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检索条件"任意字段=2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022"

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Application of Convolution Neural Network for Cloud Shadows Removal in Landsat Imagery

Application of Convolution Neural Network for Cloud Shadows ...

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2022 ieee international conference on current development in engineering and technology, ccet 2022

作者： Gupta, Ruchika Kumar, Sandeep Gupta, Anish Abes Business School Ghaziabad India Sharda School of Engineering and Technology Department of Cse U.P. Greater Noida India Zonal Head North - It Academics INurture Eduaction Solution Pvt. Ltd. Bengaluru India

ISBN: (纸本)9781665454155

In this article deep CNN is being used for the removal of noise caused by clouds and its shadow. CNN does the detection and denoising of the clouds and its shadow very accurately. In the proposed system, Deep CNN Algorithm is used for cloud and its shadow detection. CNN helps in better image processing and sematic segmentation. Python libraries have been used to create a CNN, then the Landsat images will be passed as input and will categorize each pixel of the image into 3 categories. After training the model, it is be feeded with new Landsat images to check whether it gives correct result or not. The input is provided to the CNN model in the form of Landsat images. The output is segmented into 3 categories: cloud, dark cloud shadow, and light cloud shadow. Image is considered as a 2d array. Values between 0 to 1 or 0 to 255 based on how it is processed are filled. To do so, a portion of the mirror image is added to boundaries, where some existing data is taken from the 2d array right to left and extra boundaries of 6x6 are filled. Fourier transformation is applied on that array to transform as per their requirements. Using the Deep CNN algorithm, we will be able to combine the whole input image to get multilevel features. Deep CNN does better image processing and semantic segmentation. © 2022 ieee.

关键词： Landsat

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Clustering-Based Under-Sampling with Normalization in Class-Imbalanced Data

Clustering-Based Under-Sampling with Normalization in Class-...

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2022 ieee international conference on current development in engineering and technology, ccet 2022

作者： Akash, Abdul Hady Mahi, Fabiha Faiz Mondal, Tanmoy Rahman, Md. Naimur Ishrak, Ibne Farhan Rahman, Mohammad Azizur Arnob, Shad Alvee, Sajan Mahamud University of Asia Pacific Department of Computer Science and Engineering Dhaka Bangladesh Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh North South University Department of Electrical and Computer Engineering Dhaka Bangladesh

ISBN: (纸本)9781665454155

In some real-world data sets, there is a class imbalance where one class (the minority class) has a limited number of data points and the other class (the dominant class) has a large number of data points. With the state-of-the-art machine learning approaches, it is extremely challenging to build an efficient model without taking data preparation into account to balance the unbalanced data sets. To ensure that each class has the same number of data points, random under-sampling has been used in numerous research. During the data preparation phase of this study, this research experiments with under-sampling techniques that use a clustering technique. This Research uses under-sampling techniques with normalization in this non-interest-bearing imbalanced data collection with a majority and minority class. Both majority and minority classifications contain personal information focuses. This Research first uses k-fold cross-validation to separate this unbalanced data set into preparation and testing sets. This Research separates the data into a majority course subset and a minority course subset after normalizing it. The majority of lesson information evaluations are minimized by using a clustering-based under-sampling method. The minority lesson subset is then combined with the reduced lion's share course subset to create an updated preparation set. Then The author normalizes the information once more at that moment. The classifier is then independently prepared and evaluated using the updated preparation and testing sets. © 2022 ieee.

关键词： Classification (of information)

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Smart Electronic Arm Module using Arduino Applications

Smart Electronic Arm Module using Arduino Applications

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2022 ieee international conference on current development in engineering and technology, ccet 2022

作者： Kanna, R. Kishore Hema, L.K. Ramya, V. Subha Kripa, N. Gomalavalli, R. Ambikapathy, A. Vels Institute of Science Technology Advanced Studies Department of Biomedical Engineering Chennai India Department of Biomedical Engineering Chennai India Bharath Institute of Higher Education and Research Department of Biomedical Engineering Chennai India Siddharth Institute of Engineering and Technology Department of Electronics and Communication Engineering Andhra Pradesh India Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9781665454155

