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检索条件"任意字段=International Applied Science and Precision Engineering Conference 2013, ASPEC 2013"

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1st international applied science and precision engineering conference 2013, aspec 2013

1st International Applied Science and Precision Engineering ...

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international applied science and precision engineering conference 2013, aspec 2013

ISBN: (纸本)9783037859476

The proceedings contain 228 papers. The special focus in this conference is on applied science and precision engineering. The topics include: Effects of grain size and lubricating conditions on micro forward and backward hollow extrusion of brass;direct heating billet within die during hot forging process;using soft material as die during hot forging;transparent conductive oxide GZO thin films by Sol-Gel process;photo-electronic properties of titanium dioxide nano thin films;step-stress accelerated degradation testing of NBR sealing ring;study the rheological property of gel abrasives in magnetic abrasive finishing;experiment on intermittent gas jet assisted modulated fiber laser drilling;temperature effect on mechanical properties of aluminum film;thermoelectric properties of transition metal deposited MWCNT buckypaper;a study on measurement of photoplethysmograph using a Smartphone camera;compound optical film using gray scale mask embedded with micro-voids;design of secondary optical element for a two-reflector solar concentrator;integrated multi-object Taguchi method with optical design for contact lenses;improvement on Zhang's camera calibration;video matching by one-dimensional PSNR profile;design of a magnetic gear set with low torque ripple;heat transfer of oscillating fluid through finned heat sink with top bypass clearance;reducing cogging force of a permanent magnet transverse flux linear synchronous motor;design and optimization on active engine mounting systems for vibration isolation;harmonic analysis and filter design for the light rail transit systems;modeling of a shape memory alloy beam and its stochastic chaos;parametric study of a micromixer with convergent-divergent sinusoidal walls;design and manufacturing of drug eluting depot stents with micro-sized drug reservoirs;finite-element analysis of the magnetic field in a magnetic gear mechanism;kinematic analysis of an 8-speed bicycle transmission hub;ground vibration characteristics for high-speed

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Smart Hybrid Mini-Xception Model and Eyebrow Displacement-Based Stress Level and Emotion Detection System 12th

Smart Hybrid Mini-Xception Model and Eyebrow Displacement-Ba...

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12th international conference on Recent Trends in Computing, ICRTC 2024

作者： Bhuvana, S. Anantha Prabha, P. Deva Priya, M. Christy Jeba Malar, A. Karthick, S. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Department of Computer Science and Engineering PSG Institute of Technology and Applied Research Tamilnadu Coimbatore India Department of Computer Science and Engineering Karpagam College of Engineering Tamilnadu Coimbatore India Department of Information Technology Sri Krishna College of Technology Tamilnadu Coimbatore India Department of Computer Science and Engineering Delhi - NCR Campus SRM Institute of Science and Technology Uttar Pradesh Ghaziabad India

ISBN: (纸本)9789819789450

Stress is a state of mental or emotional strain due to adversative or challenging situations. A human may undergo bad life experiences or events, and it is a significant issue to be dealt in today's society. It comes as a result of family situations, health concerns, work environments and people's behavior among other things. It affects people of various ages, including children, teenagers, middle-aged people and senior citizens. It has serious consequences affecting human body and life. These problems can be addressed by detecting mental stress at an early stage. The main goal of the propounded system is to identify human stress using a pre-trained Mini-Xception model. Additional measures such as eye moments, mouth activity and head motion are employed for determining the level of human stress. FER2013 dataset is used and the system is tested for all kinds of emotions. Human stress level is experimented by capturing video using webcam. From the experimental outcomes, it is evident that the proposed system offers better performance in terms of precision, Accuracy, Specificity and Sensitivity in contrast to traditional methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Eyebrow displacement FER2013 dataset Mini-Xception model Stress detection

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Low-cost contact-free screen control based on machine vision 4

Low-cost contact-free screen control based on machine vision

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4th Optics Frontier conference, OFS 2024

作者： Lin, Yangbing Wang, Teng Yan, Wei Peng, Xiao Zhang, Xinhai Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China College of Physics and Optoelectronic Engineering Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province Shenzhen University Shenzhen518060 China School of Computer Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9781510682269

Contact-free manipulation technology represents a novel approach that offers a fresh possibility for human-machine interaction, aiming to meet the evolving demands of this interface. In this paper, we introduce a contact-free planar display control technique based on imaging. In our research, we employ cameras as sensors and integrate infrared lasers with image processing techniques to detect and localize input signals. By establishing a coordinate mapping relationship between the operational plane and the display plane, we achieved contact-free control over the planar display. Our paper introduces two methods for establishing this coordinate mapping. The first involves constructing mapping functions between the rectified and transformed camera imagery and the display plane, thereby creating a point-to-point correspondence. The second method entails dividing both the camera imagery and the display plane into segments, establishing a one-to-one relationship between regions. We analyze the strengths and limitations of these two approaches. While the former boasts higher theoretical precision, it is more susceptible to equipment factors and exhibits slower response speeds. Conversely, the latter, despite its lower theoretical precision, offers faster response times. Through the setup of an experimental platform, we demonstrate the feasibility of our proposed. © 2024 SPIE.

