检索结果-内蒙古大学图书馆

An automated speech analysis system for the detection of cognitive decline in elderly

International Journal of Speech technology 2023年第2期26卷 337-353页

作者： Loizou, Christos P. Pantzaris, Marios Faculty of Engineering & Technology Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology 30 Arch. Kyprianos Str. Office 420 Limassol3036 Cyprus Cyprus Institute of Neurology and Genetics P. O. Box 23462 Nicosia1683 Cyprus

The goal of this study is to develop and test an automated integrated speech analysis system for detecting mild cognitive impairment (MCI) and dementia in spontaneous free speech. During the years 2010–2016, speech recordings (N = 2800) were obtained from 200 Greek Cypriots over the age of 65. These were divided into three groups (G1, G2, and G3) based on the results of their Mini-mental state examination (MMSE): G1:95 normal (NOR) individuals with an MMSE greater than 26;G2:65 MCI subjects with 20 ≤ MMSE ≤ 26;G3:40 dementia subjects with 0 ≤ MMSE © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

Federated Learning Empowered Breast Cancer Detection in Images: A YOLO and ResNet-50 Fusion Approach

Federated Learning Empowered Breast Cancer Detection in Imag...

引用

2024 International Conference on Computational Intelligence and Computing Applications, ICCICA 2024

作者： Trivedi, Naresh Kumar Jain, Sachin Kaswan, Suresh Jain, Vishal Chitkara University Institute Of Engineering And Technology Chitkara University Punjab India Ajay Kumar Garg Engineering College Department Of Computer Science And Engineering Ghaziabad India Sharda University Sharda School Of Engineering & Technology Department Of Computer Science & Engineering UP Greater Noida India Chandigarh University Department Of Computer Science & Engineering Punjab India

ISBN: (纸本)9798350306446

In the world, breast cancer kills more women than any other disease. An accurate forecast model was created, and the highest risk was identified by a data mining-based classification effort that used many approaches. The development of automated breast cancer diagnostic tools has been enabled by advances in data mining and machine learning. It is possible to tell benign breast lesions from malignant ones during a breast cancer diagnosis. More than that, people who have had tumors surgically removed can be given prognoses that tell them when the cancer will return. Consequently, the issues surrounding categorization include these two concerns. There are a lot of data mining techniques used to categorize patients as either "cancerous"or "non-cancerous"in this field. Breast cancer diagnostic concerns are thus encapsulated in the domain of hotly debated classification issues. This work used deep learning to diagnose breast cancer via federated learning while protecting user and hospital data. This study uses YOLO and RestNet-50 DL models. YOLO trains RestNet using client data. The server receives client-trained models for global model integration. Integration gives the client access to the global model for performance evaluation. The suggested model outperforms another state-of-the-art deep learning model in the identical scenario with 98.73% accuracy when all clients receive data equally. The federated research environment has hyper-performance elements like many clients and communication cycles. © 2024 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

VANET Handoff from IEEE 80.11p to Cellular Network Based on Discharging with Handover Pronouncement Based on Software Defined Network (DHP-SDN) 22nd

VANET Handoff from IEEE 80.11p to Cellular Network Based on ...

引用

22nd International Conference on Hybrid Intelligent Systems, HIS 2022 and the 18th International Conference on Information Assurance and Security, IAS 2022

作者： Sarvavnan, M. Narayanan, R. Lakshmi Kavitha, K. Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Networking and Communications SRM Institute of Science and Technology Chennai India Department of Computer Science and Engineering Kongu Engineering College Erode India

ISBN: (纸本)9783031274084

In Vehicular Adhoc Network (VANET) is an emerging domain with high dynamic mobility and disrupted network in Discharging with Handover Pronouncement based on Software Defined Network (DHP-SDN) with advance predictive management tool described in this work for discharging of vehicle-to-infrastructure communication with Software Defined Network (SDN) architecture. Various parameters were addressed in research articles like maintaining connectivity, identifying appropriate intermediate node for carrying signal and transferring of data but in the proposed model SDN monitors the discharging signal based on the speediness, terrestrial location, nearby vehicle RSU from the vehicle which has cellular and IEEE 802.11p network boundary. SDN regulator computes when the due time is to settle on a choice, chooses whether it is appropriate or not have the vehicle to handoff from cell organization to the ahead IEEE 802.11p organization. The simulation results that using DHP-SDN method maintains the networking quality by reducing the load and traffic congestion. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Movie Sense—Hybrid Movie Recommendation System with Sentimental Analysis 3rd

Movie Sense—Hybrid Movie Recommendation System with Sentime...

