Update README.md

README.md

@@ -8,20 +8,19 @@ multilinguality:
 - monolingual
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-# FedJam Dataset
+## FedJam Dataset
 
 The **FedJam dataset** is a **multimodal dataset** designed for jamming detection and classification in wireless networks, pairing **time–frequency spectrogram images** with **cross-layer network KPI time series**. The dataset is designed to support **multimodal learning**, **federated learning**, and **robust classification under heterogeneous data distributions**.
 Each sample contains **aligned vision and time-series modalities**, enabling joint modeling of physical-layer signal characteristics and network-layer performance indicators.
 
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-# Code
+## Code
 
 The research code for the paper **_“FedJam: Multi-Modal Federated Learning Framework for Jamming Detection”_**,  
 which uses this dataset, can be accessed here:
 
-**🔗 GitHub repository:** https://github.com/panitsasi/fedJam  
-*(accepted at IEEE INFOCOM 2026)*
+** GitHub repository:** https://github.com/panitsasi/fedJam *(accepted at IEEE INFOCOM 2026)*
 
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@@ -34,7 +33,7 @@ which uses this dataset, can be accessed here:
 
 - **Modality 2 (Time Series)**: Network KPIs (WiFi)  
   - Format: CSV / structured sequences  
-  - **Fixed-length multivariate time series**
+  - **Fixed-length normalized multivariate time series**
   - **256 measurements per KPI feature, per sample**
   - Features:
     - `Time`