关键词： Machine vision

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Enhancing Facial Emotion Recognition through Deep Learning and Image Pre-processing 3

Enhancing Facial Emotion Recognition through Deep Learning a...

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3rd international conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Singh, Ekta Nand, Parma Sharda University Department of Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798350303360

Humans frequently communicate effectively using their faces in addition to their words. The use of computer vision techniques to categorize face emotion has been extensively studied. Given the difficulties and restrictions of databases, such as the use of static data or facial capture in artificial contexts, these have had different degrees of success. As a result, we think that novel preprocessing methods are necessary to increase the precision of facial expression detection models. In this study, we suggest a novel, yet straightforward, approach to improving the precision of face emotion identification. Our research was done using the FER2013 dataset, which includes static facial photos of 7 basic emotions. Resizing and Normalization image preprocessing techniques were applied on the dataset prior to the splitting into train and test sets. The training images were split into train and test sets in the ratios of 75% and 25% respectively. The facial expressions in the photos were classified using Convolution Neural Networks [CNNs], with an accuracy of 76.75% on the test set. © 2023 IEEE.

关键词： Emotion Recognition

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Enhancing Facial Expression Recognition with a Directional Attentive Neural Network 3

Enhancing Facial Expression Recognition with a Directional A...

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3rd IEEE World conference on applied Intelligence and Computing, AIC 2024

作者： Singh, Jagendra Shelke, Nitin Arvind Masson, Palak Agrawal, Rishi Sharma, Amit Parashar, Amit Bennett University School of Computer Science Engineering & Technology Greater Noida India Raj Kumar Goel Institute of Technology Greater Noida India Gla University Department of Computer Engineering & Applications Mathura India Lovely Professional University School of Computer Application Phagwara India Pranveer Singh Institute of Technology Basic Science & Humanities-Chemistry Kanpur India

ISBN: (纸本)9798350384598

The proposed DANN was developed for better recognition of facial expression. The proposed DANN combines the attention and directional filters, which filter out features that focus on the informative facial regions while capturing the directional patterns in the facial queue. The average accuracy after benchmarking all the 10 experiment trials was in the very high level with the proposed DANN on datasets combining CK+, FER2013, and RAF-DB, with an average accuracy of 88.04%. The model showed a good trade-off between precision and recall: its average weighted F1 score was 0.881, while the average precision and recall were 0.883. This implies that the model will maximize the identification of true positive samples while, at the same time, minimizing that of false positives and false negatives. All these results are indicative of the robustness and reliability of the DANN architecture in classifying the facial expressions correctly across the different datasets and different experimental settings. The results suggest the high potential of DANN in furthering the state-of-the-art facial expression recognition with prosperous affective computing, human-computer interaction, and psychology. © 2024 IEEE.

关键词： Affective computing Attention mechanisms Deep learning Directional Attentive Neural Network Facial expression recognition

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Fraud Detection in Credit Card Transactional Data using Hybrid Machine Learning Algorithm 6

Fraud Detection in Credit Card Transactional Data using Hybr...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Dharma, Bhukya Latha, D. Department of Computer Science and Engineering Adikavi Nannaya University A.P Rajamahendravaram India

ISBN: (纸本)9798331522667

Now-a-days credit cards have grown significantly because of quick development of e-commerce and online banking. This leads to many fraud transactions. Normally, credit card frauds occur mainly when the card is lost at an unauthorized purpose or any fraudsters attempt to utilize card as well as the person using card for his/her online payment transparency. This credit card fraud detection can be solved by using Machine Learning (ML)techniques, when required data is gathered and available. This analysis presents hybrid ML approach for fraud detection in credit card transactions. The dataset used in this analysis is collected 284,807 transactions in September 2013 from European cardholders. For developing hybrid model ML techniques like Support Vector Machine (SVM) and Logistic Regression (LR) are used. The results of Hybrid ML methods are depended on Accuracy, precision, Recall, and F1-score. Results states that, described model achieves high performance parameters Accuracy, precision, Recall and F1-Score of 97%,96%,97%,97% respectively than other models. © 2025 IEEE.

关键词： Logistic regression

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Facial Emotion Detection using CNN & VGG16 Model 9

Facial Emotion Detection using CNN & VGG16 Model

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9th IEEE international conference for Convergence in Technology, I2CT 2024

作者： Negi, Aryan Singh Arora, Anamika Bisht, Sourav Devliyal, Swati Kumar, Bura Vijay Kaur, Gurjot Graphic Era Hill University Computer Science And Engineering Uttarakhand Dehradun India Graphic Era Deemed To Be University Computer Science And Engineering Uttarakhand Dehradun India Sr University School of Computer Science & Artificial Intelligence Warangal India Chitkara University Institute of Engineering And Technology Chitkara University Punjab India

ISBN: (纸本)9798350394474

In fields like human-computer interaction, healthcare, and marketing, facial and emotional recognition utilizing machine learning (ML) has found many uses. The primary method used in this study is Convolutional Neural Networks (CNNs), more especially pre-trained models like ResNet and VGG16 that have been tweaked using labelled facial expression datasets. Enhancement techniques are used to enhance model generalization, and data preparation, ensemble learning, and transfer learning are used to address issues like posture variations and cultural expressions. In tests conducted on the benchmark datasets CK+ and FER-2013, competition-level performance is displayed in parameters such as accuracy, precision, recall, and F1-score. The application of this ML-based methodology in emotion-aware systems, human-computer interaction, and mental health monitoring is highlighted by these *** present work underscores the potential of machine learning (ML) in detecting facial expressions and emotions. Further research is necessary to improve the functionality of these systems in order to achieve greater social advantages. © 2024 IEEE.

