most citedScale Steerable Filters for Locally Scale-Invariant Convolutional Neural Networks

35 citations · 65 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2019

Investigating Convolutional Neural Networks using Spatial Orderness

Rohan Ghosh, Anupam K. Gupta, Mehul Motani

Convolutional Neural Networks (CNN) have been pivotal to the success of many state-of-the-art classification problems, in a wide variety of domains (for e.g. vision, speech, graphs…

cs.CV201935 cited

Scale Steerable Filters for Locally Scale-Invariant Convolutional Neural Networks

Rohan Ghosh, Anupam K. Gupta

Augmenting transformation knowledge onto a convolutional neural network's weights has often yielded significant improvements in performance. For rotational transformation augmentat…

cs.CV2019

Pose-Invariant Object Recognition for Event-Based Vision with Slow-ELM

Rohan Ghosh, Siyi Tang, Mahdi Rasouli +2

Neuromorphic image sensors produce activity-driven spiking output at every pixel. These low-power consuming imagers which encode visual change information in the form of spikes hel…

cs.CV201927 cited

Spatiotemporal Filtering for Event-Based Action Recognition

Rohan Ghosh, Anupam Gupta, Andrei Nakagawa +2

In this paper, we address the challenging problem of action recognition, using event-based cameras. To recognise most gestural actions, often higher temporal precision is required…

cs.CV20193 cited

Spatiotemporal Feature Learning for Event-Based Vision

Rohan Ghosh, Anupam Gupta, Siyi Tang +2

Unlike conventional frame-based sensors, event-based visual sensors output information through spikes at a high temporal resolution. By only encoding changes in pixel intensity, th…