User profiles for Sonali Agarwal
 | Sonali AgarwalAssociate Professor, Indian Institute of Information Technology, Allahabad, India Verified email at iiita.ac.in Cited by 4990 |
One-class support vector classifiers: A survey
S Alam, SK Sonbhadra, S Agarwal… - Knowledge-Based …, 2020 - Elsevier
Over the past two decades, one-class classification (OCC) becomes very popular due to its
diversified applicability in data mining and pattern recognition problems. Concerning to OCC, …
diversified applicability in data mining and pattern recognition problems. Concerning to OCC, …
[PDF][PDF] A survey on Data Mining approaches for Healthcare
Data Mining is one of the most motivating area of research that is become increasingly popular
in health organization. Data Mining plays an important role for uncovering new trends in …
in health organization. Data Mining plays an important role for uncovering new trends in …
COVID-19 epidemic analysis using machine learning and deep learning algorithms
The catastrophic outbreak of Severe Acute Respiratory Syndrome - Coronavirus (SARS-CoV-2)
also known as COVID-2019 has brought the worldwide threat to the living society. The …
also known as COVID-2019 has brought the worldwide threat to the living society. The …
White blood cell subtype detection and classification
Machine learning has endless applications in the health care industry. White blood cell
classification is one of the interesting and promising area of research. The classification of the …
classification is one of the interesting and promising area of research. The classification of the …
Face mask detection using transfer learning of inceptionv3
The world is facing a huge health crisis due to the rapid transmission of coronavirus (COVID-19).
Several guidelines were issued by the World Health Organization (WHO) for protection …
Several guidelines were issued by the World Health Organization (WHO) for protection …
Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques
The rampant coronavirus disease 2019 (COVID-19) has brought global crisis with its deadly
spread to more than 180 countries, and about 3,519,901 confirmed cases along with …
spread to more than 180 countries, and about 3,519,901 confirmed cases along with …
Sample reduction using farthest boundary point estimation (FBPE) for support vector data description (SVDD)
S Alam, SK Sonbhadra, S Agarwal… - Pattern Recognition …, 2020 - Elsevier
The objective of this paper is to design an algorithm to maximize the learning ability and
knowledge about the target class while minimizing the number of training samples for support …
knowledge about the target class while minimizing the number of training samples for support …
[HTML][HTML] Modality specific U-Net variants for biomedical image segmentation: a survey
With the advent of advancements in deep learning approaches, such as deep convolution
neural network, residual neural network, adversarial network; U-Net architectures are most …
neural network, residual neural network, adversarial network; U-Net architectures are most …
[HTML][HTML] Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks
The novel coronavirus 2019 (COVID-19) is a respiratory syndrome that resembles pneumonia.
The current diagnostic procedure of COVID-19 follows reverse-transcriptase polymerase …
The current diagnostic procedure of COVID-19 follows reverse-transcriptase polymerase …
A comparison on multi-class classification methods based on least squares twin support vector machine
Least Squares Twin Support Vector Machine (LSTSVM) is a binary classifier and the
extension of it to multiclass is still an ongoing research issue. In this paper, we extended the …
extension of it to multiclass is still an ongoing research issue. In this paper, we extended the …