4 papers
Device-First Feedback: Toward Mobile-Native LLM-Driven Neural Architecture Search
Saif U Din, Muhammad Ahsan Hussain, Radu Timofte +1
Deploying convolutional neural networks generated by large language models (LLMs) on real mobile hardware requires more than GPU validation accuracy: INT8 TensorFlow Lite export, d…
LEMUR 2: Unlocking Neural Network Diversity for AI
Tolgay Atinc Uzun, Waleed Khalid, Saif U Din +17
Existing NAS benchmarks (e.g., NAS-Bench, NATS-Bench) cover only narrow, task-specific regions of the architectural design space and lack cross-domain or deployment-aware evaluatio…
A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions
Rahima Khanam, Muhammad Hussain
The YOLO (You Only Look Once) series has been a leading framework in real-time object detection, consistently improving the balance between speed and accuracy. However, integrating…
YOLOv11: An Overview of the Key Architectural Enhancements
Rahima Khanam, Muhammad Hussain
This study presents an architectural analysis of YOLOv11, the latest iteration in the YOLO (You Only Look Once) series of object detection models. We examine the models architectur…