检索结果-内蒙古大学图书馆

10th Scholar's Yearly Symposium of Technology, engineering and Mathematics, SYSTEM 2024

作者： Iacobelli, Emanuele Pelella, Davide Ponzi, Valerio Russo, Samuele Napoli, Christian Department of Computer Automatic and Management Engineering Sapienza University of Rome Rome00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Roma00185 Italy Department of Psychology Sapienza University of Rome Rome00185 Italy Department of Computational Intelligence Czestochowa University of Technology Czestochowa42-201 Poland

Eye-tracking technology has long been a valuable tool across various domains, and recent advancements in neural networks have significantly expanded its versatility and potential. However, real-world applications continue to face challenges such as accommodating users’ natural movements, variations in lighting, occlusions of the eyes, and the limited availability of large, open-source datasets for training models. To address these issues, we developed a comprehensive pipeline that produces a lightweight and efficient model, requiring only an RGB camera as external hardware, making it easily deployable on standard PCs. Key input features include facial images, eye regions, head pose angles, the Eye Aspect Ratio (EAR), and a face grid that determines the face’s location within the camera’s frame. The model was trained using a custom dataset, in which participants were instructed to fixate on both randomly positioned points and the standard 9-point grid commonly employed in eye-tracking calibration. The resulting system was integrated into a real-time application, offering fast and accessible gaze tracking, making it well-suited for studies requiring rapid gaze assessments across broad regions of the screen, such as psychometric research and Human-computer Interaction (HCI) tasks. Its design is particularly advantageous for gaze laterality studies, which explore hemispheric dominance and attentional bias in cognitive and emotional processing, key concepts relevant to ADHD and dyslexia. Moreover, the system’s capabilities naturally extend to emotional and decision-making tasks, where broad-area gaze tracking can support the analysis of preference formation and attentional patterns without the need for specialized hardware. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Open systems

来源：评论

学校读者我要写书评

暂无评论

Trust-Region Based Stochastic Variational Inference for Distributed and Asynchronous Networks

引用

Journal of Systems science & Complexity 2022年第6期35卷 2062-2076页

作者： FU Weiming QIN Jiahu LING Qing KANG Yu YE Baijia Department of Automation University of Science and Technology of ChinaHefei 230027China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China School of Computer Science and Engineering and Guangdong Province Key Laboratory of Computational ScienceSun Yat-Sen UniversityGuangzhou 510006China Institute of Advanced Technology University of Science and Technology of ChinaHefei 230027China

Stochastic variational inference is an efficient Bayesian inference technology for massive datasets,which approximates posteriors by using noisy gradient *** stochastic variational inference can only be performed in a centralized manner,which limits its applications in a wide range of situations where data is possessed by multiple ***,this paper develops a novel trust-region based stochastic variational inference algorithm for a general class of conjugate-exponential models over distributed and asynchronous networks,where the global parameters are diffused over the network by using the Metropolis rule and the local parameters are updated by using the trust-region ***,a simple rule is introduced to balance the transmission frequencies between neighboring nodes such that the proposed distributed algorithm can be performed in an asynchronous *** utility of the proposed algorithm is tested by fitting the Bernoulli model and the Gaussian model to different datasets on a synthetic network,and experimental results demonstrate its effectiveness and advantages over existing works.

关键词： Asynchronous networks Bayesian inference distributed algorithm stochastic variational inference trust-region method

来源：评论

学校读者我要写书评

暂无评论

A Visual Attention-Based Model for Bengali Image Captioning

引用

SN computer science 2023年第2期4卷 208页

作者： Das, Bidyut Pal, Ratnabali Majumder, Mukta Phadikar, Santanu Sekh, Arif Ahmed Department of Information Technology Haldia Institute of Technology West Bengal Haldia 721657 India Department of Applied Mathematics NIT Durgapur West Bengal Durgapur 713213 India Department of Computational Science Brainware University West Bengal Kolkata 700125 India Department of Computer Science and Technology University of North Bengal West Bengal Siliguri 734014 India Department of Computer Science and Engineering Maulana Abul Kalam Azad University of Technology W.B. West Bengal Haringhata 741249 India School of Computer Science and Engineering XIM University Odisha Bhubaneswar 752050 India