Automation is often employed in today's society to assist people in doing their jobs and improve work efficiency. One kind of automation device that is often employed to assist humans in doing their jobs is the robot. Robots play a variety of functions in human life and are used to make a variety of human tasks easier. Robots are often used because they can make tasks simpler and more productively do them. Robots are used in many different ways to assist people in their work, including drones, welding robots, and agricultural robots. One sort of robot that we come across often is a robot arm, which performs duties comparable to those of a human arm. The robot may be controlled in its application utilizing a variety of techniques, some of which directly use a cable connection and others which utilize a wireless technique. Additionally, a controller-the robot's brain-is required to operate a robot. In order to operate the robot arm via Bluetooth, this research will create a controller based on Arduino, one of the most popular microcontroller boards for use in education, hobbies, and the workplace. The identification of the programme and data collection from various sources, such as a journal or discussion forum, are the first steps in the methodology used in this study. Next, the systems schematic design of the hardware used in this research is done, and then the Arduino programme and smartphone app are added. The select and place activity may be carried out wirelessly utilizing a Bluetooth connection by the Arduino software and the simple Android applications created using App Inventor. © 2022 ieee.

关键词： Agricultural robots

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Software Requirement Ambiguity Avoidance Framework (SRAAF) for Selecting Suitable Requirement Elicitation Techniques for Software Projects

Software Requirement Ambiguity Avoidance Framework (SRAAF) f...

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2022 ieee international conference on current development in engineering and technology, ccet 2022

作者： Gupta, Ashok Kumar Siddiqui, Shams Tabrez Qidwai, Khalid Ali Haider, Agha Salman Khan, Haneef Ahmad, Md Oqail Universiti Malaysia Terengganu Faculty of Science and Technology Kuala Terengganu Malaysia Jazan University Department of Computer Science Jazan Saudi Arabia Jazan University Department of Computer and Network Engineering Jazan Saudi Arabia B.S Abdur Rahman Crescent Institute of Science and Technology Department of Computer Application Tamil Nadu India

ISBN: (纸本)9781665454155

Ambiguity is an intrinsic deficiency of natural language written requirement documents. Requirement Engineers face difficulties while communicating with stakeholders from different backgrounds and knowledge to extract requirements. The selection of a suitable requirement elicitation technique plays a critical role to improve the quality of elicited requirements. Differences among elicitation techniques are very large;it implies that some techniques may perform better than others for a particular situation. Generally, requirement engineers select elicitation techniques based on their interests, knowledge, and experience. The selection of the right technique is critical as all techniques can not fit into different situations. In addition, before starting the new project, there is no software available that can help in selecting suitable elicitation techniques based on the situation. This paper proposed a software-based selection of suitable elicitation techniques used in SRAAF (Software Requirement Ambiguity Avoidance Framework). The tool focuses on the first phase of SRAAF, specifically the situational parameter based selection of effective elicitation techniques. These situational parameters are mapped onto the knowledge base for the selection process. The tool takes situational parameters as input related to three categories: project, requirement engineer, and stakeholders. The tool suggests a technique based on situational parameters under the current settings. If any new evidence related to situational parameters, elicitation technique or contextual value is originated, these values or information can be easily included in the tool. © 2022 ieee.

关键词： Engineers

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Sentimental Analysis of Movie Review using Machine Learning Approach

Sentimental Analysis of Movie Review using Machine Learning ...

引用

2022 ieee international conference on current development in engineering and technology, ccet 2022

作者： Zumma, Md.Thoufiq Tahmiduzzaman, K.B.M. Khan, Raihan Roni, Nashed Shah Rahat-Bin-Rafique, A.A.M. Akash, Abdul Hady Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665454155

A key area of machine learning called sentiment analysis seeks to extract subjective data from textual evaluations. The most popular technique for anticipating user ratings is sentiment analysis, and several machine-learning techniques have been employed to provide precise predictions. Sentiment analysis is the skill of examining information regarding what the general public really thinks about your company, a text, an opinion, a social media post, etc. It is a very potent tool in the analytics toolbox. Natural language processing and text mining both have a close connection to the study of sentiment. It can be used to evaluate the reviewer's viewpoint on certain topics or the review's overall polarity. The accuracy of the model is evaluated using sentiment analysis on the IMDB movie reviews dataset utilizing machine learning (ML) and natural language processing (NLP) techniques. Natural language processing and machine learning combine to provide the fundamental building blocks of sentiment analysis. Provides context to grasp the meaning of any text by enhancing the capabilities of machine learning and natural language processing. Using machine learning classification methods, this study suggests a prediction model for the sentiment analysis of movie reviews. This study aids researchers in choosing the most effective method for doing accurate and timely emotive analysis on IMDB movie reviews. Here, want to estimate the general polarity of the review using machine learning and natural language processing (NLP). © 2022 ieee.