引用

3rd International Conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Sudhane, G. Sai Rao, G. Venkateswara Vani, V. Karthik, N. Department of Electrical and Electronics Engineering Puducherry India Department of Computer Science and Engineering National Institute of Technology Puducherry Puducherry Karaikal609609 India

ISBN: (纸本)9789819783540

Post-pandemic, with the advent of many OTT platforms, there are a number of different movies and web series available which makes it difficult for the users to find a suitable movie to watch. So the movie recommendation system helps the users by recommending some movies based on their past search history, their interests and also considering the movie genre, actors, director and movie ratings. Our system uses a hybrid filtering technique which makes the system suitable for new users as well by considering the interests of various other users using SVD. Sentimental Analysis is done using a Sentiment Intensity Analyzer (SIA). Since it uses the most accurate methods, it makes the system a robust one. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Hybrid Algorithm for Secure Routing in MANET Using Cryptographic Applications

Hybrid Algorithm for Secure Routing in MANET Using Cryptogra...

引用

2024 IEEE International Conference on Electronic Systems and Intelligent Computing, ICESIC 2024

作者： Muruganandam, S. Gnanavel, S. Narayana, K.E. Jaeyalakshmi, M. Antony Kumar, K. Panimalar Engineering College Department of Computer Science and Business Systems Chennai India SRM Institute of Science and Technology Kattankulathur Campus Faculty of Engineering and Technology Department of Computing Technologies Chengalpattu India Rajalakshmi Engineering College Department of Information Technology Chennai India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr Sagunthala R and D Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331522988

In Mobile sensor Networks, Each and every wireless node dynamically changes its location due to its mobility nature. The routing information is maintained by the master node to deliver a data packet from source to destination. The attackers easily hack this wireless network. The performance of the complete networks is dropped by packets transmission attacks. Attacker node drops the packet. An enhanced protection technique in response to packets transmission misbehaviour attacks is provided to increase the energy efficiency of mobile nodes. This paper proposed the Cryptographic formed Malicious Node Detection and Secure Routing framework (CMNDSR). This model incorporates three various strategies specially algorithm for control of access, to protects initial illegal node in the network. The suspected identification and prevention techniques based on hop count value. Secure routing method with a private key generated at random like one time password (OTP). The proposed methods are power efficient, by operating a minimum number of nodes in challenging environment. The misbehaviour nodes are promptly identified and isolated using this proposed approach. The Cryptographic based Secure routing algorithm is applied to provide secure transmission in wireless networking environment. The outcomes of the simulation display how effectively the recommended approach can identify malicious nodes in a MANET. In comparison with previous methods, the energy consumption is 10% lower and the suspicious node detection rate is increased by 95%. © 2024 IEEE.

关键词： Encryption algorithms

来源：评论

学校读者我要写书评

暂无评论

Automated Breast Cancer Diagnosis Using Deep Learning CNN Models 2

Automated Breast Cancer Diagnosis Using Deep Learning CNN Mo...

引用

2nd IEEE International Conference on Emerging Research in Computational Science, ICERCS 2024

作者： Saravanan, G. Jeevanantham Prabin, S.M. Parthasarathy, R. VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Chennai India Vellore Institute of Technology School of Computer Science and Engineering Vellore India VelTech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Design Chennai India

ISBN: (纸本)9798331534950

The study introduces a deep learning model, CCNN, developed to identify and classify eight types of breast cancer: normal adenosis, normal fibroadenoma, normal phyllodes tumor, normal tubular adenoma, malignant ductal carcinoma, malignant lobular carcinoma, malignant mucinous carcinoma, and malignant papillary carcinoma. This model was integrated with five pre-existing models - Xception, InceptionV3, VGG19, MobileNetV2, and ResNet101 - all trained for image classification using the ImageNet database, to categorize breast cancer MRI images. The dataset, sourced from Kaggle's repository, was further augmented using the Generative Adversarial Network (GAN) technique. For 30 experiments carried out to evaluate the introduced model and the transfer learning of five and proposed CCNN models, the F1-score values accuracy yielded were respectively: 98.04%, 96.13%, 98.54%, 97.11%, 94.20% and 98.98%. This study emphasizes the importance of improving the accuracy of early breast cancer detection to enhance the survival rates of patients. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Bottleneck-Minimal Indexing for Generative Document Retrieval 41

Bottleneck-Minimal Indexing for Generative Document Retrieva...

