Raw Dataset
33,137 images
396 car models
Data Cleaning
& Quality Control
Resource
Check
& Planning
Random Sampling
10,000 images
≥20 per class
YOLO Object Detection
Strategy
Roboflow Auto-labeling
Requires Paid Version
Manual Labeling
33K images
Too Large Scale
Switched to
Image Classification
No Labels Required

🚀 EfficientNet Pipeline

EfficientNetB7
4+ hrs/epoch
Session Timeouts
EfficientNetB0
Epochs: 50→20
Final
Model A

🏗️ ResNet Pipeline

ResNet50
3+ hrs/epoch
GPU Instability
ResNet50
Epochs: 25→5
Final
Model B
Colab Resource
Limitations
GPU Session
Instability
Memory
Bottlenecks
Training Duration
Constraints
Checkpoint
System
Lightweight
Models
Epoch
Optimization
Data
Sampling
Final
Model A
Final
Model B
Test
Predictions
Missing
Predictions
Fill with zeros
submission.csv
📊 Dataset: 10K/33K samples
🎯 Classes: 396 vehicle models
⚡ Platform: Colab-optimized
🔧 Method: Transfer Learning
Cloud Setup
(AWS/GCP)
Use Full Dataset
Training
Advanced Models
(ViT, ConvNeXt)
Ensemble
Techniques
Combine Models
(Detection + Classification)