2023 4th International Conference on Signal Processing and Communication (ICSPC)最新文献_第3页

Design of GPS Antenna for Vehicular Application 车载GPS天线的设计

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10125699

A. Abhiram, Sunkesula Hasan Basha, Sakthi Abirami Balakrishnan, Devi Sowjanya P

引用次数: 0

Slotted Hexagonal Ultrawideband Microstrip Antenna (SHUMA) for Telemetry Applications 遥测用开槽六角超宽带微带天线(SHUMA)

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10125623

Melbin Elsa Cheriyan, R. Krishnan, Ramu R, Glintu Joy, Abina Ann Mathew, Shefin Shaji

引用次数: 0

Analysis of Gall Bladder & Kidney Stone Using Spectroscopic Technique: A Review 用光谱技术分析胆囊结石和肾结石的研究进展

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10125670

Abhyanand Kumar, Lokesh Phagna, Sagar Rawat, Neha Gupta

引用次数: 0

Machine Learning Based Fuzzy Logic Approach for Auto Harmonization of Melodies in C Major 基于机器学习模糊逻辑的C大调旋律自动和声方法

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10125905

Abraham George, X. Mary, Pochiraju Udaya Sai Venkatesh, Gurram Aakash, Bhupathiraju S S M Karthikeya Varma, Kocherlakota Snigdha

{"title":"Machine Learning Based Fuzzy Logic Approach for Auto Harmonization of Melodies in C Major","authors":"Abraham George, X. Mary, Pochiraju Udaya Sai Venkatesh, Gurram Aakash, Bhupathiraju S S M Karthikeya Varma, Kocherlakota Snigdha","doi":"10.1109/ICSPC57692.2023.10125905","DOIUrl":"https://doi.org/10.1109/ICSPC57692.2023.10125905","url":null,"abstract":"Melody harmonization has been a matter of interest for musicians over the past centuries. Numerous efforts have been made in harmonically arranging music both manually and automatically. As harmonization is evolved from chord progressions, sincere efforts have been made to emulate Bach’s compositional methods to create impressive chord patterns using algorithmic approaches. Different artificial intelligence techniques involving supervised learning have also been subsequently applied. In this paper, we propose a fuzzy logic approach for automatically harmonizing melodies in C major scale. The model is built on the basis of data gathered from musical corpora over the ages. The melody is harmonized utilizing a fuzzy reasoning-based automated harmonization technique. Through the fuzzy reasoning applied, typical chord progressions resembling legendary manual compositions are obtained. We have used basic chords avoiding complex textures so that the tonality of the music is retained. The performance of the system is evaluated comprehensively. The system shows competency on comparative analysis with manual harmonization done by musicians on the same melody.","PeriodicalId":109624,"journal":{"name":"2023 4th International Conference on Signal Processing and Communication (ICSPC)","volume":"450 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116407862","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

Anxiety and Fear based Safety detector using kNN Classification Algorithm 基于kNN分类算法的焦虑和恐惧安全检测器

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10125620

M. Karthiga, V. G. Priyaa, A. Sagayaraj, J. Vinu, R. Rupesh, R C Karthik

引用次数: 0

Design and Parametric Analysis of Quad band Metamaterial Absorber 四波段超材料吸收体的设计与参数分析

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10125702

Jeena Viji, Titto Anujan

引用次数: 0

Exploring Solutions for Text-to-Speech Synthesis of Low-Resource Languages 探索低资源语言的文本-语音合成解决方案

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10125834

A. R. Gladston, K. Pradeep

{"title":"Exploring Solutions for Text-to-Speech Synthesis of Low-Resource Languages","authors":"A. R. Gladston, K. Pradeep","doi":"10.1109/ICSPC57692.2023.10125834","DOIUrl":"https://doi.org/10.1109/ICSPC57692.2023.10125834","url":null,"abstract":"A text-to-speech synthesis system is expected to convert any given text to highly intelligible and natural speech that sounds as human-like as possible. It finds its place in a variety of applications, like virtual assistants, speech-assistive aids, and speech-to-speech translation systems. In recent years several deep learning-based methods have been proposed for text-to-speech synthesis, which result in synthetic speech that is intelligible and very natural. However, these methods require a large amount of speech data, in the order of tens of hours, preferably recorded from a single speaker and in a quiet/studio environment. While such a large amount of data might be easily available for certain languages, like English, which are widely spoken and used globally, this is not the case with several other languages. In this regard, the current work explores state-of-the-art text-to-speech synthesis methods and strategies for handling low-resource languages. The paper ultimately aims to provide insight into developing text-to-speech systems for Indian languages and hence reviews the work done so far on Indian languages as well. Since India is a multilingual country where several languages co-exist, a multilingual synthesizer would be preferable. Further, one recurring suggestion to handle data scarcity is to make use of data from multiple languages too. Therefore, the current work focuses on exploring multilingual text-to-speech synthesis for low-resource languages.","PeriodicalId":109624,"journal":{"name":"2023 4th International Conference on Signal Processing and Communication (ICSPC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133193848","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 Algorithms for Crop Yield Prediction in Real-Time Scenarios 实时作物产量预测的机器学习算法

