2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)最新文献_第7页

Monitoring Maritime Traffic with Ship Detection via YOLOv4 通过YOLOv4监测船舶探测海上交通

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760632

Gaurav Verma, Aditya Gupta, Shobhit Bansal, Himanshu Dhiman

引用次数: 1

A Low Energy Consuming MAC Protocol for Wireless Sensor Networks 一种低能耗的无线传感器网络MAC协议

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760530

Ramesh Babu Pedditi, Kumar Debasis

引用次数: 1

ANN based approach to predict criminal trends in Bangladesh 基于神经网络的方法预测孟加拉国的犯罪趋势

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760684

Faisal Farhan, Thahmidul Islam Nafi

{"title":"ANN based approach to predict criminal trends in Bangladesh","authors":"Faisal Farhan, Thahmidul Islam Nafi","doi":"10.1109/AISP53593.2022.9760684","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760684","url":null,"abstract":"Crime trend analysis has become a mandatory task as the scale of crime is increasing rapidly all over the globe. In recent years, Bangladesh has encountered various types of crimes and the rate is increasing with its increased population. Both physical and digital based crimes have become very common and their fatality can disrupt the advancement of any country. To tackle the situation, it is important to investigate and forecast the crime patterns that can assist the law enforcement agencies for easier investigation. Machine Learning and Deep Learning based crime analysis has become very popular as they can accurately and efficiently analyze large criminal dataset. In this study, the authors implemented machine learning techniques as well as ANN architecture to assess and forecast crime trends in Bangladesh. The dataset in this experiment was collected from the Bangladesh Police website that consists of criminal records of various crimes during the years 2010 to 2019. Authors evaluated the performance of ANN with other regression models named linear Regression and Support Vector Regression for crime prediction. The proposed model(ANN) outperforms other two models in this study compared to all the performance evaluation metrics. Hence ANN model is suggested by the authors to forecast and analyze future crime trends.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"8 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79831263","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

A data-driven approach to predict the risk of readmission among patients with Diabetes Mellitus 预测糖尿病患者再入院风险的数据驱动方法

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760601

Sachin Parajuli, Sanjaya Parajuli, Manoj Kumar Guragai

引用次数: 0

Power and Area Efficient Multi-operand Binary Tree Adder 功率和面积高效的多操作二叉树加法器

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760615

Ankam Anirudh, U. Nanda, Milan Biswal

引用次数: 0

A Review on Raspberry Pi and its Robotic Applications 树莓派及其机器人应用综述

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760590

Sudha Ellison Mathe, Ashok Chakravarthy Pamarthy, Hari Kishan Kondaveeti, Suseela Vappangi

引用次数: 5

Accent Classification of Native and Non-Native Children using Harmonic Pitch 母语儿童与非母语儿童使用和声音高的口音分类

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760588

Kodali Radha, Mohan Bansal, Shaik Mulla Shabber

{"title":"Accent Classification of Native and Non-Native Children using Harmonic Pitch","authors":"Kodali Radha, Mohan Bansal, Shaik Mulla Shabber","doi":"10.1109/AISP53593.2022.9760588","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760588","url":null,"abstract":"To combat the Covid-19 outbreak, the education system shifted away from the classroom to distinct e-learning on digital platforms, which made effective use of voice-based recognition systems, especially for preliterate children. Children’s speech recognition systems face multiple challenges owing to their immature vocal tracts, and they demand more intelligence due to the fact that children with diverse accents utter words differently. Accent refers to a unique style of pronouncing a language, particularly one associated with a specific nation, place, or socio-economic background. This paper aims to extract reliable acoustic and prosodic speech cues of accent for classification of native and non-native preschool children using harmonic pitch estimation along with Mel Frequency Cepstral Coefficients (MFCCs) to train the k-Nearest Neighbour (k-NN) classifier. The experimental results reveal that the proposed robust model outperforms various feature extractors in accent classification of native and non-native children in terms of accuracy & F-Measure and more discriminate against noisy environments.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"23 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82833919","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: 10

InDiP: Intelligent Digital Painter for Low Resolution Face Inpainting InDiP:智能数字画家低分辨率的面部绘画

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760668

Naveen Cheggoju, K. Madhavi, Mallela Jayadeep

{"title":"InDiP: Intelligent Digital Painter for Low Resolution Face Inpainting","authors":"Naveen Cheggoju, K. Madhavi, Mallela Jayadeep","doi":"10.1109/AISP53593.2022.9760668","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760668","url":null,"abstract":"In the recent years Artificial Intelligence (AI) has become a go to approach to solve any kind of real-world problems. In these pandemic times, there are many issues arising around the world. One of such issues is the identification of a masked person. It has become difficult to even recognize the very well-known persons due to masks, which has made the field of surveillance suffer a lot. The Object of this research is to solve this issue by reconstructing the face behind the mask using deep learning models. We are proposing a network called as Intelligent Design Painter (InDiP) with capabilities of reconstructing the face behind the mask at low resolutions. This would make the recognition of the masked persons easier. To achieve this target initially work has been done on reconstructing the general human images for fine tuning. After fine tuning the algorithm it has applied on masked faces to obtain the desired results. When checked the accuracy with the original image, the results seem satisfactory. In this approach a sequence Transformer is trained to forecast pixels based on data from a succession of 2D inputs without taking into consideration any of the 2D input structure. Even though the GPT-2 scale model has been trained on low-resolution ImageNet datasets without labels, the network is able to perform satisfactorily. So by using this model ONE can deduce the facial images of the masked people.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"2014 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87934793","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

Wireless Biometric Lock Using Arduino with the IoT 使用Arduino与物联网的无线生物识别锁

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760583

G. Ganesh, Annaadi Nithish Reddy, Annadi Sai Siddu Vardhan Reddy, N.V.Punith Chowdary

引用次数: 2

A review on optimization techniques of battery charging in electric vehicles 电动汽车电池充电优化技术综述

2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP) Pub Date : 2022-02-12 DOI: 10.1109/AISP53593.2022.9760545

Muniprakash T, V. K, P. Naik, R. Varma, R. Supraja, Rahul Vijay Lingadhal

引用次数: 1