检索结果-内蒙古大学图书馆

Colorectal cancer classification using weakly annotated whole slide images: Multiple instance learning optimization study

引用

computers in Biology and Medicine 2025年 186卷 109649-109649页

作者： Saeed, Ahmed Ismail, Mohamed A. Ghanem, Nagia M. Computer and Systems Engineering Department Faculty of Engineering Alexandria University Alexandria Egypt

Colorectal cancer (CRC) is considered one of the most deadly cancer types nowadays. It is rapidly increasing due to many factors, such as unhealthy lifestyles, water and food pollution, aging, and medical diagnosis development. Detecting CRC in its early stages can help stop its growth by providing the necessary treatments, thereby saving many people's lives. There are various tests that doctors can perform to diagnose CRC;however, biopsy using histopathological images is considered the "gold standard" for CRC diagnosis. Deep learning techniques can now be leveraged to build computer-aided diagnosis (CAD) systems that can affirm if an input sample shows any symptoms of cancer and determine its stage and location with an acceptable degree of confidence. In this research, we utilize deep learning to study the CRC classification problem using weakly annotated histopathological whole slide images (WSIs). We relax the constraints of the multiple instance learning (MIL) algorithm and primarily propose WSI-label prediction functions to be integrated with MIL, which significantly enhances the performance of WSI-level classification. We also applied efficient preprocessing techniques that output a computationally power-efficient dataset representation and performed multiple experiments to compose the most efficient CAD system. Our study introduces a notable improvement over the results obtained by the baseline research where we achieved an accuracy of 93.05% compared to 84.17%. Furthermore, our results using only the weakly annotated WSIs outperformed the baseline results that are based on performing initial pre-training using a strongly annotated part of the dataset. © 2025 Elsevier Ltd

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Leveraging EfficientNetB3 in a Deep Learning Framework for High-Accuracy MRI Tumor Classification

引用

computers, Materials & Continua 2024年第10期81卷 867-883页

作者： Mahesh Thyluru Ramakrishna Kuppusamy Pothanaicker Padma Selvaraj Surbhi Bhatia Khan Vinoth Kumar Venkatesan Saeed Alzahrani Mohammad Alojail Department of Computer Science&Engineering Faculty of Engineering and TechnologyJAIN(Deemed-to-be University)Bengaluru562112India School of Computer Science and Engineering VIT-AP UniversityAmaravati522241India Department of Computer Science&Technology Madanapalle Institute of Technology&ScienceMadanapalle517325India School of Science Engineering and EnvironmentUniversity of SalfordManchesterM54WTUK School of Computer Science Engineering&Information Systems(SCORE) Vellore Institute of Technology(VIT)Vellore632014India Management Information System Department College of Business AdministrationKing Saud UniversityRiyadh11531Saudi Arabia Adjunct Research Faculty Centre for Research Impact&OutcomeChitkara UniversityRajpuraPunjab140401India

Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient *** different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI *** approaches predominantly rely on traditional machine learning and basic deep learning methods for image *** methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI *** the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor *** approach highlights a major advancement in employing sophisticated machine learning techniques within computer Science and engineering,showcasing a highly accurate framework with significant potential for healthcare *** model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification *** successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current *** integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider *** research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.

关键词： Deep learning MRI brain tumor cassification EfficientNetB3 computational engineering healthcare technology artificial intelligence in medical imaging tumor segmentation neuro-oncology

来源：评论

学校读者我要写书评

暂无评论

Exploring Deep Learning Methods for computer Vision Applications across Multiple Sectors:Challenges and Future Trends

引用

computer Modeling in engineering & Sciences 2024年第4期139卷 103-141页

作者： Narayanan Ganesh Rajendran Shankar Miroslav Mahdal Janakiraman SenthilMurugan Jasgurpreet Singh Chohan Kanak Kalita School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502India Department of Control Systems and Instrumentation Faculty of Mechanical EngineeringVSB-Technical University of OstravaOstrava70800Czech Republic Department of Computer Science and Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Mechanical Engineering and University Centre for Research&Development Chandigarh UniversityMohali140413India Department of Mechanical Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyAvadi600062India

computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(DL)methods are more successful than other traditional machine learning(ML)methods *** techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face *** this review,a structured discussion on the history,methods,and applications of DL methods to CV problems is *** sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of DL methods and *** review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.

