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Machine Learning Approaches to Facial Recognition: A Survey 人脸识别的机器学习方法:综述
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049964
Raegan Faith F. Paguirigan, Mikelene Beron B. Camero, Mark Angerlo Equias, Mideth B. Abisado, G. Sampedro
{"title":"Machine Learning Approaches to Facial Recognition: A Survey","authors":"Raegan Faith F. Paguirigan, Mikelene Beron B. Camero, Mark Angerlo Equias, Mideth B. Abisado, G. Sampedro","doi":"10.1109/ICEIC57457.2023.10049964","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049964","url":null,"abstract":"Due to the rapid development of technology, face recognition has received much attention recently. The face continues to be the most challenging study topic for experts in computer vision and image processing since it has unique characteristics that must be recognized as an entity. This survey explores the most challenging face aspects, including position change, age, lighting, and occlusion. They are considered essential elements in facial recognition systems when used with facial images. The current state of face detection methods and techniques is also examined in this paper. These methods and techniques include Eigenface, Artificial Neural Network (ANN), Support Vector Machine (SVM), Principal Component Analysis (PCA), Independent Component Analysis (ICA), Gabor Wavelets, 3D morphable models, and Hidden Markov Model (HMM). However, the goal of this study is to give a comprehensive assessment of the literature on face recognition and its applications. After a thorough discussion, the most important findings are presented.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124669602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automatic Conversation Turn-Taking Segmentation in Semantic Facet 语义面会话自动分词
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049858
Dongin Jung, Yoon-Sik Cho
{"title":"Automatic Conversation Turn-Taking Segmentation in Semantic Facet","authors":"Dongin Jung, Yoon-Sik Cho","doi":"10.1109/ICEIC57457.2023.10049858","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049858","url":null,"abstract":"Turn-taking is a significant aspect of a smooth conversation system. Detecting end-of-turn can be difficult for automatic conversation systems, and this can cause misleading conversation systems. To make a conversational system recognizing turn transition points, we propose a token-level turn-taking segmentation using linguistic features. This task imitates the automatic speech recognition environment by organizing several settings. Moreover, we utilize GPT-2, which is well known as a pretrained generative language model, to be able to predict in token-level live text stream. We evaluate our model compared to RNN series models in general conversation datasets and explore model prediction with test sample scenarios.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124707884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Material map generation using hyper-spectral NIR images 使用高光谱近红外图像生成材料贴图
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049950
Dong-Keun Han, Jeonghyo Ha, Jong-Ok Kim
{"title":"Material map generation using hyper-spectral NIR images","authors":"Dong-Keun Han, Jeonghyo Ha, Jong-Ok Kim","doi":"10.1109/ICEIC57457.2023.10049950","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049950","url":null,"abstract":"The hyper-spectral curve on the near-infrared (NIR) bands commonly exhibits distinct characteristics for each surface material. NIR information can be a useful clue to identify the surface material of an object. In this paper, the surface material of each local patch is first classified by a deep network from NIR hyper-spectral images, and then, those classification results are collected to obtain the surface material map of an entire scene. To train the classification network, we built a hyper-spectral dataset which includes 5 different materials. Experimental results show that we can get a quite effective material map.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129538968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Efficient NPU-Aware Filter Pruning in Convolutional Neural Network 卷积神经网络中一种有效的npu感知滤波剪枝
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049954
Soyoung Lee, Kyungho Kim, Jonghoon Kwak, Eunchong Lee, Sang-Seol Lee
{"title":"An Efficient NPU-Aware Filter Pruning in Convolutional Neural Network","authors":"Soyoung Lee, Kyungho Kim, Jonghoon Kwak, Eunchong Lee, Sang-Seol Lee","doi":"10.1109/ICEIC57457.2023.10049954","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049954","url":null,"abstract":"The neural processing unit (NPU)is a high-performance and low-power acceleration specialized in implementing artificial intelligence (AI) such as training and inference. The NPU needs a compressed network because it is used with low power and low latency to process the convolutional neural network (CNN). Therefore, in this paper, we propose an efficient NPU-aware filter pruning method for CNN to increase the efficiency of NPU. NPU-aware filter pruning is performed in multiples of the channel unit size, which is the operation unit of the NPU to reduce unnecessary computation and save memory storage space. In the experimental results with VGGNet-16 and ResNet-18 on the CIFAR10 dataset, the proposed method reduced hardware inefficient space and unnecessary computation by 1.86~6.78% compared to general pruning method without loss of accuracy.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126955824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Machine Learning-based Signal-to-Noise Ratio Estimation using Amplitude Frequency Vector 基于机器学习的幅频矢量信噪比估计
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049849
June-Young Ahn, Hano Wang
{"title":"Machine Learning-based Signal-to-Noise Ratio Estimation using Amplitude Frequency Vector","authors":"June-Young Ahn, Hano Wang","doi":"10.1109/ICEIC57457.2023.10049849","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049849","url":null,"abstract":"In this paper, we propose a new SNR estimator using a machine learning model (MLSE) that has trained the amplitude pattern of data symbols. In order for the neural network to estimate the SNR, the received data symbols are converted into a kind of histogram, an amplitude frequency vector (AFV), depending on the amplitude value. The machine learning model is trained to match the pattern of the AFV to the SNR, and as a result, the MLSE can estimate the SNR with a very high accuracy of mean squared error (MSE) below 0.01 even in very low SNR region. Unlike conventional SNR estimation techniques that utilize additional information including pilot signals, the proposed SNR estimator uses only data symbols, so there is no signaling overhead. In addition, since it uses a machine learning model, its computational complexity is very low.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126378292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reflectance-based Code Optimization for Motion Deblurring 基于反射率的运动去模糊代码优化