Image caption or description generation is a fundamental task that involves computer vision (CV) and natural language processing (NLP) ideas to recognize an image-context and produces description(s) using a natural language. Bengali is one of the world’s most commonly spoken languages, ranking fifth. For this reason, large research achievements have been recognized to image captioning, i.e. explaining images with grammatically correct and semantically meaningful Bengali sentences. Many established datasets exist for image caption generation in English, but no standard dataset is available for Bengali. This paper proposes a model for generating automatic image captions in the Bengali language. This study uses only two initial available Bengali datasets to train the encoder-decoder neural network model. We have curated the human errors available in the datasets and benchmarked. Experimental results of this proposed model performs better than other baseline models using these datasets. It achieved 0.67 and 0.65 BLEU-1, and 0.26 and 0.24 BLEU-4 respectively. We expect that our research will take attentions to more researchers from regional language understanding and accelerate Bengali vision-language understanding. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Attention mechanism Bengali image caption Bengali NLP Deep learning Image description

来源：评论

学校读者我要写书评

暂无评论

IoT Wearable Breast Temperature Assessment System 7

IoT Wearable Breast Temperature Assessment System

引用

7th International Conference on Computing Methodologies and Communication, ICCMC 2023

作者： Ashreetha, B. Dankan Gowda, V. Anandaram, Harishchander Nithya, B.A. Gupta, Neeraj Verma, Basant Kumar Department of Electronics & Communication Engineering College Sree Vidyanikethan Engineering College Andhra Pradesh Tirupati India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Karnataka Bangalore India Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Tamilnadu Coimbatore India Department of Computer Science School of Applied Sciences Reva University Karnataka Bengaluru India Department of Computer Science and Engineering SGT University Haryana Gurugram India

ISBN: (纸本)9781665464086

Cancer is an undesirable cell with odd characteristic varies from normal cell of the breast tissue. This will develop swiftly and infiltrate surrounding tissue and forms as tumor which happens in both men and women. After lung cancer, breast cancer has become the largest cause of malignancies in women which raise the mortality rate. In this article, Sensor enabled wearable device framework to detect breast temperature abnormalities is suggested. Early work on wearable sensors supported to monitor breast temperature is presented. The concept of a wearable garment with sensor-enabled patches is also considered. Detailed architecture of the proposed framework is explained, and implementation specifics are examined. Later the statistical highlights help to process the sensor-generated breast temperature data are explained. The performance of the proposed framework is examined by taking abnormal and normal patient temperature dataset and the findings are described using attractive figure representations. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Optimizing Forwarding Strategies in Sparsely Delay-Tolerant Networks with Short Contact Durations 15

Optimizing Forwarding Strategies in Sparsely Delay-Tolerant ...

引用

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

作者： Nemera, Yadesa Bedasa Jule, Leta Tesfaye Sivakumar, S. Pavithra, J. Sampathkumar, A. Rastogi, Ravi Dambi Dollo Univeristy Department of Information Technology Ethiopia Dambi Dollo University College of Natural and Computational Science Department of Physics Dambi Dollo Ethiopia Nehru Institute of Engineering and Technology Department of Cse Coimbatore India Dhanalakshmi Srinivasan College of Engineering Department of Artificial intelligence and data science Coimbatore India Dambi Dollo Univeristy Department of Computer Science Ethiopia Koneru Lakshmaiah Education Foundation Department of Cse AP Guntur India

ISBN: (纸本)9798350370249

Delay-tolerant networks (DTNs) are specific settings that experience either instability or the absence of a complete path between the source and destination nodes. The contact lifetime between pairs of network nodes is constrained by the mobility of nodes and the restricted bandwidth of peer- to-peer wireless transmission. In sparsely delay-tolerant networks, the re-establishment of contact between pairs of nodes is significantly delayed beyond the duration of the initial contact. Hence, the need for careful thought in designing a buffer control forwarding policy arises due to the limited contact period. Although forwarding algorithms have been designed extensively, much research has not been done on forwarding when there is a short contact time. When the message exchange between the pairs of network nodes is not completed during the contract period, they must wait until they are within communication range once more. To tackle the issue, we have suggested an innovative forwarding policy in buffer management that considers the duration of interaction. To assess the effectiveness of the proposed effort, we utilized the Opportunistic Network Environment (ONE) networking simulator. The suggested approach is combined with the MaxProp routing protocol buffer control forwarding policy and evaluated using two distinct metrics: bundle delivery rate and average delivery delay. In addition, we evaluated the performance of the suggested work by considering the number of nodes, buffer size, and simulation time. Across all the trials conducted in this thesis, the simulation results consistently demonstrate that our suggested method beats the existing forwarding strategy. © 2024 IEEE.