关键词： Neural network machine vision classification object detection deep learning

来源：评论

学校读者我要写书评

暂无评论

Enhancing Wireless Sensor Network Data Collection through Aerial Unmanned Vehicles

Enhancing Wireless Sensor Network Data Collection through Ae...

引用

2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Ali Alheeti, Khattab M. Najim, Ali Hamza Satar, Nurhizam Safie Mohd Aliesawi, Salah A. Hashim, Aisha Hassan Abdallah Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia College of Computer and Information Technology Department of Computer Networking Systems University of Anbar Anbar Iraq Faculty of Engineering Department of Electrical and Computer Engineering International Islamic University Malaysia Selangor Malaysia

ISBN: (纸本)9798350369106

This study addresses the critical aspect of data collection within Wireless Sensor Networks (WSNs), which consist of autonomous, compact sensor devices deployed to monitor environmental conditions. These networks have limited processing capacity, storage, short-range communication capabilities, and constrained battery power. A primary challenge in WSN s revolves around data gathering, particularly when employing static sinks, leading to premature energy depletion in nodes near these sinks. Integrating mobile collectors introduces the potential for energy conservation by shortening data routes. This article introduces three distinct algorithms for optimizing data collection in WSN s. Our approach involves an in-depth analysis of diverse strategies to mitigate packet collisions and facilitate the retransmission of lost packets. Our findings underscore the considerable impact that packet collisions can exert on the overall network performance during data gathering within wireless sensor networks. Through empirical exploration and analysis, we highlight the significance of these algorithms in enhancing the efficiency, energy conservation, and reliability of data collection processes within WSNs. This research sheds light on these algorithms' vital role in addressing the pressing challenges of data gathering and network performance optimization in wireless sensor networks. © 2024 IEEE.

关键词： Aircraft accidents

来源：评论

学校读者我要写书评

暂无评论

Revisiting the thermal ageing on the metallised polypropylene film capacitor:from device to dielectric film

引用

High Voltage 2023年第2期8卷 305-314页

作者： Yushuang He Feipeng Wang Guoqiang Du Lei Pan Kaizheng Wang Reimund Gerhard Ronald Plath Pawel Rozga Pavel Trnka State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing UniversityChongqingChina Faculty of Electrical Engineering Kunming University of Science and TechnologyKunmingChina Soft Transducer Materials and Systems Universität PotsdamPotsdamGermany Faculty IV Electrical Engineering and Computer Science Technische Universität BerlinBerlinGermany Institute of Electrical Power Engineering Lodz University of TechnologyLodzPoland Faculty of Electrical Engineering University of West BohemiaPilsenCzech Republic

Metallised polypropylene film capacitors(MPPFCs)are widely used in power electronics and are generally degraded by elevated *** work aims to determine the relationships between the structural changes of MPPFC and the microstructural variations of the PP film during the thermal ageing of MPPFC at 100℃ for 38 *** capacitance of MPPFC has a slight decrease during thermal ***,the breakdown voltage of the MPPFC decreases by 39.4%by the *** partial discharge(PD)number of MPPFC increases linearly with ageing *** tear-down analysis of the MPPFC reveals that the molecular structure of the PP film has not been altered but has led to molecular chain scission and the generation of some polar fragments/***,the relative permittivity of the PP films rises as the ageing time ***,thermal ageing causes the conversion of aluminum to alumina in the metallised electrode,which is hydrophilic for polar groups and leads to an adhesion effect between the metallised electrodes and the PP *** angle measurements prove that the surface hydrophilicity of the PP sample increased after thermal ***,the PD/breakdown voltage in the MPPFC increases/decreases due to the uneven adhesion of the metallised PP film.

关键词： film thermal ageing

来源：评论

学校读者我要写书评

暂无评论

ASSESSMENT OF THE SIGNIFICANCE OF FEATURES FOR THE IDENTIFICATION OF DOMESTIC APPLIANCES 27

ASSESSMENT OF THE SIGNIFICANCE OF FEATURES FOR THE IDENTIFIC...

