, we propose a dynamic multi-scale conditional diffusion model (PolypSegDiff). First, we design a dynamic multi-scale integration module to fuse the noise segmentation mask and the original image, dynamically extract multi-scale conditional features, and strengthen the network’s ability of identifying polyp areas. Second, we design a hierarchical feature enhancement module to extract and combine image features at different levels. This module significantly enriches the semantic diversity of conditional features, enabling the denoising network to more accurately understand the semantic relationships between polyps and the surrounding normal tissues. Experimental results across five publicly available polyp segmentation datasets demonstrate that PolypSegDiff outperforms existing popular methods in segmentation accuracy, achieving outstanding performance and robust generalization. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Semantic Segmentation

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An Image Super-Resolution Based Method for Palmprint Recognition 18th

An Image Super-Resolution Based Method for Palmprint Recogn...

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18th Chinese Conference on Biometric Recognition, CCBR 2024

作者： Yang, Zekai Luo, Dacan Zeng, Ming Wan, Hao Kang, Wenxiong School of Automation Science and Engineering South China University of Technology Guangzhou China Guang Zhou Baiyun International Airport Company Limited Guangzhou China

ISBN: (纸本)9789819610679

Palmprint recognition, noted for its high reliability and privacy has recently aroused wide attention in biometrics. For palmprint recognition, High-quality palmprint images are more effective. However, in real-world scenarios, the quality of palmprint images tends to be low due to limitations in device capabilities and various environmental factors. This study introduced a palmprint recognition method based on image super-resolution (SR), called PPSRNet. The proposed PPSRNet consists of two parallel branches that extract features from SR palmprint images and original images, merging them through score fusion at the final stage. This method employs image SR to enhance image quality and refine the intricate details of palm texture, thereby improving recognition performance. It also utilizes score fusion to address potential negative effects during the image SR process. Experimental results on three popular public palmprint biometric datasets demonstrated the effectiveness of PPSRNet for palmprint recognition. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Palmprint recognition

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