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10126011

N. V. S. Krishna, Pokala Neeraj, B. Surya, B. Prudhvi, V. Deepthi

引用次数: 0

Automatic Disease Classification of Paddy Leaf Images Using Deep Learning Algorithms 基于深度学习算法的水稻叶片图像疾病自动分类

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10125872

Durgadevi Velusamy, A. Mounika, D. Ragulraj, K. Vigneshwaran

{"title":"Automatic Disease Classification of Paddy Leaf Images Using Deep Learning Algorithms","authors":"Durgadevi Velusamy, A. Mounika, D. Ragulraj, K. Vigneshwaran","doi":"10.1109/ICSPC57692.2023.10125872","DOIUrl":"https://doi.org/10.1109/ICSPC57692.2023.10125872","url":null,"abstract":"Agriculture is considered one of the primary sectors in India. Especially rice is the primary stable food widely cultivated and consumed by 50% of the Indian population. Paddy crop is susceptible to several diseases like other crops that indirectly affect agricultural development and economic loss. To address this limitation, in this study, we have applied deep learning algorithms for the recognition and classification of diseases at an earlier stage. The paddy plant disease diagnosis is made by applying image processing techniques to identify the changes in leaves and its texture. We have used pre-processing techniques for segmentation, feature extraction and classification of disease. First, we have to perform data augmentation to improve the number of images in the dataset. Second, the segmentation of plant leaves are performed to identify the test infected region. Then, we applied CNN algorithm to extract features from the data. After feature extraction, we trained different classification algorithms to recognize and classify the images into disease and non-disease images. The application of machine learning and deep learning algorithms helps in the precise location and identification of infectious leaves that help farmers to use automated methods for disease diagnosis.","PeriodicalId":109624,"journal":{"name":"2023 4th International Conference on Signal Processing and Communication (ICSPC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114581212","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

VLSI Implementation of Median Filter for Noise Removal in EMG Signal 肌电信号去噪中值滤波的VLSI实现

2023 4th International Conference on Signal Processing and Communication (ICSPC) Pub Date : 2023-03-23 DOI: 10.1109/ICSPC57692.2023.10125903

D. Malathi, Philip Naveen, V. Sahasra, S. Rithika

{"title":"VLSI Implementation of Median Filter for Noise Removal in EMG Signal","authors":"D. Malathi, Philip Naveen, V. Sahasra, S. Rithika","doi":"10.1109/ICSPC57692.2023.10125903","DOIUrl":"https://doi.org/10.1109/ICSPC57692.2023.10125903","url":null,"abstract":"The most important requirement in processing real world signals is using less computational time and energy efficient processing to minimizing the noise in the signals. The Electromyography (EMG) signal is a type of physiological signal produced by muscles when they are contracting. EMG data are frequently required to assist diagnose or rule out a variety of diseases, including Muscle diseases like muscular dystrophy and polymyositis. However, EMG signals are easily affected by environmental noise like inherent noise in electronics equipment, motion artifact, inherent instability of signal. This noise should be eliminated to obtain accurate results from the diagnosis. The existing architecture utilizes a sorting method to sort the input samples either in increasing or decreasing order and determine the median value it needs a lot of comparators. Meanwhile the dynamic power consumption and computational time is high. A novel median filter design based on a ID filter using a low-power design is proposed. At the end of each machine cycle, it produces a median output after receiving an input sample through a two-stage pipelined filter. The circuit’s power utilization is decreased by reducing the signal transitions. The gating method is used to decrease dynamic power usage. The outcome result of the proposed architecture showed that it has lower power utilization of S6 mW in S-bit sample width, while the current method has 19SmW power consumption. It shows that the power consumption of proposed architecture is reduced by 56.56% while comparing with the existing method.","PeriodicalId":109624,"journal":{"name":"2023 4th International Conference on Signal Processing and Communication (ICSPC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131767730","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