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049961
Jaelin Lee, B. Jeon
{"title":"Reflectance-based Code Optimization for Motion Deblurring","authors":"Jaelin Lee, B. Jeon","doi":"10.1109/ICEIC57457.2023.10049961","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049961","url":null,"abstract":"We propose a method for determining a code set based on the reflectance of the scene in the coded exposure photography technique using multiple color LEDs with same power. Coded exposure imaging affects image brightness, which affects motion deblurring performance. Thus, the performance of the motion deblurring depends on the duty cycle of the code. Previously, since the image was modulated with a single code, the duty cycle of the code considered only the overall brightness of the scene. The coded imaging with multiple color LEDs can consider the brightness of each color channel, allowing the code set to be further optimized based on the reflectance of each color in the scene. We demonstrated the effectiveness of our method by comparing it with conventional methods and confirmed that the average PSNR increases by 2.2dB.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115294876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Query Similarity of Various Linguistic Levels for Hybridized Conversational Agents 混合会话代理不同语言层次的查询相似度
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049903
So-Eon Kim, Choong-Seon Hong, Seong-Bae Park
{"title":"Query Similarity of Various Linguistic Levels for Hybridized Conversational Agents","authors":"So-Eon Kim, Choong-Seon Hong, Seong-Bae Park","doi":"10.1109/ICEIC57457.2023.10049903","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049903","url":null,"abstract":"The performance of retrieval-based conversational agents is affected by the discrepancy between a user query and a retrieved query similar to the user query. There have been a number of previous studies to cope with this discrepancy, and a skeleton-based response generation is one of the successful approaches. However, it shows some ineffectiveness in that it considers only the lexical similarity in finding a similar query from a database of query-response pairs. Therefore, this paper proposes a CNN-based model which uses the combination of the neural representation of two queries and manually-designed lexico-syntactic features to determine the similarity between the queries. According to the experimental results on a manually-constructed dataset, the proposed model outperforms legacy search engine in finding similar queries from the database, which proves the plausibility of the proposed model.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121700312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DWT+DWT: Deep Learning Domain Generalization Techniques Using Discrete Wavelet Transform with Deep Whitening Transform DWT+DWT:使用离散小波变换和深度白化变换的深度学习领域泛化技术
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049902
Jin Shin, Hyun Kim
{"title":"DWT+DWT: Deep Learning Domain Generalization Techniques Using Discrete Wavelet Transform with Deep Whitening Transform","authors":"Jin Shin, Hyun Kim","doi":"10.1109/ICEIC57457.2023.10049902","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049902","url":null,"abstract":"Recently, there is a growing demand for a deep learning framework with robust generalization performance in real-world domains, such as an autonomous driving environment. The existing domain generalization methodologies for convolutional neural networks have been designed to actively utilize the feature map with the generative model or normalization techniques to distinguish domain-specific information. However, augmented images are essential for measuring style sensitivity. This study shows that style information can be extracted from an original image through color space separation and frequency decomposition without a separate augmented image. Therefore, it can be used as a method independent of existing network models. The proposed method shows an mIoU improvement by 1.54% compared to the existing method in the semantic segmentation model trained using urban scene datasets.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"112 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113981756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
High-Level AMBA Monitoring Platform for SoC Architecture Exploration 用于探索 SoC 架构的高级 AMBA 监控平台
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049893
Jaeyun Lim, Yujin Jeon, Eun-Gyeong Ham, Ji-Hoon Kim
{"title":"High-Level AMBA Monitoring Platform for SoC Architecture Exploration","authors":"Jaeyun Lim, Yujin Jeon, Eun-Gyeong Ham, Ji-Hoon Kim","doi":"10.1109/ICEIC57457.2023.10049893","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049893","url":null,"abstract":"As a System on Chip (SoC) hardware complexity grows dramatically, it becomes more difficult to find the optimal SoC architecture with various hardware IPs. Accordingly, SoC architecture exploration should be performed before the chip-level implementation where various types of on-chip interconnect topology are compared according to the on-chip traffic patterns from a number of hardware IPs in terms of area, transaction latency, power consumption, etc. In this paper, we propose a high-level AMBA (Advanced Microcontroller Bus Architecture) Monitoring Platform where various traffic statistics can be obtained with C++ modeling using open-source Verilator. For the evaluation, we built the baseline SoC platform with Arm Cortex-M4F CPU core and various hardware IPs. With the proposed high-level AMBA monitoring platform, the high-level C++ modeling of on-chip traffic analysis allows to find optimal AMBA on-chip interconnects in the early stages with fast analysis time based on the on-chip traffic analysis.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128081244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Dual-Mode Waveguide Cavity Filters and Diplexer With Fractional Bandwidths Around 0.2% 分数带宽约为0.2%的双模波导腔滤波器和双工器
2023 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2023-02-05 DOI: 10.1109/ICEIC57457.2023.10049947
Jong-Hyuk Lee, S. Jeong, Boyoung Lee, Myeong‐Gil Lee, Juseop Lee
{"title":"Dual-Mode Waveguide Cavity Filters and Diplexer With Fractional Bandwidths Around 0.2%","authors":"Jong-Hyuk Lee, S. Jeong, Boyoung Lee, Myeong‐Gil Lee, Juseop Lee","doi":"10.1109/ICEIC57457.2023.10049947","DOIUrl":"https://doi.org/10.1109/ICEIC57457.2023.10049947","url":null,"abstract":"This work presents the design of a low-loss narrowband waveguide diplexer for S-band satellite communication links. The design of ultra-narrowband (Δ around 0.2%) filters will be discussed as well as their applications to diplexer design. The fabricated diplexer exhibits a low-loss performance (max 1.3 dB and 1.8 dB insertion loss in each channel), and it is suited for channelizing narrow-band signals transmitted from geostationary satellites.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128099990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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