检索结果-内蒙古大学图书馆

Spatially adaptive pyramid feature fusion for scale-aware crowd counting

Pattern Recognition 2025年 168卷

作者： Shenjian Gong Zhaoliang Yao Wangmeng Zuo Jian Yang PongChi Yuen Shanshan Zhang PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education and Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 China Hikvision Research Institute China School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China Department of Computer Science Hong Kong Baptist University Hong Kong

Crowd counting is a challenging task to predict the number of persons in crowded scenes. The major challenge comes from density/scale variation in one single image, which results in a significant performance decrease for most methods. In this work, we aim to explore how to solve the scale variation problem with assistance from the segmentation task. We first simultaneously predict a coarse density map, along with multi-scale segmentation masks, which provide strong priors of background and head regions with different scales; then we propose a Spatially Adaptive Pyramid (SAP) feature fusion block to fully integrate the coarse density map and multi-scale segmentation masks; in SAP, a feature pyramid and corresponding attention pyramid are obtained for multi-scale head regions, and then cross-scale correlations are computed to handle the scale variation problem. These high-dimensional cross-scale correlation features are then used to refine the density map, based on which the final counting numbers are obtained. Experiments show that our proposed SAP block significantly outperforms previous fusion methods, and obtains consistent improvements on various backbones. Compared to previous state-of-the-art methods, our method is better at handling scale variation, surpassing previous methods on the challenging ShanghaiTech A, UCF-QNRF and NWPU datasets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comprehensive curriculum of programming for engineers, its teaching models and in-lab monitoring technique

Comprehensive curriculum of programming for engineers, its t...

引用

International MultiConference of Engineers and computer Scientists 2015, IMECS 2015

作者： Satoskar, Mohit Mali, Sagar Department of Computer Science and Information Technology Ramrao Adik Institute of Technology Mumbai India Computer Programming and System Software Design Area of Computer Science at Kolhapur Maharashtra India

ISBN: (纸本)9789881925329

Issues related to the curriculum design of C programming language is analysed. Aspects and necessity of programming for engineers is discussed. The enhanced outlay of programming for engineers and generating the curriculum is presented. Relativity and dependency briefly highlighted. A superlative teaching model of computer languages is discussed along with its principles. In-lab monitoring technique is developed successfully using client-server architecture which ensures learner live workshop progress. It is shown how the programming for engineer's curriculum design and techniques help to create highest quality outcome.

关键词： Curricula

来源：评论

学校读者我要写书评

暂无评论

Screening cognitive impairment in patients with atrial fibrillation: A deep learning model based on retinal fundus photographs

Heart Rhythm O2

引用

Heart Rhythm O2 2025年第5期6卷 678.0-686.0页

作者： Wang, Zhen Li, Mingxiao Xia, Peng Jiang, Chao Shen, Ting Ma, Jiaming Bai, Yu Zhang, Suhui Lai, Yiwei Li, Sitong Xu, Hui Xu, Yang Ma, Tong Ju, Lie He, Liu Dong, Li Sang, Caihua Long, Deyong Chen, Yuzhong Du, Xin Ge, Zongyuan Dong, Jianzeng Wei, Wen-Bin Ma, Changsheng Department of Cardiology Beijing Anzhen Hospital Capital Medical University Beijing China Engineering Research Center of Medical Devices for Cardiovascular Diseases Ministry of Education Capital Medical University Beijing China National Clinical Research Center for Cardiovascular Diseases Beijing China Beijing Airdoc Technology Co. Ltd. Beijing China Department of Electrical and Computer Systems Engineering Faculty of Engineering Monash University Clayton Australia Yale School of Medicine New Haven Connecticut United States School of Clinical Medicine Peking Union Medical College and Chinese Academy of Medical Science Beijing China Beijing Tongren Eye Center Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment Beijing Ophthalmology & Visual Sciences Key Lab Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology Beijing Tongren Hospital Capital Medical University Beijing China Monash e-Research Center Monash University Clayton Australia

