Python
Sentiment Analysis and Emotion Detection on Cryptocurrency Related Tweets Using Ensemble LSTM-GRU Model
Silent Alert: Advancing Women’s Security through Smart Sign Recognition and AI
Sleep Apnea Detection From Single-Lead ECG: A Comprehensive Analysis of Machine Learning and Deep Learning Algorithms
Smart Attendance Monitoring System Using Face Recognition for People with Disabilities
Social Media Forensics an Adaptive Cyberbullying-Related Hate Speech Detection Approach Based on Neural Networks with Uncertainty
The Effect of Fake Reviews on e-Commerce during and After Covid-19 Pandemic: SKL-Based Fake Reviews Detection
Time Series Forecasting and Modeling of Food Demand Supply Chain Based on Regressors Analysis
Toward Fast and Accurate Violence Detection for Automated Video Surveillance Applications
Toward Improving Breast Cancer Classification Using an Adaptive Voting Ensemble Learning Algorithm
Traffic Signs Recognition using CNN and Keras
Twitter Spam Detection Using Natural Language Processing by Encoder Decoder Model
Whale and Dolphin Classification
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.