2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)最新文献_第5页

A Review on Charge Control Techniques for Batteries in Electric Vehicles 电动汽车电池充电控制技术研究进展

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9808007

Jeny Sophia S, K. R, S. P., Nandini G. Iyer, A. M, Nivethitha S B

引用次数: 2

High Frequency Response Pulse Processing Front-end for the Radiation Detector 辐射探测器高频响应脉冲处理前端

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807851

V. Neha, Balaram Mohanty, Abhishek Basu, Mohammed Salah Shaikh, Sridhar Bonda, I. Mirza

引用次数: 0

Channel prior based Retinex model for underwater image enhancement 基于信道先验的水下图像增强Retinex模型

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807919

Sathvik Srinivas, V. R. Siddharth, Surya Dutta, Nikhil S. Khare, Lavanya Krishna

{"title":"Channel prior based Retinex model for underwater image enhancement","authors":"Sathvik Srinivas, V. R. Siddharth, Surya Dutta, Nikhil S. Khare, Lavanya Krishna","doi":"10.1109/ICAECT54875.2022.9807919","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807919","url":null,"abstract":"Since light undergoes absorption and scattering when it travels in water, images taken under water fall prey to color distortion, fuzziness/haziness, underexposure, and color cast. To alleviate these issues, this paper proposes a novel Retinex-based enhancing approach aimed at enhancing low-quality under-water images. Firstly, the input image undergoes pre-processing, where a color correction technique is employed to address the problem of color distortion. This is followed by conversion of the input image from the Red, Green and Blue color space to the Lab color space. Then, by means of the multi scale Retinex, the illumination component of the image is procured. Image dehazing algorithms, i.e., bright channel prior and underwater dark channel prior algorithms are applied individually on the procured illumination component. The image gets enhanced and is then converted back to the Red, Green and Blue color space from the Lab color space. The final enhanced image is obtained by performing histogram equalization on the enhanced Red, Green and Blue image. This is intended to make the output color intensity more realistic. The efficacy of the algorithms are gauged by means of some image quality metrics. Compared to pre-existing techniques, the method proposed manages to effectively enhance images while keeping detail loss to a minimum.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133489710","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: 2

Cultivating Tulip at Extent by Using Machine Learning in Context to Bangladesh 在孟加拉国使用机器学习在一定程度上培育郁金香

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807948

Md Riad Hasan, Abir Abdullha, Md. Forhad Hossain, A. Sattar

引用次数: 0

Importance of Initialization in K-Means Clustering 初始化在k均值聚类中的重要性

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807996

Anubhav Gupta, Antriksh Tomer, S. Dahiya

引用次数: 0

Reduction of Gaussian noise from Computed Tomography Images using Optimized Bilateral Filter by Enhanced Grasshopper Algorithm 基于增强Grasshopper算法的优化双边滤波器对ct图像高斯噪声的降噪

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9808017

Devanand Bhonsle, Jaspal Bagga, S K Mishra, Chandrahas Sahu, Varsha Sahu, Ashutosh Mishra

引用次数: 0

Video Captioning based on Image Captioning as Subsidiary Content 基于图像字幕作为辅助内容的视频字幕

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807935

J. Vaishnavi, V. Narmatha

{"title":"Video Captioning based on Image Captioning as Subsidiary Content","authors":"J. Vaishnavi, V. Narmatha","doi":"10.1109/ICAECT54875.2022.9807935","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807935","url":null,"abstract":"Video captioning is the more heuristic task of the combination of computer vision and Natural language processing while researchers are concentrated more in video related tasks. Dense video captioning is still considering the more challenging task as it needs to consider every event occurs in the video and provide optimal captions separately for all the events presents in the video with high diversity. Captioning process with less corpus leads to less performance. To avoid such issues, our proposed model constructed with the option of generating captions with high diversity. Image captions are taken as subsidiary content to enlarge the diversity for captioning the videos. Attention mechanism is utilized for the generation process. Generator and three different discriminators are utilized to contribute an appropriate caption which enriches the captioning process. ActivityNet caption dataset is used to demonstrate the proposed model. Microsoft coco image dataset is considered as subsidiary content for captioning. The benchmark metrics BLEU and METEOR are used to estimate the performance of the proposed model.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124994815","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: 2

Research on wind power Prediction based on BP neural Network 基于BP神经网络的风电功率预测研究

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807962

D. Hu, Zhaoyun Zhang, Hao Zhou

引用次数: 2

A Unified and Semantic Model Approach for Histopathologic Cancer Detection Based on Deep Double Transfer Learning 基于深度双迁移学习的组织病理学肿瘤检测统一语义模型方法

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807873

U. R, S. B., S. G

{"title":"A Unified and Semantic Model Approach for Histopathologic Cancer Detection Based on Deep Double Transfer Learning","authors":"U. R, S. B., S. G","doi":"10.1109/ICAECT54875.2022.9807873","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807873","url":null,"abstract":"Accurately predicting the risk of cancer recurrence and metastasis is very important for individual cancer treatment. Currently, doctors usually use a histological grade that pathologists determine by performing a semi-quantitative analysis of the three histopathological and cytological features of hematoxylin-eosin (HE) stained histopathological images. Evaluate the prognosis and treatment options of patients with breast cancer. In order to efficiently and objectively fully utilize the valuable information underlying HE-stained histopathological images, this work has potential as a feature for constructing a classification model of cancer prognosis. So, a calculation method is proposed to extract morphological information. Breast cancer is not a single disease, but it is composed of many different biological entities with different pathological features and clinical significance. With the advent of personalized medicine, pathologists are facing a significant increase in the workload and complexity of digital pathology in cancer diagnosis, and diagnostic protocols need to focus on equal efficiency and accuracy. Computer-aided image processing techniques have been shown to be able to improve the efficiency, accuracy, and consistency of histopathological assessments and provide decision support to ensure diagnostic consistency. First, a method for segmenting tumor lesions based on a pixel-by-pixel deep learning classifier is proposed and a method for segmenting cell nuclei based on marker-driven watersheds. It then subdivides all image objects and extracts a rich set of predefined quantitative morphological object feature. Then a classification model based on these measurements is used to predict disease-free survival in binary patients. Finally, the predictive model is tested in two independent cohorts of breast cancer patients.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122096922","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: 1

Single Server Queueing Model with Multiple Working Vacation and with Breakdown 具有多个工作假期和故障的单服务器排队模型

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807852

M. Seenivasan, S. Chandiraleka

引用次数: 0