kbhujbal/SubmarineShield-underwater_anomaly_recognition_svm
⚓ ML system for submarine threat detection using SVM to classify sonar signals as mines or rocks. Features GridSearchCV optimization, sklearn pipelines, and comprehensive evaluation metrics for underwater anomaly recognition.
Stars
9
Forks
1
Language
Python
License
MIT
Category
Last pushed
Nov 24, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/kbhujbal/SubmarineShield-underwater_anomaly_recognition_svm"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
RamySaleem/Machine-Predict-Lithologies-Using-Wireline-logs
To identify lithologies, geoscientists use subsurface data such as wireline logs and...
CatalystsReachOut/SonarRockMinePrediction
Submarines have to predict whether it is crossing a mine or a rock. So, we have to build a...
waleedgeo/GFSM
Official Repository for the paper "Global Flood Susceptibility"
Promisekeh/Lithology-Prediction-with-Machine-Learning
Lithology prediction of oil well logs using machine learning
NhanPhamThanh-IT/Logistic-Regression-Rock-Mine-Prediction
🪨 Machine learning project using logistic regression to classify sonar signals as either rocks...