关键词： Buffer Management Forwarding Policy Contact Duration DTN Sparse DTN

来源：评论

学校读者我要写书评

暂无评论

A Voice Enabled Grammar Correction System using Transformers 3

A Voice Enabled Grammar Correction System using Transformers

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Jain, Prakhar Bahirat, Nishtha Yashwantrao Shibi, C.Sherin Babitha Lincy, R. Jency Rubia, J. Arunarani, A.R. SRM Institute of Science and Technology School of Computing Department of Computational Intelligence Tamil Nadu Chengalpattu Kattankulathur India Sri Eshwar College of Engineering Computer and Communication Engineering Department Tamil Nadu Coimbatore India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of ECE Tamil Nadu Avadi India

ISBN: (纸本)9798350372120

This paper introduces a groundbreaking real-time grammar error detection and correction system (named 'Error Ears') that adapts to linguistic interactions. At the core of the proposed approach lies the utilization of the potent 'T5' model, renowned for its capability to comprehend and produce human-like text. The proposed workflow meticulously covers essential stages including data pre-processing, model training, and fine-tuning. By fine-tuning the 'T5' model on a diverse dataset of sentences with numerous grammatical errors, the goal is to empower it to distinguish complex contextual nuances in speech. Preliminary results indicate that 'Error Ears' represents a substantial advancement over traditional correctional systems. This system excels at swiftly identifying and rectifying intricate spoken language errors, encompassing structural and contextual details. What sets it apart is its ability to provide real-time contextual suggestions, rendering it especially valuable during virtual meetings, presentations, and everyday conversations. 'Error Ears' is poised to redefine spoken language communication standards by enhancing clarity and precision. Its potential utility extends across a spectrum of contexts and linguistic environments, ensuring more efficient and accurate oral communication. In the digital age, this study opens up new avenues for a better comprehension and expression of language, resulting in more effective and transparent communication. © 2024 IEEE.

关键词： Data handling

来源：评论

学校读者我要写书评

暂无评论

An Effective Automated Framework for Oral Cancer Detection by Enhanced Convolutional Neural Networks 12

An Effective Automated Framework for Oral Cancer Detection b...

引用

12th IEEE International Conference on Advanced Computing, ICoAC 2023

作者： Santhiya, M. Sindhuja, M. Jegatha, R. Manikandan, J. Rajalakshmi Engineering College Thandalam Department of Computer Science and Engineering Chennai India Faculty of Engineering and Technology Srm Institute of Science and Technology Kattankulathur Department of Computational Intelligence Chennai India Sri Sai Ram Institute of Technology Department of Information Technology Chennai India St. Joseph's College of Engineering Omr Department of Information Technology Chennai India

ISBN: (纸本)9798350318210

Oral cancer, an aggressive form of cancer affecting the mouth and throat, has been on an alarming worldwide increase due to tobacco use and smoking. Oral cancer presents various challenges such as high incidence rates, delayed diagnosis, inadequate treatment plans and late prognoses and outcomes;early detection is crucial in improving prognosis outcomes and survival prospects. Machine learning techniques have gained prominence for improving cancer diagnosis while decreasing mortality and morbidity;in recent years they were used to detect oral cancer, providing highly accurate classification tasks yet limited capabilities in terms of feature extraction capabilities. To address these limitations, we are currently employing a deep-learning approach. To this end, we have devised an automated framework encompassing feature extraction, preprocessing and classification. Contrast-limited adaptive Histogram Equalization (CLACHE), used for effective pre-processing purposes to increase image contrast and resolution, is one form of pre-processing while Gray Level Cooccurrence Matrix extracts statistical texture-based features;finally, a Modified Convolutional Neural Net (MCNN) was employed for accurate classification of oral cancer cases. Utilizing Kaggle Repository dataset, we used it to assess the performance of our framework, while comparing it against other high-performance methods. Our proposed framework had an accuracy rating of 99.13% which surpasses current state-of-the art approaches. © 2023 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Two Surface Multipactor with Non-Sinusoidal RF Fields and Space Charge Effects 24

Two Surface Multipactor with Non-Sinusoidal RF Fields and Sp...

