Prasanna Kompalli

• PhD
• Gokaraju Rangaraju Institute of Engineering & Technology

Colors are the smiles of nature. Digital image processing has widely employed the use of the function the color due to its effectiveness as a tool in classifying and identifying objects, which can be distinguished based on various relevant shades of color. This work aims to create a software tool that assists color-blind individuals in identifying...

In many countries, agriculture has an excess impact on life of human beings and economic status. As leaf plays an important role, it gives information about the quantity and quality of agriculture yield depending upon the condition in advance. In this paper, we proposed the system which focuses on the detection of disease in plant leaves using Deep...

Plants are extremely disposed to diseases that mark the growth of the plant which in chance marks the natural balance of the agriculturalist. The yield of crop drops due to contagions instigated by numerous types of illnesses on parts of the houseplant. Leaf illnesses are principally instigated by fungi, bacteria, virus, etc. Verdict of the illness...

Computed Tomography (CT) images are cross-sectional images of any specific area of a human body which allows doctors to see inside of a patient. CT scan is almost always the first imaging modality used to assess patients with suspected hemorrhage. A CT scan provides image reports in the form of grey shades. It is sometimes difficult to distinguish...

Background Road accidents are major cause of deaths worldwide. This is enormously due to fatigue, drowsiness and microsleep of the drivers. This don’t just risk the life of driver and copassengers but also a great threat to the vehicles and humans moving around that vehicle. Methods Research, online content and previously published paper related t...

In recent years, advancement in technologies has made it possible for most of the present-day organizations to store and record large streams of data. Such data sets which continuously and rapidly grow over time are referred to as data streams. Mining of such data streams is a unique opportunity and also a challenging task. Data stream mining is a...

Data coming from different sources is referred to as data streams. Data stream mining is an online learning technique where each data point must be processed as the data arrives and discarded as the processing is completed. Progress of technologies has resulted in the monitoring these data streams in real time. Data streams has created many new cha...

In recent years, advancement in technologies has made it possible for most of the present-day organizations to store and record large streams of data. Such data sets, which continuously and rapidly grow over time, are referred to as data streams. Mining of such data streams is a unique opportunity and also a challenging task. Data stream mining is...

Associative Classification is a recent and rewarding approach which combines associative rule mining and classification. This technique has attracted many researchers as it derives accurate classifier with effective rules. Associative classifiers are useful for application where maximum predictive accuracy is desired. Healthcare industry collects l...

Associative Classification is a recent and rewarding approach which combines associative rule mining and classification. This technique has attracted many researchers as it derives accurate classifier with effective rules. Associative classifiers are useful for application where maximum predictive accuracy is desired. Increasing access to huge data...

Data stream associative classification poses many challenges to the data mining community. In this paper, we address four major challenges posed, namely, infinite length, extraction of knowledge with single scan, processing time, and accuracy. Since data streams are infinite in length, it is impractical to store and use all the historical data for...

The data streams have recently emerged to address the problems of continuous data. Mining with data streams is the process of extracting knowledge structures from continuous, rapid data records [1]. An important goal in data stream mining is generation of compact representation of data. This helps in reducing time and space needed for further decis...

Due to the advancement of Technologies, many companies and organizations today have huge databases, that grow to a limit of millions of records per day. This data generation and storage has become faster than ever. This resulted in databases of unbounded growth. The data even changes over time. As a consequence, if the data cannot fit into memory,...