3 papers
cs.CV2020
Enabling Incremental Knowledge Transfer for Object Detection at the Edge
Mohammad Farhadi Bajestani, Mehdi Ghasemi, Sarma Vrudhula +1
Object detection using deep neural networks (DNNs) involves a huge amount of computation which impedes its implementation on resource/energy-limited user-end devices. The reason fo…
cs.CV2019
A Novel Design of Adaptive and Hierarchical Convolutional Neural Networks using Partial Reconfiguration on FPGA
Mohammad Farhadi, Mehdi Ghasemi, Yezhou Yang
Nowadays most research in visual recognition using Convolutional Neural Networks (CNNs) follows the "deeper model with deeper confidence" belief to gain a higher recognition accura…
cs.CV2019
TKD: Temporal Knowledge Distillation for Active Perception
Mohammad Farhadi, Yezhou Yang
Deep neural networks based methods have been proved to achieve outstanding performance on object detection and classification tasks. Despite significant performance improvement, du…