Showing 61–72 of 95 results

Impact of Fuzziness for Skin Lesion Classification with Transformer-Based Model

5,500.00
Aim:       The primary objective of this project is to elevate the accuracy of skin lesion classification through the implementation

Integration of Traditional Knowledge and Modern Science: A Holistic Approach to Identify Medicinal Leaves for Curing Diseases

5,500.00
Aim: The aim of this project is to develop and implement a holistic methodology for identifying and evaluating medicinal leaves with the potential to treat various diseases.

Intelligent Crop Recommendation System using Machine Learning

5,500.00
Aim:       Predict the crop yield and deliver the end user with proper recommendations about required fertilizer ratio based on

Krushi Sahyog: Plant disease identification and Crop recommendation using Artificial Intelligence

5,500.00
Aim:             To detect the plant leaf disease and to recommend the crop using Machine and Deep learning. Abstract:  

LCDctCNN: Lung Cancer Diagnosis of CT scan Images Using CNN Based Model

5,500.00
Aim:  To create a robust and accurate diagnostic tool employing Convolutional Neural Networks (CNNs) for the analysis of CT scan

LE-YOLO: Lightweight and Efficient Detection Model for Wind Turbine Blade Defects Based on Improved YOLO

5,500.00
Aim: To develop a lightweight and efficient detection model using YOLO-v8 for identifying wind turbine blade defects with improved accuracy and real-time performance.

Loan Status Prediction in the Banking Sector using Machine Learning

5,500.00
Aim:          To determine the customer loan approval system using machine learning algorithms. Abstract:          Loan approval is a

LSTM Based Phishing Detection for Big Email Data

5,500.00
Aim:           Cybersecurity incidents have occurred frequently. Attackers have used phishing emails as a knock-on to successfully invade government systems.

Machine Learning Based Heart Disease Prediction System

5,500.00
Aim:       To apply machine learning techniques result in improving the accuracy in the prediction of cardiovascular disease.

Machine Learning Techniques for Sentiment Analysis of COVID-19-Related Twitter Data using GPT

5,500.00
Aim:           The aim of this research is to improve the accuracy and contextual understanding of sentiment analysis in COVID-19-related

Measuring the Heart Attack Possibility using Different Types of Machine Learning Algorithms

5,500.00
Aim:             To apply machine learning techniques result in improving the accuracy in the prediction of cardiovascular disease. Abstract:            

Medical Chatbot

5,500.00
Aim:          To create a chatbot that predicts medical conditions from images and provides disease-specific information, treatment options, and patient