15 citations · 15 across the 2 of their papers we have counts for
5 papers
Biased Mixtures Of Experts: Enabling Computer Vision Inference Under Data Transfer Limitations
Alhabib Abbas, Yiannis Andreopoulos
We propose a novel mixture-of-experts class to optimize computer vision models in accordance with data transfer limitations at test time. Our approach postulates that the minimum a…
Graph-based Spatial-temporal Feature Learning for Neuromorphic Vision Sensing
Yin Bi, Aaron Chadha, Alhabib Abbas +2
Neuromorphic vision sensing (NVS)\ devices represent visual information as sequences of asynchronous discrete events (a.k.a., "spikes") in response to changes in scene reflectance.…
Graph-Based Object Classification for Neuromorphic Vision Sensing
Yin Bi, Aaron Chadha, Alhabib Abbas +2
Neuromorphic vision sensing (NVS)\ devices represent visual information as sequences of asynchronous discrete events (a.k.a., ``spikes'') in response to changes in scene reflectanc…
Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks
Mohammad Jubran, Alhabib Abbas, Aaron Chadha +1
Advanced video classification systems decode video frames to derive the necessary texture and motion representations for ingestion and analysis by spatio-temporal deep convolutiona…
Video Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor
Aaron Chadha, Alhabib Abbas, Yiannis Andreopoulos
We investigate video classification via a two-stream convolutional neural network (CNN) design that directly ingests information extracted from compressed video bitstreams. Our app…