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Aim: To detect the diabetic retinopathy disease in the earlier stage using Deep learning method Synopsis: Diabetic Retinopathy is a disease that can lead to partial or complete blindness. Research shows that it contributes around 5 percent of the total cases of blindness. Usually it takes about two weeks for the diagnosis of disease; time and money..

Aim:          Cyber bulling is described as the serious, intentional, and repetitive acts of a person’s cruelty toward others using various digital technologies. It is mainly expressed through nasty tweets, texts, or other social media posts. So we analyzing sentiment, emoji and bully detection to contro..

Aim:                  To apply machine learning techniques result in improving the accuracy in the liver disease prediction. Abstract:            The life of humans living without liver tumors is one of the fun..

Aim:          To apply the Deep Learning techniques based on convolution neural network improving the face mask detector accuracy.Synopsis:          The corona virus disease 2019 (COVID-19) has globally infected over 2.7million people and caused over 180,000 d..

Aim:          The aim of this paper is to develop an automatic white blood cell classification system using deep learning techniques. Specifically, the objective is to create a model capable of accurately classifying white blood cells (leucocytes) to aid in the diagnosis of various hematologic diseases, ..

Aim:          The aim is to leverage the power of machine learning to create efficient and accurate fraud detection systems that protect the interests of both financial institutions and their customers.Abstract:          As technology advanced and e-commerce s..

Aim:          Housing prices keep changing day in and day out and sometimes are hyped rather than being based on valuation. Predicting housing prices with real factors is the main crux of our research project. Here we aim to make our evaluations based on every basic parameter that is considered while det..

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Aim:             To detect the plant leaf disease and to recommend the crop using Machine and Deep learning. Abstract:              India is one of the leading countries worldwide in terms of farm output. Even after being a leading ..

Aim: To create a robust and accurate diagnostic tool employing Convolutional Neural Networks (CNNs) for the analysis of CT scan images, aiming to enhance the efficiency, precision, and early detection of lung cancer, ultimately contributing to improved patient outcomes and healthcare practicesAbstract:The most deadly and life-threatening disea..

Aim:            To detect the plant leaf diseases using neural network for high accuracy detectionSynopsis:            To ensure global food security and the overall profit of stakeholders, the importance of correctly detecting and classify..

Aim:         To determine the customer loan approval system using machine learning algorithms.Abstract:         Loan approval is a very important process for banking organizations. The systems approved or reject the loan applications. Recovery of loans is a major contributin..

Aim:          Cybersecurity incidents have occurred frequently. Attackers have used phishing emails as a knock-on to successfully invade government systems. Therefore, we designed a phishing email detection  method based on Bidirectional LSTM neural networkAbstract:     &nbs..

Aim:          The aim of this research is to improve the accuracy and contextual understanding of sentiment analysis in COVID-19-related tweets by combining the rule-based approach of TextBlob with the deep learning capabilities of GPT-2.Abstract:         The preva..

Aim:            To detect the COVID-19 using Machine Learning Classification Algorithms Abstract:          The Corona-virus 2019(COVID-19), which first occurs in Wuhan city of China in December 2019, spread quickly around the world and became a plagu..