引用

41st International Conference on Machine Learning, ICML 2024

作者： Du, Xin Xiu, Lixin Tanaka-Ishii, Kumiko Waseda Research Institute for Science and Engineering Waseda University Japan Department of Mathematical Informatics The University of Tokyo Japan Department of Computer Science and Engineering Waseda University Japan

We apply an information-theoretic perspective to reconsider generative document retrieval (GDR), in which a document x ∈ X is indexed by t ∈ T, and a neural autoregressive model is trained to map queries Q to T. GDR can be considered to involve information transmission from documents X to queries Q, with the requirement to transmit more bits via the indexes T. By applying Shannon's rate-distortion theory, the optimality of indexing can be analyzed in terms of the mutual information, and the design of the indexes T can then be regarded as a bottleneck in GDR. After reformulating GDR from this perspective, we empirically quantify the bottleneck underlying GDR. Finally, using the NQ320K and MARCO datasets, we evaluate our proposed bottleneck-minimal indexing method in comparison with various previous indexing methods, and we show that it outperforms those methods. Copyright 2024 by the author(s)

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Supermarket Billing System using Webcam 2

Supermarket Billing System using Webcam

引用

2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Naik, S.K. Lokesh Ganesh, D. Srilakshmi, Ch. Reddy, V. Surya Narayana Sirisha, N. Kiran, Ajmeera Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India Vardhaman College of Engineering Department of Cse Hyderabad India Vnr Vignana Jyothi Institute of Enginnering and Technology Department of It Hyderabad India Bvrit Hyderabad College of Engineering for Women Department of Cse Hyderabad India Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad Dundigal India

ISBN: (纸本)9798350370188

We save time and energy by shopping in supermarkets, which provide a big selection. RFID technology helps stores streamline billing. RFID employs radio waves to automatically identify and track tags on things. This technology can speed up barcode scanning. Products with RFID tags can be scanned swiftly by an RFID reader. This will speed up barcode scanning, reducing client wait time. It will also reduce barcode scanning errors. Customers can also pay with credit/debit cards, online wallets, etc. This will speed up payments. The system can also offer loyalty points and incentives to boost client satisfaction. The technology tracks inventory levels and alerts the store when they drop. It will prevent stores from running out of goods. It also keeps transaction records for future examination. It can also detect fraudulent purchases and notify the store. This will reduce theft and fraud. The webcam-based billing system will speed up bill generation and payment and make it more convenient for customers. It will also monitor inventory and detect fraud. © 2024 IEEE.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Advanced Techniques for Early Prediction from CT Scans 4

Advanced Techniques for Early Prediction from CT Scans

引用

4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Sachdeva, Vrinda Mishra, Nitin Kumar, Arun Singh, Neeru G.L Bajaj Institute of Technology and Management Department of Computer Science Engineering Greater Noida India Its Engineering College Department of Computer Science Engineering Greater Noida India G.L Bajaj Institute of Technology and Management Department of Information Technology Greater Noida India

ISBN: (纸本)9798350364729

Visual representation holds significant significance in the healthcare industry. Healthcare professionals previously utilized medical imagery to accurately diagnose diseases and offer food to patients. Healthcare professionals occasionally encountered difficulties in diagnosing operations as a result of intricate medical imaging. Cancer is a noncommunicable disease that is difficult to detect in its early stages. The death rate of human beings rises annually as a result of inaccurate diagnosis. The researchers are encountering a significant obstacle in the analysis of medical imagery connected to cancer. The early detection of cancer is a significant obstacle that must be overcome. Therefore, it is imperative to preprocess medical images in order to detect important aspects. This study applies various image preprocessing algorithms to medical images of lung cancer. An analysis is conducted using a comparison-based approach. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Textile Defect Classification Using Deep Convolutional Neural Networks (DCNN) 5th

Textile Defect Classification Using Deep Convolutional Neura...

引用

5th International Conference on Innovative Product Design and Intelligent Manufacturing Systems, ICIPDIMS 2023

作者： Potluru, Sri Sashank Karnati, Tarun Mande, Ramesh Gudavalli, Hruthi sri Miriyala, Sai Manikanta Department of Information Technology V R Siddhartha Engineering College Vijayawada India Department of Computer science SRK Institute of Technology Vijayawada India

ISBN: (纸本)9789819767311

The textile industry has a standing history and offers a diverse range of products, such as clothing, home furnishings, and more. The quality of the product is undeniably impacted by the fabric’s quality. The caliber of the merchandise is undeniably impacted by the fabric’s quality. Still, several complications can surface during the fabric production process due to factors, like imperfect yarn or mechanical glitches. Neglecting these flaws can incur losses and harm the brand’s reputation. At times, researchers have put forth machine learning techniques, like CNN, RCNN, and others to detect defects in fabrics. However, there is still a challenge in achieving time and accurate segmentation and classification of these defects. This research paper introduces an new approach that combines the power of DCNNs with the efficiency of the YOLOv7 detection mechanism to bridge this gap. We propose a network architecture that includes preprocessing feature extraction using ResNet-50 and defect detection using YOLOv7 and then classify the fabric defect into their category using a deep convolutional neural network. This results in classification of fabric defects. Impressively, this network achieves an accuracy of 96.29%. By conducting this study, we hope to raise the bar for fabric defect detection and offer the textile industry a reliable, automated, and extremely precise instrument for ensuring fabric quality. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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：