Conference Presentations by Appalabatla Shanmukha Priya Sreenidhi
2023 3rd Asian Conference on Innovation in Technology (ASIANCON), IEEE, 2023
Image Denoising is one of the current day challenges in the field of image processing. Noise in t... more Image Denoising is one of the current day challenges in the field of image processing. Noise in the image is the existence of artifacts that do not start from the original picture content. Autoencoders have made considerable progress in image denoising because of their ability to reconstruct image inputs. Autoencoders for denoising images usually accepts a degraded image as input and is trained to predict the reconstructed image as its output. An effort has been made to analyse the functioning of selected autoencoders for image denoising, such as Basic Autoencoder, Denoising Autoencoder and Convolutional Denoising Autoencoder using the Modified National Institute of Standards and Technology database (MNIST) dataset. The performance of these models is evaluated and compared using Structural Similarity Index Measure, Peak Signal to Noise Ratio evaluation metrics. The strengths and weaknesses of each autoencoder are discussed and the factors that influence their performance are explored. Qualitative and quantitative analysis of the dataset provides an insight of effectiveness and efficiency of each autoencoder in denoising images. Observations show that Convolutional Denoising Autoencoder out-performs other autoencoders in terms of the evaluation metrics and better reconstructed image. This study can act as a base for researchers and practitioners to identify suitable autoencoders for denoising images in real-life applications.
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2023 World Conference on Communication & Computing (WCONF), IEEE, 2023
Reading habit opens up the door to succeed in learning. It is the soul of education. It is theref... more Reading habit opens up the door to succeed in learning. It is the soul of education. It is therefore essential to explore the reading habits of professional students to access their interest in reading in turn their personality, communication skills. The practice of reading does not mirror the lifestyle of most undergraduates in Academics and Universities. It is assumed that quite handful of professional students are aware of how to read, what to read, when to read and where to read. Basically, reading for refreshment or relieving stress is quite common among the educated population.The study is a concise survey on “Reading Habits of Professional Students.” Data is collected using a validated online questionnaire. It is analysed using Pandas – a Python library for analysis and manipulation of data. Further matplotlib – a popular python package for data visualisation is used to showcase the results in the form of plots and graphs. Interpretations are drawn based on the varied responses from the respondents. The findings disclosed that nearly all the respondents understand the importance of reading. The study revealed that 91.95% love to read from their various fields while 8.05% showed their unwillingness towards book reading. 43.34% of the student population likes reading fiction books, whereas only 1.24% of professional students go with non-fictional books besides 55.42% showed interest to read both. It is observed that reading habit among professional students pursuing their engineering stream is encouraging. It is recommended that students should develop and show curiosity towards book reading. Parents should function as catalysts encouraging their children by supplementing them with needed reading resources besides creating a conducive atmosphere for them.
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Papers by Appalabatla Shanmukha Priya Sreenidhi
2023 World Conference on Communication & Computing (WCONF)
Reading habit opens up the door to succeed in learning. It is the soul of education. It is theref... more Reading habit opens up the door to succeed in learning. It is the soul of education. It is therefore essential to explore the reading habits of professional students to access their interest in reading in turn their personality, communication skills. The practice of reading does not mirror the lifestyle of most undergraduates in Academics and Universities. It is assumed that quite handful of professional students are aware of how to read, what to read, when to read and where to read. Basically, reading for refreshment or relieving stress is quite common among the educated population.The study is a concise survey on “Reading Habits of Professional Students.” Data is collected using a validated online questionnaire. It is analysed using Pandas – a Python library for analysis and manipulation of data. Further matplotlib – a popular python package for data visualisation is used to showcase the results in the form of plots and graphs. Interpretations are drawn based on the varied responses from the respondents. The findings disclosed that nearly all the respondents understand the importance of reading. The study revealed that 91.95% love to read from their various fields while 8.05% showed their unwillingness towards book reading. 43.34% of the student population likes reading fiction books, whereas only 1.24% of professional students go with non-fictional books besides 55.42% showed interest to read both. It is observed that reading habit among professional students pursuing their engineering stream is encouraging. It is recommended that students should develop and show curiosity towards book reading. Parents should function as catalysts encouraging their children by supplementing them with needed reading resources besides creating a conducive atmosphere for them.
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2023 3rd Asian Conference on Innovation in Technology (ASIANCON)
Image Denoising is one of the current day challenges in the field of image processing. Noise in t... more Image Denoising is one of the current day challenges in the field of image processing. Noise in the image is the existence of artifacts that do not start from the original picture content. Autoencoders have made considerable progress in image denoising because of their ability to reconstruct image inputs. Autoencoders for denoising images usually accepts a degraded image as input and is trained to predict the reconstructed image as its output. An effort has been made to analyse the functioning of selected autoencoders for image denoising, such as Basic Autoencoder, Denoising Autoencoder and Convolutional Denoising Autoencoder using the Modified National Institute of Standards and Technology database (MNIST) dataset. The performance of these models is evaluated and compared using Structural Similarity Index Measure, Peak Signal to Noise Ratio evaluation metrics. The strengths and weaknesses of each autoencoder are discussed and the factors that influence their performance are explored. Qualitative and quantitative analysis of the dataset provides an insight of effectiveness and efficiency of each autoencoder in denoising images. Observations show that Convolutional Denoising Autoencoder out-performs other autoencoders in terms of the evaluation metrics and better reconstructed image. This study can act as a base for researchers and practitioners to identify suitable autoencoders for denoising images in real-life applications.
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TIJER, 2023
The automotive industry has witnessed an exponential growth in the sale of cars, driven by factor... more The automotive industry has witnessed an exponential growth in the sale of cars, driven by factors such as economic considerations, changing consumer preferences, and improved vehicle durability. Due to the fact that not everyone can afford to buy a new automobile and that used cars with no internal mechanical issues are available for a slightly reduced price compared to the original price, used car sales have also significantly increased. In order to improve decision-making for both buyers and sellers, this paper presents a detailed study on the prediction of used automobile pricing using machine learning approach. The growing importance of used car price forecasting in the context of the dynamic automotive market is addressed in this research. For both buyers and sellers, determining the market value of used cars is essential given the increase in demand for them. This study measures model's predicted performance using machine learning algorithms. A user application is created that displays the anticipated cost after receiving input from vehicle manufacturer parameters such as model and other details. The proposed web explore model aims to predict the resale price of automobiles with 90% accuracy.
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Conference Presentations by Appalabatla Shanmukha Priya Sreenidhi
Papers by Appalabatla Shanmukha Priya Sreenidhi