关键词： Sentiment analysis

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Human Computer Interface Application for Emotion Detection Using Facial Recognition

Human Computer Interface Application for Emotion Detection U...

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2022 ieee international conference on current development in engineering and technology, ccet 2022

作者： Kanna, R. Kishore Surendhar, Prasath Alias Rubi, Jaya Jyothi, G. Ambikapathy, A. Vasuki, R. Department of Biomedical Engineering Chennai India Department of Biomedical Engineering Chennai India B.V. Raju Institute of Technology Department of Pharmaceutical Engineering Andhra Pradesh India Galgotias College of Engineering and Technology Department of Electrical & Electronics Engineering Uttar Pradesh India Bharath Institute of Science and Technology Department of Biomedical Engineering Chennai India

ISBN: (纸本)9781665454155

An essential tool for describing human emotion is facial expression. From morning tonight, people go through a broad spectrum of emotions that may be caused by their mental or physical health. The six major facial expressions of happy, sorrow, surprise, fear, disgust, and rage are now classified by psychology as six universal emotions, despite the fact that humans experience a broad variety of emotions. Facial muscle movements may be used to determine humane motions. The brow, lips, nose, and eyes are the four primary facial characteristics Facial recognition is a topic that is now the focus of much investigation. Finding a match between the input image and the images to red in the database is the aim of face recognition. Human- computer interaction and the solution to the problem of criminal identification depend on facial recognition. The data in face recognition tasks has a high intrinsic complexity, making the dimensionality reduction strategy essential. Picture space's dimensionality is decreased using PCA. In the domains of computer vision, image processing, pattern recognition and other areas, the modelling of the face using Gabor features has generated a lot of attention. The major justification for using the Gabor filter is its biological significance. Mammal primary visual cortex neurons have an accessible field profile that is oriented toward spatial frequency features. Additionally, Gabor filters may make advantage of well-known visual properties as spatial localization, orientation selectivity and spatial frequency feature. So, we are proposing this computational model approach for the detection of emotional changes using dataset from EMOTIC database by recognition system. In this approach we achieved around 88% accuracy which efficient and better when it's been compared with computer modeling Methodologies. © 2022 ieee.

关键词： Gabor filters

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Automated Defective ECG Signal Detection using MATLAB Applications

Automated Defective ECG Signal Detection using MATLAB Applic...

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2022 ieee international conference on current development in engineering and technology, ccet 2022

作者： Kanna, R. Kishore Ansari, Aftab Ahmed Kripa, N. Jyothi, G. Mutheeswaran, U. Hema, L.K. Department of Biomedical Engineering Chennai India Universität Medizinische Mannheim Heidelberg University Medizinische Fakultät Mannheim Mannheim Germany Bharath Institute of Higher Education and Research Department of Biomedical Engineering Chennai India B.V. Raju Institute of Technology Department of Pharmaceutical Engineering Andra Pradesh India

ISBN: (纸本)9781665454155

The examination of cardiac illness uses electrocardiograms (ECGs or EKGs), which are electrical recordings of the heart. This heart's electrical activity causes line drawings to appear on paper. A series of waves is the name for the peaks and valleys in the line tracings. There are six distinct waveforms in this sequence of waves, which may be identified as cardiac waves (P, Q, R, S, and T). The majority of older techniques for analyzing ECG signals to find PQRST used DSP techniques like wavelet transform and fast Fourier transform, as well as artificial neural networks. While the electrocardiogram (ECG) signal's P, Q, R, S, and T values are detected using a straightforward and reliable approach in this study, the Holter monitor is crucial in the long-term monitoring of serious heart abnormalities in cardiac monitoring. Once the recording has been made, it must be examined to identify any waveform anomalies that might indicate the presence of arrhythmias or other abnormalities in the heart. In order to avoid potential harm during crucial hours, the time needed for a medical professional to review the waveforms must be extended. The efficiency of detecting and monitoring arrhythmias is increased by bio signal processing in MATLAB applications. using MATLAB to identify cardiac waves by applying a simple mathematical procedure to get cardiac wave values and display these values on the ECG waves simultaneously. In place of clinical diagnosis, this programme will be focused on scientific research. In this method, baseline correction, denoising, and arrhythmia identification come after parameter extraction. Future research on irregular waveform recognition may be applied to various bio signal applications, such as EEG, EOG, ERG, and EMG monitoring, to enhance the efficiency of analyzing aberrations in irregular waveforms. © 2022 ieee.

