2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)最新文献

{"title":"Audio Compensation Network: to Improve the Quality of Low-Energy Audio in Visual Sound Separation","authors":"Yining Gao, Pengyuan Zhang, Zejia Tian","doi":"10.1109/ICCECE51280.2021.9342383","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342383","url":null,"abstract":"Separating the single audio from the mixed audio has always been a task that researchers are trying to achieve. In visual audio, visual information can be used as an aid to audio separation, helping us to separate audio better. However, under the current method, the independent sound separated from the mixed video has the phenomenon that high energy audio causes serious interference to the low energy audio. We call it \"over-complete separation\" and \"incomplete separation\", which seriously affects our separation. This paper proposes a new separation network, which can compensate for the loss of low-energy audio in the separation process, improve the signal-to-noise ratio and loudness of low-energy audio, and achieve better results than state-of-the-art methods on our dataset.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116368774","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}

{"title":"Application of Convexified Convolutional Neural Network in Text Classification","authors":"Yuanchong Bian, Chang Liu, Bincheng Wang, Owen Xingjian Zhang","doi":"10.1109/ICCECE51280.2021.9342409","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342409","url":null,"abstract":"This paper introduces a type of convexified convolutional neural network (CCNN), introduced by Zhang, Liang and Wainwright. We applied this model on the classification of text-based online shopping reviews. This work makes an estimate on the error term brought by the low rank approximation. We also build our codes on the work done by Schaik. We make adjustments on the choices of kernel functions and further extend the application of the algorithm to multilayer CCNNs. The results show that Zhang’s model is practical on learning shallow CCNNs. However, there is no big improvement in multilayer CCNN. Analysis of likely causes are mentioned by the end of this section. Strengths, weaknesses as well as future work are discussed in the end.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121481332","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}

{"title":"Research and Application on the Improved SSD Chip Defect Inspection Algorithm","authors":"L. Zhi, Zhou Bo","doi":"10.1109/ICCECE51280.2021.9342114","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342114","url":null,"abstract":"Defect inspection is an important part of the light-emitting diode (LED) production process. In the production environment, most of the defects to be inspected are small targets below 32×32 pixels, which cannot be detected by current SSD algorithm effectively. Based on the concept of DSSD (Deconvolutional Single Shot Detector) algorithm, an improved SSD (Single Shot Detector) chip defect inspection method is proposed to accurately inspect LED chips surface defects. First, the original algorithm’s basic network VGGNet is replaced by ResNet, and the first pooling layer is removed; then a prediction module and a deconvolution module are added to fuse the semantic information between the high-level and low-level; finally, model hidden layer is pruned, and the last convolution layer and deconvolution module are removed. The experimental results show that compared with the original SSD algorithm, which enhances the accuracy of chip defect inspection.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121847417","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}

{"title":"Optimization of Bandgap Reference with High PSRR on Deep Submicron","authors":"S. Jun","doi":"10.1109/ICCECE51280.2021.9342379","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342379","url":null,"abstract":"In this paper, optimization of a bandgap reference (BGR) with high power supply reject ration (PSRR) is presented. Voltage reference is an important core modulation in analog integrated circuit (IC), digital-analog hybrid IC and purely digital IC, such as analog-to-digital converter (ADC), digital-to-analog converter (DAC) and power management with high precision voltage or current reference, and is widely used in power managements, wireless environmental sensors and medical electronics. The folded current mirror is used to reduce the reference voltage fluctuation, and the op amp voltage feedback is used to stabilize the voltage fluctuation and MOS capacitor noise reduction. The proposed bandgap reference is based on op amp and optimized in circuit structure, layout & routing and device parameters. The optimized bandgap reference is implemented in a 180nm process, whose reference voltage generated is 1.25018V, the Temperature Coefficient (TC) is 126ppm $/^{circ}mathrm{C}$ in the temperature range of $- 25^{circ}mathrm{C}$ to $85^{circ}mathrm{C}$, and the PSRR is 89.5dB at low frequencies. And the active area occupies $261 times 161 mu m^{2}$.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132134086","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}

{"title":"CT Radio Genomics of Non-Small Cell Lung Cancer Using Machine and Deep Learning","authors":"Yi-yun Song","doi":"10.1109/ICCECE51280.2021.9342170","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342170","url":null,"abstract":"Non-small cell lung cancer is the most common type of lung cancer, and the most common genetic markers for it are mutation of the epidermal growth factor receptor gene (EGFR) and the Kirsten rat sarcoma (KRAS) gene. The objective of this paper was to predict the EGFR and KRAS mutation status, given CT features, by using machine learning models. Features extracted from 144 CT scans of the tumor area included statistical, shape, pathological, and deep learning features. The ResNet-34 neural network was used to extract deep learning features. All features were fed into machine learning models (random forest, logistic regression, support vector machine) and evaluated with 10-fold cross validation, confusion matrices, and the area under the ROC curves. P-values were calculated through t-testing and Mann-Whitley rank-sum testing, proving a significant statistical difference between mutated and non mutated genes. Between predicting EGFR and KRAS mutations, all machine learning models performed better in predicting EGFR mutations. In predicting EGFR mutation, the logistic regression (AUC =0.85) and support vector machine (AUC =0.84) machine learning models performed best. In predicting KRAS mutations, the machine learning models performed sub-optimally, with the best performance from the support vector machine (AUC =0.73). By calculating permutation feature importance, it can be seen that the inclusion of deep learning features aided in the machine learning models’ performance.Overall, machine learning algorithms, if optimized and provided with more data, could prove useful in predicting EGFR and KRAS mutation status in NSCLC patients, saving time and money.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132233885","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}