引用

27th International Conference on Electricity Distribution, CIRED 2023

作者： Ma, Liya Schmidt, Maximilian Schegner, Peter Technische Universitaet Dresden Institute of Electrical Power Systems and High Voltage engineering Faculty of Electrical and Computer Engineering Dresden Germany

ISBN: (纸本)9781839539596

The load identification technologies in the domestic field, also called Non-Intrusive Load Monitoring (NILM), aim to break down the total electricity consumption at household level to the appliance level. This detailed information helps to identify the behaviour of users, deduce energy saving concepts, or provide live assistance for the residents. The NILM approaches are carried out with appliance features, such as the absorbed power, the voltage and current profile. They are defined as appliance-specific characteristics or features, which supposed to make the appliance clearly distinguishable from others. However, most of the publications focus on the identification algorithms. There is barely a contribution to analyse the significance of features. Hereby, the significance means, how consistent and reliable a feature differs from one appliance to another. This paper works on this question. Based on analyses of publications and own measurements, this paper gives an overview of the significance of representative features. Furthermore, suitable features for one-second data are selected and NILM is carried out. © The Institution of engineering and Technology 2023.

关键词： Domestic appliances

来源：评论

学校读者我要写书评

暂无评论

Spatial Attention Integrated EfficientNet Architecture for Breast Cancer Classification with Explainable AI

引用

computers, Materials & Continua 2024年第9期80卷 5029-5045页

作者： Sannasi Chakravarthy Bharanidharan Nagarajan Surbhi Bhatia Khan Vinoth Kumar Venkatesan Mahesh Thyluru Ramakrishna Ahlam AlMusharraf Khursheed Aurungzeb Department of Electronics and Communication Engineering Bannari Amman Institute of TechnologySathyamangalam638402India School of Computer Science Engineering and Information Systems(SCORE) Vellore Institute of TechnologyVellore632014India School of Science Engineering and EnvironmentUniversity of SalfordManchesterM54WTUK Department of Computer Science&Engineering Faculty of Engineering and TechnologyJAIN(Deemed-to-be University)Bengaluru562112India Department of Management College of Business AdministrationPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Adjunct Research Faculty Centre for Research Impact&OutcomeChitkara UniversityRajpura140401India

Breast cancer is a type of cancer responsible for higher mortality rates among *** cruelty of breast cancer always requires a promising approach for its earlier *** light of this,the proposed research leverages the representation ability of pretrained EfficientNet-B0 model and the classification ability of the XGBoost model for the binary classification of breast *** addition,the above transfer learning model is modified in such a way that it will focus more on tumor cells in the input ***,the work proposed an EfficientNet-B0 having a Spatial Attention Layer with XGBoost(ESA-XGBNet)for binary classification of *** this,the work is trained,tested,and validated using original and augmented mammogram images of three public datasets namely CBIS-DDSM,INbreast,and MIAS *** accuracy of 97.585%(CBISDDSM),98.255%(INbreast),and 98.91%(MIAS)is obtained using the proposed ESA-XGBNet architecture as compared with the existing ***,the decision-making of the proposed ESA-XGBNet architecture is visualized and validated using the Attention Guided GradCAM-based Explainable AI technique.

关键词： EfficientNet mammograms breast cancer Explainable AI deep-learning transfer learning

来源：评论

学校读者我要写书评

暂无评论

Sigma-Delta Modulation for Enhanced Underwater Optical Wireless Communication systems 23

Sigma-Delta Modulation for Enhanced Underwater Optical Wirel...

引用

23rd International Conference on Transparent Optical Networks, ICTON 2023

作者： Araújo, João H. Rocha, Henrique J. Tavares, Joana S. Salgado, Henrique M. Technology and Science INESC TEC - Institute for Systems and Computer Engineering Porto Portugal University of Porto Faculty of Engineering Porto Portugal

ISBN: (纸本)9798350303032

This paper presents an experimental investigation of sigma-delta modulation (SDM) as a means of improving the performance of underwater optical communication systems. The study considers the impact of the key parameters of SDM, including oversampling ratio, the system's signal-to-noise ratio, bandwidth, and optical link distance. The results of this study provide insights into the design and optimization of SDM-based underwater optical communication systems, paving the way for future research in this field. A fully digital solution, albeit operating at a lower bit rate than previously published OFDM counterparts, provides immunity against nonlinearities of the system and robustness to noise, which is relevant in harsh environments. Moreover, the proposed solution based on a first-order bandpass SDM architecture avoids the employment of a DAC at the receiver, simplifying its operation and reducing costs. An experimental investigation is carried out for the transmission of 16-QAM over SDM, and a transmission distance of 4.8 m over the underwater channel is achieved with a maximum transmission rate of 400 Mbit/s with an MER of 28 dB. © 2023 IEEE.

