检索结果-内蒙古大学图书馆

3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Shreevatsan, S.S. Annambhotla, Yasasree Lasya Reji, Anaswara Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This study compares different scheduling algorithms used in edge computing for real-time video processing. Instead of sending video data to cloud servers, the video is processed directly at the edge, reducing delays and saving bandwidth. The focus is on how different scheduling methods manage resources, prioritize tasks, and reduce the time it takes to analyze video. The algorithms are tested in simulated environments to understand how they impact system efficiency and performance. The goal of this work is to find the best scheduling policies for real-time video processing at the edge, improving overall system performance and scalability. © 2025 IEEE.

关键词： Scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Locating and Routing for IoT-Based Fire Evacuation System 5th

Locating and Routing for IoT-Based Fire Evacuation System

引用

5th International Conference on computing and Network Communications, CoCoNet 2023

作者： Krishnan, Vineeth Santhosh Kumar, Govind Anand, Prarthana Rajesh, M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9789819745395

Fire in skyscrapers and high-rise building is inevitable due to huge volumes of thick gauged wires crawling all over the building, the rise in the number of electronic equipment inside and highly unpredictable acts of nature. These fires turn devastating when the latency in the response and evacuation system is not able to keep up with the enormity associated with modern towering buildings. As we move on to a more connected world, the amount of data generated by the equipment inside the building can now not only be used for their intended purpose. But together they provide a clearer and accurate view of the situation inside the building in real time. This Connected Fire Evacuation System takes in data from the various sensors as well as CCTV devices inside the building to present a real-time link for assisting trapped occupants by actively locating them and planning an escape route for them. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Fire extinguishers

来源：评论

学校读者我要写书评

暂无评论

Image Compression Algorithms - Comparative Analysis 3

Image Compression Algorithms - Comparative Analysis

引用

3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Niharika Reddy, G. Namrutha, M. Akshaya, Namratha Bhaskaran, Sreebha Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508456

Due to the abundance of the new digital media data, the issue of image quality and volume of data requiring compression has become a significant factor of concern, especially in media storage and transmitting. This work affords a comparative analysis of different image compression techniques with focus on the compression ratio, quality preservation, and complexity. A new hybrid model of Predictive Coding, Run Length Coding and Quantum Entropy Coding (QEC) is proposed and shown to exhibit negligible quality loss with substantial space saving. The experimental outcomes show that the proposed method reduces space 80 percent and works better than previous methods for areas requiring high speed and relative accuracy. These insights are timely, as practical computing-communication trade-offs are paramount in the new generation of social networks, medicine, and multimedia streaming. © 2025 IEEE.

关键词： Image compression

来源：评论

学校读者我要写书评

暂无评论

Parasitic Patch Antenna with Beam Switching for 5G Millimeter-Wave Frequencies 10

Parasitic Patch Antenna with Beam Switching for 5G Millimete...

引用

10th International Conference on engineering and Emerging Technologies, ICEET 2024

作者： Nurgali, Raiymbek Ahmad, Jawad Hashmi, Mohammad School of Engineering and Digital Science Nazarbayev University Department of Electrical and Computer Engineering Astana Kazakhstan

ISBN: (纸本)9798331532895

This paper presents a novel millimeter-wave (mmWave) antenna design for 5G applications, featuring a parasitic elliptical patch antenna with beam-switching capabilities and coaxial feeding. The antenna was initially designed as a single-element patch antenna for the 28 GHz mmWave band, demonstrating favorable impedance matching and broadside radiation patterns. Circular parasitic patches with and without vias were strategically placed around the main radiator to enhance the radiation pattern and gain. The single-element design achieved an impedance bandwidth of 2.7 GHz (26.8-29.5 GHz) and a gain of 7.5 dBi at 28 GHz. The optimized parasitic structure, consisting of carefully positioned open and short circular patches, significantly improved the antenna's performance. The parasitic design exhibited an enhanced return loss of -30.5 dB, indicating excellent impedance matching, and a gain of approximately 8 dBi. The proposed antenna exhibits enhanced performance characteristics in terms of gain, return loss, and beam steering capabilities, and it is suitable for next-generation wireless communication systems. © 2024 IEEE.

