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 Fast and Accurate Violence Detection for Automated Video Surveillance Applications

5,500.00
Aim: Ā Ā Ā Ā Ā Ā Ā Ā Ā  To detect and identify the Violation detection using Deep-Learning techniques. Abstract: Ā Ā Ā Ā Ā Ā Ā  The widespread deployment of surveillance cameras,

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

5,500.00
Aim: The primary aim of this study is to develop a robust and accurate auxiliary diagnostic system for breast cancer by integrating machine learning techniques with a hybrid strategy.

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.

 

Traffic Signs Recognition using CNN and Keras

5,500.00
Aim: Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā  To detect and identify the Traffic Signs detection using CNN. Ā Abstract: Ā Ā Ā Ā Ā Ā Ā Ā  Traffic sign recognition and detection are

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 

Uncertain Facial Expression Recognition via Multi-Task Assisted Correction

5,500.00
The aim of this research is to develop a robust and accurate facial expression recognition system that addresses the challenges posed by uncertain and ambiguous data. We aim to improve upon existing methods to enhance feature representation learning and uncertainty mitigation.

Whale and Dolphin Classification

5,500.00
The proposed method involves a multi-step process to classify whale and dolphin species from images. First, the dataset is collected and pre-processed to ensure high-quality input data. The VGG16 model is used to extract features from the images, capturing complex patterns and details. These features are then used to train a Support Vector Machine (SVM) model, which excels in binary and multi-class classification tasks.