Background: Patients with atrial fibrillation (AF) have a higher risk of cognitive impairment (CI). However, complexity of CI diagnosis and lack of simple screening approaches limited early screening and intervention of CI in AF patients. Objective: Our study aimed to develop deep learning models based on fundus photographs for easy screening of CI in AF patients. Methods: From May 2021 to April 2023, patients who completed fundus examination and cognitive function evaluation in the Chinese Atrial Fibrillation Registry Study were included. The training and validation sets were randomly split at an 8:2 ratio. Participants from the Beijing Eye Study served as the external validation set. Different deep learning models were trained, and their CI detection ability was validated. Results: A total of 899 patients in the Chinese Atrial Fibrillation Registry Study were included. In the validation set, the vision-ensemble model based on fundus images alone had an area under the receiver-operating characteristic curve (AUROC) of 0.855 (95% confidence interval 0.816–0.894) for CI screening. The multimodal model (AUROC 0.861, 95% confidence interval 0.823–0.898), based on fundus photographs and 4 clinical variables, performed comparably to the vision-ensemble model. The AUROC of the vision-ensemble model for CI screening achieved 0.773 (95% confidence interval 0.709–0.837) in the external test set. In the saliency map, the vision-ensemble model focused on areas around retinal vessels and the optic disc. Conclusion: A vision-ensemble model based on fundus images might be practical for preliminary screening of CI in AF patients. © 2025 Heart Rhythm Society

关键词： Artificial intelligence Atrial fibrillation Cognitive impairment Deep learning Fundus photography

来源：评论

学校读者我要写书评

暂无评论

On optimising shape-generic array programs using symbolic structural information

引用

18th International Symposium on Implementation and Application of Functional Languages, IFL 2006

作者： Trojahner, Kai Grelck, Clemens Scholz, Sven-Bodo University of Lübeck Institute of Software Technology and Programming Languages University of Hertfordshire Department of Computer Science

ISBN: (纸本)9783540741299

Shape-generic programming and high run time performance do match if generic source code is systematically specialised into nongeneric executable code. However, as soon as we drop the assumption of whole-world knowledge or refrain from specialisation for other reasons, compiled generic code is substantially less efficient. Limited effectiveness of code optimisation techniques due to the inherent lack of knowledge about the structural properties of arrays can be identified as the single most important source of inefficiency. However, in many cases partial structural information or structural relationships between arrays would actually suffice for optimisation. We propose symbolic array attributes as a uniform scheme to infer and to represent partial and relational structural information in shape-generic array code. By reusing the regular language to express structural properties in intermediate code, existing optimisations benefit from symbolic array attributes with little or no alteration. In fact, program optimisation and identification of structural properties cross-fertilise each other. We outline our approach in the context of the functional array language SAC and demonstrate its effectiveness by a small case study. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Information analysis

来源：评论

学校读者我要写书评

暂无评论

Evaluating Keyphrase Extraction Methods for Clustering Influenza-Related Scientific Papers 8

Evaluating Keyphrase Extraction Methods for Clustering Influ...

引用

8th International Iranian Conference on Signal Processing and Intelligent Systems, ICSPIS 2022

作者： Forghani, Majid Firstkov, Artyom Alyannezhadi, Mohammad. M. Forghani, Kazem Krasovskii Institute of Mathematics & Mechanics Mathematical Programming Lab. Yekaterinburg Russia University of Science and Technology of Mazandaran Department of Science Behshahr Iran Iran University of Science and Technology Computer Science Department Tehran Iran

ISBN: (纸本)9781665476232

The number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. This increases the complexity of the search for relevant articles. Modern search engines leverage keyphrases to improve the performance of search results. Keyphrases (or keywords) are a set of single or multi-word expressions which provide a very compact summary of contents and describe the overall topic of a document. Implementation of keyphrase extraction can be varied for specific-domain databases. This motivated us to evaluate these methods on a database of influenza scientific literature. In this work, we considered 9 well known methods for extracting keyphrases. Our preliminary results show txhat graph-based methods which employ topics outperform others using our database. We also determined that influenza-related papers can be grouped into three general topics: public health & medical care;molecular biology & immunology;and phylogenetic & epidemiological studies. © 2022 IEEE.