关键词： Delta sigma modulation

来源：评论

学校读者我要写书评

暂无评论

SP-DSTS-MIMO Scheme-Aided H.266 for Reliable High Data Rate Mobile Video Communication

引用

computers, Materials & Continua 2023年第1期74卷 995-1010页

作者： Khadem Ullah Nasru Minallah Durre Nayab Ishtiaque Ahmed Jaroslav Frnda Jan Nedoma Department of Computer Systems Engineering University of Engineering and Technology PeshawarPeshawar25000Pakistan National Centre in Big Data and Cloud Computing University of Engineering and Technology Peshawar(NCBC-UETP)Peshawar25000Pakistan Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and CommunicationsUniversity of Zilina01026ZilinaSlovakia Department of Telecommunications Faculty of Electrical Engineering and Computer ScienceVSB-Technical University of OstravaOstrava-PorubaCzech Republic

With the ever growth of Internet users,video applications,and massive data traffic across the network,there is a higher need for reliable bandwidth-efficient multimedia *** Video Coding(VVC/H.266)is finalized in September 2020 providing significantly greater compression efficiency compared to Highest Efficient Video Coding(HEVC)while providing versatile effective use for Ultra-High Definition(HD)*** article analyzes the quality performance of convolutional codes,turbo codes and self-concatenated convolutional(SCC)codes based on performance metrics for reliable future video *** advent of turbo codes was a significant achievement ever in the era of wireless communication approaching nearly the Shannon *** codes are operated by the deployment of an interleaver between two Recursive Systematic Convolutional(RSC)encoders in a parallel *** RSC encoders may be operating on the same or different architectures and code *** proposed work utilizes the latest source compression standards H.266 and H.265 encoded standards and Sphere Packing modulation aided differential Space Time Spreading(SP-DSTS)for video transmission in order to provide bandwidth-efficient wireless video ***,simulation results show that turbo codes defeat convolutional codes with an averaged E_(b)/N_(0) gain of 1.5 dB while convolutional codes outperformcompared to SCC codes with an E_(b)/N_(0) gain of 3.5 dBatBit ErrorRate(BER)of 10−*** Peak Signal to Noise Ratio(PSNR)results of convolutional codes with the latest source coding standard of H.266 is plotted against convolutional codes with H.265 and it was concluded H.266 outperform with about 6 dB PSNR gain at E_(b)/N_(0) value of 4.5 dB.

关键词： H.265 RSC turbo codes SCC SP-DSTS BP-CNN BER PSNR

来源：评论

学校读者我要写书评

暂无评论

IoT Sensor Deployment in the Wildland Urban Interface: Leveraging Fire Risk Analysis 10

IoT Sensor Deployment in the Wildland Urban Interface: Lever...

引用

10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Purcell, Richard Naik, Kshirasagar Zaman, Marzia Lung, Chung-Horng Sampalli, Srinivas Mutakabbir, Abdul Dhindsa, Manavjit Singh Das, Ursula Dalhousie University Faculty of Computer Science HalifaxNS Canada University of Waterloo Electrical and Computer Engineering WaterlooON Canada Research and Development Cistel Technology OttawaON Canada Carleton University Systems and Computer Engineering OttawaON Canada

ISBN: (纸本)9798350373011

This paper investigates algorithms for distributing Internet of Things sensors within the Wildland-Urban Interface to enhance early wildland fire detection. Using geospatial data analysis and a validated wildland fire growth model, we generated burn maps to guide sensor placement strategies across a defined region. We evaluated even grid distribution, random distributions, and genetic algorithm-based methods, testing each against 50,000 burn maps with sensor counts ranging from 50 to 800. Results indicate that while even grid distribution achieved the highest detection rates, its practicality in real-world applications is limited. Genetic algorithms showed promise but require further exploration to simulate field deployment accurately. Notably, weighting sensor placement based on wildland fire growth risk did not significantly impact detection effectiveness, highlighting the need for further research into the representativeness of burn maps. © 2024 IEEE.

关键词： Genetic algorithms

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：