关键词： Slot antennas

来源：评论

学校读者我要写书评

暂无评论

Speech Emotion Recognition Using Machine Learning 5th

Speech Emotion Recognition Using Machine Learning

引用

5th International Conference on computing and Network Communications, CoCoNet 2023

作者： Veeramaneni, Asritha Samitha, V. Charitha, Talluri Shriya, Sagi Singh, Tripty Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9789819747108

Speech emotion recognition (SER) is a technique for accurately determining a person’s emotion from their speech. Enhancing communication between people and machines. Even though emotions are arbitrary, it can be hard to annotate audio and it’s still hard to gauge someone’s emotional state. It now plays a crucial part in technological research as new technologies for human machine or medical applications are developed. It is obvious that surprise and rage feelings are more accurately predicted by our model than other emotions, It is understandable given how significantly the pitch, speed, and other qualities of the audio files for these emotions differ from those of other audio files. The system can capture and analyze various acoustic elements contained in voice signals using the SVM-based architecture and enabling the identification and categorization of various moods. Mel frequency cepstral coefficients (MFCCs), pitch, energy, and spectral features are some of these features, and they all work together to reveal important details about the emotional content that is present in speech. The deployed models attain a remarkable accuracy of 80% in identifying various emotional states from speech data after extensive training and optimization. This level of accuracy shows how well the suggested method works in properly classifying emotions based on auditory characteristics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Weighted Average Ensembled Probability Pipeline of Pre-trained CNN Models for Hand Gesture Classification 15

Weighted Average Ensembled Probability Pipeline of Pre-train...

引用

15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Gunti, Rahul Rohan Reddy, B. Swathi, Gunti Sharath Kumar Reddy, G. Vardhaman College of Engineering Department of Computer Science and Engineering Hyderabad India Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai601103 India Vellore Institute of Technology School of Computer Science and Engineering Vellore India

ISBN: (纸本)9798350370249

The automatic detection of sign language from hand gesture images is fundamental for effective human-computer interaction, especially for individuals with hearing and speech disorders. Achieving accurate detection and classification of sign language gestures is paramount. However, accurately recognizing these gestures frequently presents challenges due to dull backgrounds, variations in gesture orientation, and fluctuations in lighting conditions. Previous approaches tried to overcome these challenges but still the model performance lacks recognition accuracy and visual quality. To address this need for accuracy, we proposed a Weighted Average Ensembled Probability Pipeline composed of EfficientNetB7, ResNet-50, and Xception models. Leveraging the Extensive Hand Gesture Recognition Database (HGRD), comprising 20,000 images, our individual models achieved notable accuracies: 96.498 % for EfficientNetB7, 93.2 % for ResNet-50, and 90.175 % for Xception. Through ensemble learning, we integrate these models to attain an impressive overall accuracy of 98.95 %. This research contributes to robust gesture recognition system and underscores the significance of ensemble techniques in enhancing performance for Gesture recognition systems. © 2024 IEEE.

关键词： Gesture recognition

来源：评论

学校读者我要写书评

暂无评论

Automated Semantic Segmentation of Cervical Cells Using High-Resolution Network 5

Automated Semantic Segmentation of Cervical Cells Using High...

引用

5th IEEE International Conference on Advances in electrical, computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Resmi, S. Singh, Rimjhim Padam Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350356236

With an emphasis on the Cx22 dataset, this work offers a novel method of semantic segmentation applied to cervical cytology images. To precisely segment cervical cell structures within the images, the study makes use of deep learning techniques. In this work we are proposing different deep network models, U-Net, LinkNet, PSPNet and HRNet to perform semantic segmentation of the cells in the cervical cytology images. The performance evaluation of all the models are done using the high quality Cx22 dataset with 14,946 finely annotated cellular instances and the HRNet deep model gives better segmentation results and shows its effectiveness in accurately drawing cell boundaries. The outcomes demonstrate how our method can improve automated cervical cytology analysis with a very good F-score of 92% which leads to improvements in diagnostic support and medical image processing. © 2025 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Customer Segmentation Analysis Using Clustering Algorithms 3rd

Customer Segmentation Analysis Using Clustering Algorithms

引用

3rd International Conference on Machine Learning, Internet of Things and Big Data, ICMIB 2023

作者： Reddy, Biyyapu Sri Vardhan Rishikeshan, C.A. Dagumati, VishnuVardhan Prasad, Ashwani Singh, Bhavya School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9789819939312