关键词： Database systems

来源：评论

学校读者我要写书评

暂无评论

DNACoder: a CNN-LSTM attention-based network for genomic sequence data compression

引用

Neural Computing and Applications 2024年第29期36卷 18363-18376页

作者： Sheena, K.S. Nair, Madhu S. Artificial Intelligence & amp Computer Vision Lab Department of Computer Science Cochin University of Science and Technology Kerala Kochi682022 India

Genomic sequencing has become increasingly prevalent, generating massive amounts of data and facing a significant challenge in long-term storage and transmission. A solution that reduces the storage and transfer requirements without compromising data integrity is needed. The effectiveness of neural networks has already been endorsed in tasks like image and speech compression. Adapting them to recognize the intricate patterns in genomic sequences could help to find more redundancies and reduce storage requirements. The proposed method, called DNACoder, leverages deep learning techniques to achieve significant compression ratios while preserving the essential information in genomic data and offers a high-performance compression for genomic sequences in any data format. The results of the experiments clearly demonstrate the effectiveness of the method and its potential applications in genomic data storage. Our proposed method improves compression by 21.1% on bits per base compared to existing compressors on the benchmarked dataset. By using a deep learning prediction model that is structured as a convolutional layer followed by an attention-based long short-term memory network, we propose a novel lossless and reference-free compression approach (DNACoder), which can also be utilized as a reference-based compressor. The experimental outcome on the tested data illustrates that the advocated compression algorithm’s CNN-LSTM model makes generalizations effectively for genomic sequence data and outperforms the state-of-the-art methods. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Pulse Coupled Neural Network Edge-Based Algorithm for Image Text Locating

引用

Tsinghua science and technology 2011年第1期16卷 22-30页

作者：张昕孙富春 State Key Lab of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and TechnologyDepartment of Computer Science and TechnologyTsinghua University

This paper presents a method for locating text based on a simplified pulse coupled neural network （PCNN）. The PCNN generates a firings map in a similar way to the human visual system with non-linear image processing. The PCNN is used to segment the original image into different planes and edges detected using both the PCNN firings map and a phase congruency detector. The different edges are integrated using an automatically adjusted weighting coefficient. Both the simplified PCNN and the phase congruency energy model in the frequency domain imitate the human visual system. This paper shows how to use PCNN by changing the compute space from the spatial domain to the frequency domain for solving the text location problem. The algorithm is a simplified PCNN edge-based （PCNNE） algorithm. Three comparison tests are used to evaluate the algorithm. Tests on large data sets show PCNNE efficiently detects texts with various colors, font sizes, positions, and uneven illumination. This method outperforms several traditional methods both in text detection rate and text detection accuracy.

关键词： simplified pulse coupled neural network phase congruency text location

来源：评论

学校读者我要写书评

暂无评论

Distributed Consensus Network: A Modularized Communication Framework and Reliability Probabilistic Analysis

arXiv

引用

arXiv 2025年

作者： Li, Yuetai Xu, Zhangchen Wang, Yiqi Zhou, Zihan Zhang, Lei Crowcroft, Jon Department of Electrical & Computer Engineering University of Washington 1410 NE Campus Pkwy SeattleWA United States James Watt School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom Information Hub of HKUST Hong Kong University of Science and Technology No.1 Du Xue Rd Nansha District Guangzhou China Computer Lab University of Cambridge CambridgeCB2 1TN United Kingdom

In this paper, we propose a modularized framework for communication processes applicable to crash and Byzantine fault-tolerant consensus protocols. We abstract basic communication components and show that the communication process of the classic consensus protocols such as RAFT, single-decree Paxos, PBFT, and Hotstuff, can be represented by the combination of communication components. Based on the proposed framework, we develop an approach to analyze the consensus reliability of different protocols, where link loss and node failure are measured as a probability. We propose two latency optimization methods and implement a RAFT system to verify our theoretical analysis and the effectiveness of the proposed latency optimization methods. We also discuss decreasing consensus failure rate by adjusting protocol designs. This paper provides theoretical guidance for the design of future consensus systems with a low consensus failure rate and latency under the possible communication loss. Copyright © 2025, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-Scale Spiking Pyramid Wireless Communication Framework for Food Recognition

引用

IEEE Transactions on Multimedia 2024年 27卷 1-13页

作者： Li, Wenrui Li, Jiahui Ma, Mengyao Hong, Xiaopeng Fan, Xiaopeng Department of Computer Science and Technology Harbin Institute of Technology Harbin China Wireless Technology Lab Huawei Shenzhen China

