Enes Cingöz's starred repositories
H3-Mapping
H3-Mapping: Quasi-Heterogeneous Feature Grids for Real-time Dense Mapping Using Hierarchical Hybrid Representation (submitted to RAL 2024)
HeLiMOS-PointCloud-Toolbox
HeLiMOS: Heterogeneous LiDAR Dataset for Moving Object Segmentation @ IROS'2024
SLAM2REF
This project allows the alignment and correction of LiDAR-based SLAM session data with a reference map or another session, also the retrieval of 6-DoF poses with accuracy of up to 3 cm given an accurate TLS point cloud as a reference map (this map should be accurate at least regarding the position of permanent elements such as walls and columns).
Cryptocurrency
Unsupervised Machine Learning analysis to find patterns in Cryptocurrencies market valuations.
3D_Map_Evaluation
Quantitative 3D Map Accuracy Evaluation Hardware and Algorithm for LiDAR(-Inertial) SLAM [IEEE ICCAS 2024]
3D-Registration-with-Maximal-Cliques
Source code of CVPR 2023 paper
Stock-market-prediction-and-screener
In Stock Market Prediction, our aim is to build an efficient Machine Learning model to predict the future value of the financial stocks of a company.Our machine learning model will be presented to retail investors with a third-party web app with the help of Streamlit.
Stock-Clustering-and-Prediction
To build, train and test LSTM model to forecast next day 'Close' price and to create diverse stock portfolios using k-means clustering to detect patterns in stocks that move similarly with an underlying trend i.e., for a given period, how stocks trend together.To deploy our findings to an app along with an interactive dashboard to predict the next day ‘Close’ for any given stock.
compare-my-stocks
A system for visualizing interesting stocks. Has powerful comparison capabilities and works seamlessly with your jupyter notebook. Written in QT with matplotlib.
clustering-market-stocks
I will find similarities among companies and group them into clusters.
sp500-stock-similarity-time-series
Improve S&P 500 stock price prediction (random forest and gradient boosting trees) with time series similarity measurements: DTW, SAX, co-integration, Euclidean and Pearson.
Similarity-Correlation--in-Stock-Market
Detect Correlation in the Stock Market on the basis of various features. ● CLOSE feature is used as a criteria for comparing the stocks. ● R2_Score, Cosine Similarity and Normalized R2_Score are used as strategies to find the similarity. Technology Used: Python, NumPy, pandas, sklearn, matplotlib
Auto_Jobs_Applier_AIHawk
Auto_Jobs_Applier_AIHawk is a tool that automates the jobs application process. Utilizing artificial intelligence, it enables users to apply for multiple job offers in an automated and personalized way.
MS-Mapping
MS-Mapping: An Uncertainty-Aware Large-Scale Multi-Session LiDAR Mapping System
machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
FinMem-LLM-StockTrading
FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design
LLM-and-NLP-models-in-Cryptocurrency-Sentiment-Analysis
LLM and NLP models in Cryptocurrency Sentiment Analysis: A Comparative Classification Study
commonroad-scenario-designer
Toolbox for Map Conversion and Scenario Creation for Autonomous Vehicles.