awesome-knowledge-distillation and awesome-knowledge-distillation-for-object-detection
The first is a general-purpose knowledge distillation resource covering the entire field, while the second is a specialized curated list focused exclusively on object detection applications, making them complements that serve different scopes of the same research area.
About awesome-knowledge-distillation
dkozlov/awesome-knowledge-distillation
Awesome Knowledge Distillation
This is a curated collection of research papers focused on 'knowledge distillation,' a technique in machine learning. It helps practitioners who need to make large, complex machine learning models more efficient for real-world deployment. You'll find papers detailing how to compress high-performing but resource-intensive models into smaller, faster ones, while retaining much of their accuracy. This resource is for machine learning engineers, data scientists, or researchers who are optimizing model performance for deployment in resource-constrained environments.
About awesome-knowledge-distillation-for-object-detection
LutingWang/awesome-knowledge-distillation-for-object-detection
A curated list of awesome knowledge distillation papers and codes for object detection.
This is a curated list of research papers and associated code for 'knowledge distillation' techniques in object detection. These techniques help make object detection models — which identify and locate objects within images or videos — more efficient and faster, especially for deployment on devices with limited computing power. The resource is for researchers, machine learning engineers, and computer vision scientists working to optimize and deploy object detection systems.
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