引用

24th International Vacuum Electronics Conference, IVEC 2023

作者： Iqbal, Asif Wen, De-Qi Verboncoeur, John Zhang, Peng Michigan State University Deparment of Electrical and Computer Engineering East LansingMI48823 United States Michigan State University Department of Computational Mathematics Science and Engineering East LansingMI48823 United States

ISBN: (纸本)9781665473217

We investigate two-surface multipactor induced by non-sinusoidal Gaussian-type RF fields by employing 3D electromagnetic Particle-in-cell (PIC) simulations using computer Simulation Technology (CST) Particle Studio. We analyze the effects of the RF amplitude and the full width at half maximum (and/or half minimum) (FWHM) on multipactor susceptibility and the time dependent physics. We find that with Gaussian-type RF operation, the threshold peak RF voltage as well as the threshold time averaged RF power per unit area for multipactor development increases compared to that with sinusoidal RF operation. Shrinkage of multipactor susceptibility bands is observed in the presence of space-charge effects. © 2023 IEEE.

关键词： Electric space charge

来源：评论

学校读者我要写书评

暂无评论

Hybrid CNN Classifier for Accurate Detection of Oral Cysts in Panoramic Dental Radiograph 9

Hybrid CNN Classifier for Accurate Detection of Oral Cysts i...

引用

9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Sivagami, S. Senthilvadivu, S. Geetha, P. Yukthavarshika, J. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computational Intelligence Kattankulathur Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai India

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377972

In dentistry, machine learning approaches play a significant role in the early detection and diagnosis of oral cysts. When planning accurate medical treatment, oral and maxillofacial surgeons can benefit from preoperative detection of these cysts. Surgical planning is directly affected by classifying oral cysts as dentigerous, radicular, ameloblastoma, odontogenic carcinoma, and odontogenic keratocyte. In dentistry, the outcomes of differential diagnosis based solely on imaging are unacceptable. This research proposes a three-step framework for autonomous cyst classification, segmentation, and detection based on a Convolutional Neural Network (CNN). To begin, DENT-CNN, a modified CNN architecture is proposed to classify the oral cyst as normal or abnormal. Second, UNet is a CNN variant used to segment the categorized cyst regions on panoramic dental images. Third, the Gray Level Co-occurrence Matrix (GLCM) is combined with CNN to identify segmented cysts as benign or malignant. The proposed work is extensively evaluated using 1500 real-time dental panoramic radiographic images of the oral cyst collected from a dental hospital. To alleviate overfitting, the data augmentation approach is used. The performance of the proposed work is analyzed in terms of a cyst classification rate of 96.8 %, a Dice Score of 96.3 % for cyst segmentation, and an accuracy for the Identification phase of 96.5%. © 2024 IEEE.

关键词： Dentistry

来源：评论

学校读者我要写书评

暂无评论

Survey on Artificial Intelligence- based Depression Detection using Clinical Interview Data 3

Survey on Artificial Intelligence- based Depression Detectio...

引用

3rd International Conference on Smart Electronics and Communication, ICOSEC 2022

作者： Begum, Shaik Rasheeda Sait, Saad Yunus Srm Institute of Science and Technology Department of Computer Science and Engineering Chengalpattu District Chennai India Srm Institute of Science and Technology Department of Computational Intelligence Chengalpattu District Chennai India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

Depression is a current and significant mental illness that most people face in their daily lives. Depression affects not just the emotional state of the person but also the physical, psychological and mental state of the individual. In contrast to other diseases, depression cannot be detected by laboratory tests, remains undetected due to a lack of understanding and ignorance, and can worsen, leading to suicide. Currently, the diagnostic procedure for detecting depression adopts face-to-face interactions and self-reported questionnaires by physicians. Recognizing depression necessitates a psychiatric analysis of human behavior and social interactions. People with depression behave differently than normal people, as can be seen in the patients' audio and video recordings. computer vision and machine learning have been used to detect depression to fight the disease at an earlier stage. This article introduces a survey of research on the identification of depression using clinical interview data through Unimodal and Multimodal approaches. © 2022 IEEE.

关键词： Diseases

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：