Update README.md

README.md

@@ -57,16 +57,19 @@ HSI-SC-NeRF/
     │   └── fine-tune/
     ├── maize/                       
     └── pear/                        
+```
 
 ## 🧠 HSI-SC-NeRF Pipeline
 
 The reconstruction workflow consists of three main stages:
 
-**1. Dataset Acquisition**
+1. Dataset Acquisition
 Experimental setup and multi-view hyperspectral image collection using a stationary camera and a rotating object.
-**2. Data Preprocessing**
+
+2. Data Preprocessing
 White-reference spectral calibration, pseudo-RGB generation, and COLMAP-based pose estimation.
-**3. NeRF-Based Hyperspectral Point Cloud Reconstruction**
+
+3. NeRF-Based Hyperspectral Point Cloud Reconstruction
 Multi-channel hyperspectral NeRF training, hyperspectral point cloud generation, and refinement.
 
 This pipeline produces final 3D hyperspectral point clouds that support downstream spatial and spectral analysis.
@@ -87,10 +90,10 @@ This pipeline produces final 3D hyperspectral point clouds that support downstre
 ## 🔖 Citation
 If you use this dataset in your work, please cite:
 
-@article{ku2026hyperstationarynerf,
-  title = {HSI-SC-NeRF: NeRF-based Hyperspectral 3D Reconstruction using a Stationary Camera for Agricultural Applications},
-  author = {Kibon Ku, Talukder Z. Jubery, Adarsh Krishnamurthy, Baskar Ganapathysubramanian},
-  year = {2026},
-  journal = {arXiv preprint arXiv:2602.16950}
+@article{ku2026hyperstationarynerf,\
+  title = {HSI-SC-NeRF: NeRF-based Hyperspectral 3D Reconstruction using a Stationary Camera for Agricultural Applications},\
+  author = {Kibon Ku, Talukder Z. Jubery, Adarsh Krishnamurthy, Baskar Ganapathysubramanian},\
+  year = {2026},\
+  journal = {arXiv preprint arXiv:2602.16950}\
 }