31 citations · 45 across the 10 of their papers we have counts for
4 papers · 1 filter
BD-KD: Balancing the Divergences for Online Knowledge Distillation
Ibtihel Amara, Nazanin Sepahvand, Brett H. Meyer +2
We address the challenge of producing trustworthy and accurate compact models for edge devices. While Knowledge Distillation (KD) has improved model compression in terms of achievi…
CES-KD: Curriculum-based Expert Selection for Guided Knowledge Distillation
Ibtihel Amara, Maryam Ziaeefard, Brett H. Meyer +2
Knowledge distillation (KD) is an effective tool for compressing deep classification models for edge devices. However, the performance of KD is affected by the large capacity gap b…
Clustered Saliency Prediction
Rezvan Sherkati, James J. Clark
We present a new method for image salience prediction, Clustered Saliency Prediction. This method divides subjects into clusters based on their personal features and their known sa…
Consistency driven Sequential Transformers Attention Model for Partially Observable Scenes
Samrudhdhi B. Rangrej, Chetan L. Srinidhi, James J. Clark
Most hard attention models initially observe a complete scene to locate and sense informative glimpses, and predict class-label of a scene based on glimpses. However, in many appli…