7 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CV2023
AdaMTL: Adaptive Input-dependent Inference for Efficient Multi-Task Learning
Marina Neseem, Ahmed Agiza, Sherief Reda
Modern Augmented reality applications require performing multiple tasks on each input frame simultaneously. Multi-task learning (MTL) represents an effective approach where multipl…
cs.AR2022★ 1 cited
RUCA: RUntime Configurable Approximate Circuits with Self-Correcting Capability
Jingxiao Ma, Sherief Reda
Approximate computing is an emerging computing paradigm that offers improved power consumption by relaxing the requirement for full accuracy. Since real-world applications may have…
cs.NE2016★ 7 cited
Understanding the Impact of Precision Quantization on the Accuracy and Energy of Neural Networks
Soheil Hashemi, Nicholas Anthony, Hokchhay Tann +2
Deep neural networks are gaining in popularity as they are used to generate state-of-the-art results for a variety of computer vision and machine learning applications. At the same…