Rashmita Khilar | Anna University (original) (raw)

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Papers by Rashmita Khilar

Recent Trends in Data Science and its Applications

One-class classification (OCC) is used to construct classification models even though the outlier... more One-class classification (OCC) is used to construct classification models even though the outlier samples are inadequate, weakened and not clearly defined samples. The OCC network has been dominantly employed in diverse application of machine learning. One-Class Classification (OCC) is an exceptional condition of multi-class classification in which the data used during the training phase is generated from a single positive class. The intent of a OCC network is to learn a representation and a classifier that deals with positively labeled queries. In the recent years adversarial learning Oneclass classification (ALOCC) method has outperformed the efficiency of the OCC performance. Since it has some limitations such as instability within the training phase and issues in reconstruction of data between inlier and outlier data. In this paper work, we have propounded a Multi head Driven Self Attention mechanism incorporated in the ALOCC network. The proposed MDSAL-OCC network outperforms other self attention network in OCC and effective in elevating the OCC accuracy. In this paper, we also presented a discussion about the comprehensive elaboration of the proposed framework of one-class classification Multi head Driven Self Attention Adversarial Learned One Class Classification (MDSAL-OCC) and also discussed about the role of MDSAL-OCC in train One Class Classification networks in detecting fetal congenital heart diseases (FCHD).

International Journal of Image and Graphics, Jul 21, 2023

As innovations for image handling, image enrichment (IE) can give more effective information and ... more As innovations for image handling, image enrichment (IE) can give more effective information and image compression can decrease memory space. IE plays a vital role in the medical field for which we have to use a noiseless image. IE applies to all areas of understanding and analysis of images. This paper provides an innovative algorithm called contrast-limited adaptive fuzzy gamma (CLAFG) for IE using chest X-ray (CXR) images. The image dissimilarity is enriched by computing several histograms and membership planes. The proposed algorithm comprises various steps. Firstly, CXR is separated into contextual region (CR). Secondly, the cliplimit, a threshold value which alters the dissimilarity of the CXR and applies it to the histogram which, is generated by CR and then applies the fuzzification technique via the membership plane to the CXR. Thirdly, the clipped histograms are performed in two ways, i.e. it is merged using bi-cubic interpolation techniques and it is modified with membership function. Finally, the resulting output from bi-cubic interpolation and membership function are fond of using upgrade contemplate standard methods for a richer CXR image.

Measurement: Sensors, Dec 1, 2022

Highly promising artificial intelligence tools, including neural network (ANN), genetic algorithm... more Highly promising artificial intelligence tools, including neural network (ANN), genetic algorithm (GA) and particle swarm optimization (PSO), were applied in the present study to develop an approach for the evaluation of Se(IV) removal from aqueous solutions by reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) composites. Both GA and PSO were used to optimize the parameters of ANN. The effect of operational parameters (i.e., initial pH, temperature, contact time and initial Se(IV) concentration) on the removal efficiency was examined using response surface methodology (RSM), which was also utilized to obtain a dataset for the ANN training. The ANN-GA model results (with a prediction error of 2.88%) showed a better agreement with the experimental data than the ANN-PSO model results (with a prediction error of 4.63%) and the RSM model results (with a prediction error of 5.56%), thus the ANN-GA model was an ideal choice for modeling and optimizing the Se(IV) removal by the nZVI/rGO composites due to its low prediction error. The analysis of the experimental data illustrates that the removal process of Se(IV) obeyed the Langmuir isotherm and the pseudo-second-order kinetic model. Furthermore, the Se 3d and 3p peaks found in XPS spectra for the nZVI/rGO composites after removing treatment illustrates that the removal of Se(IV) was mainly through the adsorption and reduction mechanisms.

2019 Innovations in Power and Advanced Computing Technologies (i-PACT), Mar 1, 2019

In today's world, parking area constitutes nearly most of traffic congestion is caused by vehicle... more In today's world, parking area constitutes nearly most of traffic congestion is caused by vehicles cruising around their destination and looking for a place to park. Due to this reason many day-today activities are affected such as waste of time, fuel wastage, frustration to drivers, theft fear, pollution etc. These factors motivated to pave a new method for smart parking system. In this method the detection is reliable, even when tests are performed using images captured from a different viewpoint. It also provides to design a highly reliable & compatible image segmentation measures for parking slot identification system and a user key driven data base measures to detect the vehicle using theft alarm system.

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS), Dec 13, 2022

2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA), Sep 21, 2022

Lecture notes in networks and systems, 2022

Remote sensing and digital image processing, Nov 14, 2019

Agriculture is the backbone of Indian production which is the vital sector for food production. I... more Agriculture is the backbone of Indian production which is the vital sector for food production. It is very important for national government to know what type of crops are being grown in which region for budget planning to import and export food products. Traditional ground survey method is laborious, time-consuming, and expensive. Along with this, continuous monitoring of crops is highly difficult. Crop area estimation is a key element in crop production forecasting and estimation. Crop classification and mapping are the most challenging tasks among the land use/land cover classification problems.

2023 International Conference on Circuit Power and Computing Technologies (ICCPCT)

Optical and Quantum Electronics

2023 Eighth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)

2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF)

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS)

Smart Innovation, Systems and Technologies, 2022