Food recognition applications in human health have recently garnered significant attention in the field of computer vision. With the advancement of mobile devices, robust food recognition in wireless communication has become a practical and challenging application scenario. We propose a novel Multi-scale Spiking Pyramid Transmission Network (MSPTN) to tackle this challenge. The MSPTN learns diverse and complementary local and global feature maps simultaneously, generating a comprehensive description of food images that capture the correlations of feed-specific features. The feature sender uses a three-layer Spiking Neural Network (SNN). The proposed sender compresses features into sparse and discrete spike trains, significantly reducing the required transmission bandwidth and improving channel utilization and energy efficiency. Our model introduces the Compressed Factorized Bilinear block (CFB), which employs a low-rank feature approximation to reduce computational complexity and feature transmission volume while preserving the discriminate features. The enhancement reasoning module is proposed to enhance the received features by projecting them into a higher-dimensional space and utilizing the self-attention mechanism and sum pooling to compress them back to the original dimension. We conduct extensive experiments on the ETH Food-101 and Food2k datasets. Our results reveal that the MSPTN demonstrates state-of-the-art recognition performance, even with binary spike trains. Meanwhile, the MSPTN also exhibits remarkable robustness in wireless communication scenarios. With the combination of CFB, SNN, and EFB, our model achieves significant efficiency gains, including a nearly nine-fold decrease in feature transmission volume and a three-fold improvement in runtime & computational memory speed. IEEE

关键词： Bandwidth

来源：评论

学校读者我要写书评

暂无评论

Multiphases dose analysis of cardiac substructures using coronary CT angiography in postmastectomy radiotherapy

引用

Medical Dosimetry 2025年

作者： Zhang, Zhe Tang, Zhaohui Yang, Mengqi Moraros, John Li, Xin Zhang, Xiaomin Li, Ying Chen, Gaoxiang Wang, Shuihua Liu, Yajie Department of Radiation Oncology Peking University Shenzhen Hospital Hong Kong University of Science and Technology Medical Center Shenzhen 518048 China Department of Biosciences and bioinformatics Suzhou Municipal key Lab AI4Health School of Science Xi'an Jiaotong-Liverpool University Suzhou 215123 China Department of Computer Sciences University of Liverpool Liverpool L69 7ZX United Kingdom Department of Radiation Oncology Chinese PLA General Hospital Beijing 100039 China

This study used coronary computed tomography angiography (CCTA) in left breast cancer patients. It assessed real-time dose delivery of postmastectomy radiotherapy (PMRT) with internal lymph node irradiation (IMNIs) and normal tissue complications probability (NTCP) to the heart and subcardiac structures using tangential volumetric modulated arc therapy (T-VMAT). This research and its findings are critical in refining PMRT strategies to safeguard patient health and promote the overall efficacy of cancer management protocols. In this study, CCTA images from 16 patients were analyzed. These images were reconstructed at multiple phases (0%-90%) of the cardiac cycle for each patient. Substructures including the left ventricle (LV), right ventricle (RV), right atrium (RA), left atrium (LA), right coronary artery (RCA), and left anterior descending artery (LAD) were delineated using the RTOG 1106 OAR atlas guidelines. A rigid registration process aligned the CCTA images with planning chest CT scans. The heart's CT values were adjusted to ensure accuracy in electron density representation. The PTV was simulated, and a T-VMAT plan was created. The radiation fields were then applied to the 10 different cardiac phase images, and an accumulated plan was generated and compared with a conventional radiotherapy plan. Comparing the accumulated plan with the conventional plan, the absolute Dmean difference to the heart was 73.2 (cGy), and demonstrated a significant change of 14%. Among cardiac substructures, the largest differences in Dmean were observed in the LAD, RCA and LV-V25 with a variation of 387.5 cGy (22.5%), 195.8 cGy (34.7%) and 1.53% (52%), respectively. NTCP was slightly higher in the accumulated plan (0.44±1.57%) than in the conventional plan (0.17±0.47%). The results of this study underscore the critical role of real-time cardiac imaging in refining the delivery of PMRT with IMNIs. By leveraging CCTA and T-VMAT, we have achieved a more precise assessment of the cardi

关键词： Breast cancer Cardiac Substructures CCTA IMNIs T-VMAT

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：