Update app.py

app.py

@@ -80,13 +80,34 @@ def update_neurons(activation, seed):
 
 # Gradio Interface
 with gr.Blocks() as demo:
-    gr.Markdown("# ANN vs Linear Model Predictor")
+    gr.Markdown("# Cholestrol Concentration Prediction - ANN and Linear Model")
+    gr.Markdown("# **Cholestrol Concentration Prediction - ANN and Linear Model**")
     gr.Markdown("Dynamically select models and predict cholesterol concentration.")
     
+    gr.Markdown("### **Authors:**")
+    gr.Markdown("""
+**Poornima G**  
+Research Scholar, Centre for Nanoscience and Technology, Pondicherry University, Puducherry-605 014  
+[Google Scholar](https://scholar.google.com/citations?user=N2uAkJEAAAAJ&hl=en) | [ORCiD](https://orcid.org/0000-0002-7398-5651)
+
+**Nihad Alungal**  
+Research Scholar, Centre for Nanoscience and Technology, Pondicherry University, Puducherry-605 014  
+[Google Scholar](https://scholar.google.com/citations?hl=en&user=Qi-xkEYAAAAJ) | [ORCiD](https://orcid.org/0009-0000-4561-1874)
+
+**Caxton Emerald S**  
+Research Scholar, Department of Computer Science, School of Engineering and Technology, Pondicherry University, Puducherry - 605 014  
+[Google Scholar](https://scholar.google.com/citations?user=OgCHQv4AAAAJ&hl=en) | [ORCiD](https://orcid.org/0000-0002-7763-3987)
+
+**Dr. S. Kannan**  
+Professor, Centre for Nanoscience and Technology, Pondicherry University, Puducherry-605 014  
+[Web Page](http://www.pondiuni.edu.in/profile/dr-s-kannan)
+    """)
+    # gr.Markdown("Dynamically select models and predict cholesterol concentration.")
+    
     with gr.Row():
-        r = gr.Number(label="R (0 -255)")
-        g = gr.Number(label="G (0 -255)")
-        b = gr.Number(label="B (0 -255)")
+        r = gr.Number(label="Mean R (0 -255)")
+        g = gr.Number(label="Mean G (0 -255)")
+        b = gr.Number(label="Mean B (0 -255)")
 
     with gr.Row():
         activation = gr.Dropdown(choices=activations, label="Activation Function", interactive=True)