关键词： Electrocardiograms

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Design of Data Processing Software for Raindrop Spectrometer Based on LabVIEW 5

Design of Data Processing Software for Raindrop Spectrometer...

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5th ieee international conference on Computer and Communication engineering technology, ccet 2022

作者： Yefeng, Xu Ruili, Jiao Minsong, Huang Beijing Information Science and Technology University School of Information and Communication Engineering Beijing China Key Laboratory of Cloud-Precipitation Physics and Severe Storms Institute of Atmospheric Physics Cas Beijing China

ISBN: (数字)9781665467353

ISBN: (纸本)9781665467353

This paper studies design of data processing software for raindrop spectrometer. It includes reading, decompression, data processing, storage and display. The difficulties are data decompression and the software architecture design. This software applies digital image processing technology to process the raindrop data measured by dual-line raindrop spectrometer data processing software (DRDPS) based on LabVIEW, realizes the display from data file to particle image, stores the obtained information and geometric parameters of precipitation particles, and the obtained meteorological information of precipitation intensity, precipitation particle shape, precipitation type and precipitation particle spectrum is displayed in the front panel of the software. The test results show that the software meets the system requirements completely and can be applied to the research of cloud precipitation and other atmospheric science relevant fields. © 2022 ieee.

关键词： Software testing

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Multi-modal Graph Attention Network for Video Recommendation 5

Multi-modal Graph Attention Network for Video Recommendation

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5th ieee international conference on Computer and Communication engineering technology, ccet 2022

作者： Liu, Huizhi Li, Chen Tian, Lihua Xi'an Jiaotong University School of Software Engineering Xi'an China

ISBN: (数字)9781665467353

ISBN: (纸本)9781665467353

In view of the problems of cold start and data interaction in recommendation systems, and most current recommendation algorithms ignore the diversity of data types, the combination of multimodal data and knowledge graph is bound to improve the pertinence of video recommendation. In this paper, we propose Multi-modal Knowledge Graph Attention Network (MMKGV) model, and all the entity nodes of the knowledge graph are innovatively introduced into multimodal information. The high-order recursive node information dissemination and information aggregation are carried out on the multimodal knowledge graph through the graph attention network. In the model, the triplet function of the knowledge graph is used to construct the triplet inference relationship, and the vector representation generated by the final aggregation is used for recommendation. Through extensive experiments on two public datasets TikTok and Kwai, the results show that the MMKGV can effectively improve the effect of video recommendation compared with other comparison algorithms. © 2022 ieee.

关键词： Recommender systems

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Hierarchical Feature Fusion and Multi-scale Cost Aggregation for Stereo Matching 5

Hierarchical Feature Fusion and Multi-scale Cost Aggregation...

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5th ieee international conference on Computer and Communication engineering technology, ccet 2022

作者： Zhang, Jiaquan Li, Pengfei Wang, Xinan Zhao, Yong Shenzhen Graduate School of Peking University School of Information Engineering China

ISBN: (数字)9781665467353

ISBN: (纸本)9781665467353

To further improve the accuracy of disparity estimation in ill-posed regions and weak texture regions, in this paper we propose HFMANet: which is a stereo matching method based on hierarchical feature fusion and multi-scale cost aggregation. Specifically, we first propose a hierarchical feature fusion module, which innovatively fuses low-level features and high-level features to obtain rich semantic information while retaining the edge information of the image. Secondly, we propose a multi-scale cost aggregation module to extract rich global context information. At the same time, the layer-by-layer fusion optimization helps increase the receptive field to capture more structural information, reduce the dependence on local information, and help the disparity estimation of ill-posed regions and weak-textured regions. Comprehensive experiments are conducted on the SceneFlow and KITTI datasets, and achieve competitive results, which proves the effectiveness of the proposed method. © 2022 ieee.

关键词： Textures

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