Recognition of Fish in Aqua Cage by Machine Learning with Image Enhancement

5,500.00
Aim: The aim of this project is to propose a system to automate the process of fish population monitoring in aquaculture environments by utilizing the YOLOv8 deep learning-based object detection model, combined with image enhancement techniques.

Rule-Based With Machine Learning IDS for DDoS Attack Detection in Cyber-Physical Production Systems (CPPS)

5,500.00

To enhance DDoS attack detection by implementing a machine learning system with hyperparameter optimization and advanced prediction techniques, utilizing the CICIDS dataset to achieve high classification accuracy and improve network security.

Sleep Apnea Detection From Single-Lead ECG: A Comprehensive Analysis of Machine Learning and Deep Learning Algorithms

5,500.00
Aim: Ā Ā Ā Ā Ā Ā Ā Ā Ā  We proposed detecting Sleep Apnea Detection From Single-Lead ECG. The advancement of smart wearables technologies has provided a

Smart Attendance Monitoring System Using Face Recognition for People with Disabilities

5,500.00
Aim: Ā Ā Ā Ā Ā Ā Ā  The aim of the project is to develop an automated, real-time attendance system using face recognition technology to enhance accuracy, eliminate manual errors, and streamline attendance tracking in institutions.

Smart Electricity Meter Monitoring and Prediction using iSocket

10,500.00
Aim: Ā Ā Ā Ā Ā Ā Ā Ā Ā  Aim of the project is to build a smart home automation system to control home appliances, monitor the

Time Series Forecasting and Modeling of Food Demand Supply Chain Based on Regressors Analysis

5,500.00
Aim: Ā Ā Ā Ā Ā Ā  To Develop a methodology that combines the robustness of ARIMA and SARIMA models with the explanatory power of

Toward Improving Breast Cancer Classification Using an Adaptive Voting Ensemble Learning Algorithm

5,500.00

Aim:

Ā  Ā  Ā  Ā  Ā  To develop a high-accuracy breast cancer classification system using an optimized Support Vector Classifier integrated with preprocessing and feature selection techniques.

 

Twitter Spam Detection Using Natural Language Processing by Encoder Decoder Model

5,500.00
Aim: Ā Ā Ā Ā Ā Ā Ā Ā Ā  To enhance the assigning accuracy of former methods in spam detection in Twitter using advanced methods. Synopsis: Ā Ā Ā Ā Ā Ā Ā Ā Ā