Customer segmentation has been deployed as a prudent marketing strategy by companies to ensure that their investments are less risky and more judicious. Segmenting customers helps the companies to divide the customers into groups that reflect similarity and maximize the value of each customer to the business. The main goal of this research is to use a machine learning clustering approach called K-means clustering to accomplish consumer segmentation. Besides, the research work is also focused on performing exploratory data analysis on the given dataset. To group the customers into clusters, a K-means clustering algorithm is performed on the customer dataset. To achieve optimization and validation of the clusters, popular heuristic, interpretation, and approximation methods have been included in this paper. Further, for analyzing and visualizing the important facets of the customer dataset and the operation of the K-means algorithm, the paper presents some colorful and informative representations. The implementation of this research work has been done in the R programming language. The outcome of this work includes visualizing the segments of the mall customers in the form of clusters based on their spending scores and annual incomes. Furthermore, a better customer segmentation could be achieved by taking product reviews and customer feedback into consideration. Nevertheless, customer segmentation remains a prospective topic for many researchers and companies due to dynamic customer behavior. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： K-means clustering

来源：评论

学校读者我要写书评

暂无评论

SMART DRIVING LICENSING SYSTEM AND AUTHORIZATION OF AUTONOMOUS VEHICLE INTEGRATING WIRELESS SENSOR NETWORKS AND IoT

引用

Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2024年第9期83卷 69-85页

作者： Santhakumar, D. Sudhan, M.B. Prasanna, R. Manikandan, S.P. Prathaban, Banu Priya Kanna, Rajesh R. Saravanan, G. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai Ramapuram India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering Sree Sastha Institute of Engineering and Technology Chennai India Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering Sri Sairam Institute of Technology Tamil Nadu Chennai India

The advent of autonomous vehicles has revolutionized the automotive industry, offering promising advancements in safety, efficiency, and mobility. To integrate these autonomous vehicles into our society seamlessly, it is imperative to establish a robust licensing system that ensures the safe operation of automated vehicles on public roads. This article presents an effective smart Driving Licensing System (SDLS), a digital framework designed to regulate the existing licensing system and authorize licensing for autonomous vehicles. Through a comprehensive assessment process, the system assesses the drivers and the autonomous vehicle’s ability to navigate various road conditions, respond to dynamic environments, and prioritize safety for passengers and other road users. SDLS integrates high-level security through facial and fingerprint verification for identity verification to preserve licensing data. Hacking and unauthorized access to autonomous vehicles is prevented by robust cybersecurity protocols. The key benefits of SDLS include automated data collection, integration of wireless sensor networks (WSN) and Internet of Things (IoT), smart application processing, real-time license checks, cybersecurity measures, automated testing, and digital certification. The proposed system offers a comprehensive approach to safely integrating autonomous vehicles into our transportation ecosystem. The autonomous vehicles are integrated with antennas at rooftops or into bumpers, depending upon the vehicle design which can be connected with the SDLS for signal communication. Furthermore, the SDLS establishes a framework for continuous monitoring and updates, enabling ongoing assessments to keep pace with evolving technology and safety standards. © 2024 by Begell House, Inc.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

A4RSIC: Attention-Augmented Adversarial Autoencoder for Remote Sensing Image Compression

A4RSIC: Attention-Augmented Adversarial Autoencoder for Remo...

引用

2025 International Conference on Emerging Technologies for Intelligent Systems, ETIS 2025

作者： Sivarajan, Saran Byju, Akshara Preethy School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Kerala Amritapuri India

ISBN: (纸本)9798331507541

Reconstruction of images from the recent deep learning based models for image compression tasks does not necessarily corroborate with human perception and lose relevant inherent structural details. To address this, in this research work, a novel deep attention-augmented adversarial autoencoder based lossy remote sensing image compression (A4RSIC) approach is proposed that achieves superior compression ratio compared to the state-of-the-art methods. The A4RSIC model embeds an encoder-generator duo to generate a compact latent vector representation of the input image, which is then used to reconstruct the original image with minimal loss. The proposed model utilizes a discriminator, trained to differentiate between real and A4RSIC generated images using an adversarial approach, ensuring the fidelity of the reconstructed images. Furthermore, the model integrates a convolutional block attention module (CBAM) at relevant strategic points within the encoder and generator to enhance the salient features by leveraging spatial and channel-wise attention mechanism. This improves the quality of feature representation and compression performance. Experimental results demonstrate the efficacy of the proposed method compared to JPEG as well as other state-of-the-art methods. © 2025 IEEE.

关键词： Image compression

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：