关键词： Face recognition

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DeepEmoNet: An Efficient Deep Emotional Neural Network for Facial Expression Recognition 3

DeepEmoNet: An Efficient Deep Emotional Neural Network for F...

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3rd international conference on applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Likhitha, Dulla Sistla, Venkatrama Phani Kumar Vfstr University Department of Computer Science and Engineering Vadlamudi India

ISBN: (纸本)9798350375190

Recognizing human emotions is essential for successful interaction. This research focuses on applying deep learning techniques to identify emotions through facial expressions. Facial expressions reveal a lot about how individuals feel, making them extremely important for communication. The research focuses on developing a system that can look at facial photos and reliably determine the emotions being expressed. The primary objective was to distinguish between various emotions employing a deep learning approach. An accuracy level of approximately 88% was successfully attained by leveraging convolutional neural networks (CNNs). To conduct the analysis, the FER 2013 database was utilized, which contains grayscale images depicting facial expressions, each with dimensions of 48× 48 pixels. © 2024 IEEE.

关键词： Emotion Recognition

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Determination of Main Parameters of Air Floating Support System for Liquid Crystal Glass Substrate and Its Influence on Micro-Vibration of Glass Substrate 6th

Determination of Main Parameters of Air Floating Support Sys...

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6th international conference on Mechanical engineering and applied Composite Materials, MEACM 2023

作者： Wang, Xuejian Ma, Yunjie Xu, Zhi Huang, Bin Yang, Yongyue Anhui Province Key Laboratory of Measuring Theory and Precision Instrument School of Instrument Science and Optoelectronics Engineering Hefei University of Technology Anhui Hefei230009 China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Hefei230009 China

ISBN: (纸本)9789819716777

The physical model of air floating support is established, and calculation formulas of air supply pressure, air film thickness and throttle hole diameter are derived from the formula. The maximum amplitude of the vibration of the glass substrate is measured under the condition of constant air film thickness and constant diameter of the throttle hole, respectively, and the influence law of the main parameters of the air floating system on the maximum amplitude of the micro-vibration of the glass substrate is obtained. On this basis, the main parameters of an engineering prototype air floating system were designed as follows: air film thickness 50 μm, air supply pressure 220 Pa, throttle hole diameter 0.25 mm, and the prototype air floating support system was developed. The test results of the developed prototype of the air floating show that the maximum amplitude of the glass substrate is 0.31 μm, which is less than the design requirement of 1 μm. The experimental results show that the air floating support prototype meets the design index requirements. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Liquid crystals

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Fraud & Anomaly Detection: Using Fine-tuned OCSVM Algorithm and visualization of the enhanced results using Machine Learning Techniques 3

Fraud & Anomaly Detection: Using Fine-tuned OCSVM Algorithm ...

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3rd international conference for Innovation in Technology, INOCON 2024

作者： Garg, Kaushiv Gill, Kanwarpartap Singh Aggarwal, Priyanshi Rawat, Ramesh Singh Banerjee, Deepak Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science & Engineering Uttarakhand Dehradun248002 India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350381931

Diversion from traditional methods of fraud detection by tackling the issue of insufficient class labels in corporate data is very essential. In contrast, the use of the One-Class Support Vector Machine (OCSVM) method is employed for the purpose of unsupervised anomaly detection. This study investigates a dataset including credit card transactions conducted by cardholders from Europe during the month of September in the year 2013. The data indicates a significant discrepancy, with just 0.172% (492 out of 284,807) of the transactions being classified as fraudulent. The dataset used in this research comprises numerical variables that have undergone pre-processing by Principal Component Analysis (PCA). Nevertheless, due to confidentiality concerns, the initial attributes of the dataset have not been revealed or accessed, with the exception of two variables: 'Time', denoting the duration of each transaction in seconds, and 'Amount', indicating the monetary amount associated with each transaction. In precision when there is a lack of class labels, the 'Class' property is used to distinguish between fraudulent transactions and legitimate transactions. Given the significant disparity in the allocation of these categories, it is deemed suitable to use the Area Under the precision-Recall Curve (AUPRC) as a metric for assessing accuracy. This study presents a new approach to anomaly detection that addresses the issue of data balance and utilises the One-Class Support Vector Machine (OCSVM) technology. This study focuses on the difficulties related to the management of datasets that exhibit significant imbalances in the context of fraud detection. Specifically, it addresses the obstacles that arise when class labels are not readily available. © 2024 IEEE.

关键词： Anomaly detection

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