Search - Deep Learning

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:          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:          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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Abstract:           DEEP learning with convolution neural networks (CNNs) has achieved state-of-the-art performance for automated medical image segmentation. However, automatic segmentation methods have not demonstrated sufficiently accurate and robust results for clinical use due to the inherent..

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 address the significant challenge of identifying plant diseases using deep Residual Network.Synopsis:            The proposed work addresses the challenges of identifying plant diseases using a lightweight Deep Residual N..

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 detect the COVID-19 using CT images by using Convolutional neural networkAbstract:            The Corona-virus 2019(COVID-19), which first occurs in Wuhan city of China in December 2019, spread quickly around the world an..

Aim: Achieving exam integrity through an AI-driven Smart Proctoring System for vigilant monitoring and prevention of malpractices in online assessments.Abstract:From past three years all human activities are affected by COVID19 but where the knowledge gaining and education for students aren’t stopped. Due to covid-19 affect many of the educati..

Aim:           To automate the detection of presence of ships and to classify the types of ships available in the given Image.Synopsis:         The detection of inshore and offshore ships is an essential task for a large variety of applications in both militar..

Aim:            To detect the plant leaf diseases using convolutional neural network for high accuracy detection.Synopsis:          Identification of leaf disease is very difficult in agriculture field. If identification is incorrect then there is a huge ..

Aim:           To automate the detection of presence of ships and to classify the types of ships available in the given Image.Synopsis:         The detection of inshore and offshore ships is an essential task for a large variety of applications in both military and civilian fields. The sur..