- Generative Adversarial Networks and Image Synthesis
- Currency Recognition and Detection
- Advanced Neural Network Applications
- Retinal Imaging and Analysis
- Hydrological Forecasting Using AI
- Water Quality Monitoring Technologies
- Retinal Diseases and Treatments
- Anomaly Detection Techniques and Applications
- Image Processing and 3D Reconstruction
- Water Quality Monitoring and Analysis
- Time Series Analysis and Forecasting
- Digital Media Forensic Detection
- Retinal and Optic Conditions
Indian Institute of Management Lucknow
2023-2024
Dr. A.P.J. Abdul Kalam Technical University
2023
To obtain high performance, generalization, and accuracy in machine learning applications, such as prediction or anomaly detection, large datasets are a necessary prerequisite. Moreover, the collection of data is time-consuming, difficult, expensive for many imbalanced small datasets. These challenges evident collecting financial banking services, pharmaceuticals healthcare, manufacturing automobile, robotics car, sensor time-series data, more. overcome collection, researchers domains...
A region’s population growth inevitably results in higher water consumption. This persistent rise use increases the wastewater production. Consequently, due to this increase (influent), Wastewater Treatment Plants (WWTPs) are required run effectively order handle huge demand for treated/processed (effluent). Knowing advance influent and effluent parameters operational efficiency enables cost-effective utilization of diverse resources at treatment plants. paper is based on a...
Synthetic data generation research has been progressing at a rapid pace and novel methods are being designed every now then. Earlier, statistical were used to learn the distributions of real then sample synthetic from those distributions. Recent advances in generative models have led more efficient modeling complex high-dimensional datasets. Also, privacy concerns development robust with lesser risk breaches. Firstly, paper presents comprehensive survey existing techniques for tabular...