Session 04-07-25.md

Session of Machine Learning Division of CyberLabs

Conducted on: 04/07/2025

Agenda

VGGNet and GoogLeNet

Summary

1. The effect of the convolutional network depth on its accuracy.

2. Analyze the key design choices (small filters, increasing depth).

3. ⁠Training process of VGG (Preprocessing techniques, Choice of Hyperparameters, choice of training Scale S).

4. Testing process of VGG (Choice of test scale).

5. Different validation methods- Single Scale, Multi Scale, Dense evaluation and Multi-Crop.

6. Comparison with the state of art.

7. VGG performance on Localisation Test and Mean Average Precision(mAP).

8. Need of GoogLeNet, discussion on Hebbian Principle.

9. ⁠Need of 1x1 conv and why max pooling befor 1x1 conv.

10. Sparse and Deep connections.

11. Architecture detail of Inception Model.

12. Results of GoogLeNet.

Agenda for the next session

• Resnet
• DenseNet

Report Compiled by

Ritesh Kumbhare

Attendees

Final year: Samyak Jha Sir.

3rd year: Mukil Sir, Dilshad Sir.

2nd year: Anab, Arnav, Arjav, Anukul, Abhishek, Ritesh, Rajat, Sreenandan, Ayushman

Absentees

Second Year: None