{"title":"An Improved Detection Method of Human Target at Sea Based on Yolov3","authors":"Dongjin Li, Liuchuan Yu, Wang Jin, Rufei Zhang, Jiang Feng, Niu Fu","doi":"10.1109/ICCECE51280.2021.9342056","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342056","url":null,"abstract":"In the mission of searching and rescuing, it is often faced with the situation that the area to be searched is large and the target to be searched is small. Combined with the object detection technology, this paper proposes a method for searching drowning people. At first, we make a dataset, which contains a large number of human targets at sea. Then, we improve the Yolov3 algorithm: In the feature extraction network, we use the residual module with channel attention mechanism. In the feature fusion network, we add a bottom-up structure to the FPN structure. Moreover, in terms of loss function, we use the CIoU loss function. Finally, on the settings of the anchor box, we use a linear transformation method to deal with the anchor boxes generated by clustering algorithm. The detection accuracy of the improved algorithm for human targets at sea is 72.17%, which has a good detection effect.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134523159","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}

{"title":"Design of a Nonlinear Wireless Power Transfer System with Wide Range of Excitation Voltage","authors":"Meng Wang, Litao Ren","doi":"10.1109/ICCECE51280.2021.9342295","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342295","url":null,"abstract":"Magnetic coupling wireless power transfer (MC-WPT) has great potential in various applications such as the charging of electric productions or biomedical implants. The MC-WPT system based on nonlinear resonance has been proved to be a promising technique due to its robustness to the variation of resonant frequency. By utilizing a nonlinear component, it has been found that high power transfer efficiency can be maintained even when the frequency deviates from the original resonant frequency. The MC-WPT system is generally operated in periodic sinusoidal state. In this work, the characteristic of a nonlinear MC-WPT system is analyzed when the equivalent excitation voltage changes. The result shows that the system varies from periodic state to chaotic state with the increase of excitation voltage and operates in periodic sinusoidal state merely in a small range. In the periodic non-sinusoidal state, a filter is introduced and designed which ensure the normal operation of the nonlinear MC-WPT system in a wide range of excitation voltage.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131702313","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}

{"title":"An optimized Algorithm for Power and Beacon Control in VANETs Based On DDPG","authors":"Guoyan Yang, Ming Bai","doi":"10.1109/ICCECE51280.2021.9342048","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342048","url":null,"abstract":"The energy efficiency of in-vehicle communication terminals is critical to LTE-V2V-based in-vehicle collaborative sensing applications and other connected vehicle applications, and is the main goal of LTE-V communication system design and optimization. This paper proposed a joint optimization algorithm for power control and broadcast beacon frequency based on the LTE-V2V communication protocol. Through the simulation of different traffic flow states, the proposed algorithm is fully simulated. The results show that the method proposed in this paper can effectively deal with the dynamic randomness of the environment, and compared with several other advanced algorithms, getting higher energy efficiency.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130981998","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}

{"title":"DenseFuseNet: Improve 3D Semantic Segmentation in the Context of Autonomous Driving with Dense Correspondence","authors":"Yulun Wu","doi":"10.1109/ICCECE51280.2021.9342077","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342077","url":null,"abstract":"With the development of deep convolutional networks, autonomous driving has been reforming human social activities in the recent decade. The core issue of autonomous driving is how to integrate the multi-modal perception system effectively, that is, using sensors such as lidar, RGB camera, and radar to identify general objects in traffic scenes. Extensive investigation shows that lidar and cameras are the two most powerful sensors widely used by autonomous driving companies such as Tesla and Waymo, which indeed revealed that how to integrate them effectively is bound to be one of the core issues in the field of autonomous driving in the future. Obviously, these two kinds of sensors have their inherent advantages and disadvantages. Based on the previous research works, we are motivated to fuse lidars and RGB cameras together to build a more robust perception system. It is not easy to design a model with two different domains from scratch, and a large number of previous works (e.g., FuseSeg [10]) has sufficiently proved that merging the RGB camera and lidar models can attain better results on vision tasks than the lidar model alone. However, it cannot adequately handle the inherent correspondence between the RGB camera and lidar data but rather arbitrarily interpolates between them, which quickly leads to severe distortion, heavy computational burden, and diminishing performance.To address these problems, in this paper, we proposed a general framework to establish a connection between lidar and RGB camera sensors, matching and fusing the features of the lidar and RGB models. We also defined two kinds of inaccuracies (missing pixels and covered points) in spherical projection and conducted a numerical analysis on them. Furthermore, we proposed an efficient filling algorithm to remedy the impact of missing pixels. Finally, we proposed a 3D semantic segmentation model, DenseFuseNet, which incorporated our techniques and achieved a noticeable 5.8 and 14.2 improvement in mIoU and accuracy on top of vanilla SqueezeSeg [24]. All code is already open-source on https://github.com/IDl0T/DenseFuseNet.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132870753","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}

{"title":"UAV Path Planning based on Improved Whale optimization Algorithm","authors":"Kun Liu, Cheng Xv, Daqing Huang, Xinning Ye","doi":"10.1109/ICCECE51280.2021.9342329","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342329","url":null,"abstract":"In order to solve the problem of path planning for Unmanned Aerial Vehicle (UAV) in complex battlefield environment, an improved whale optimization algorithm (IWOA) is proposed in this paper. The algorithm is improved by adding adaptive weights. Then, the linear convergence factor of the algorithm is modified into a nonlinear convergence factor, which is beneficial to balance the global searching ability and local development ability. The simulation results show that the IWOA algorithm has better convergence than the other three algorithms.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133592652","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}