82 citations · 324 across the 42 of their papers we have counts for
8 papers · 1 filter
An Empirical Method to Quantify the Peripheral Performance Degradation in Deep Networks
Calden Wloka, John K. Tsotsos
When applying a convolutional kernel to an image, if the output is to remain the same size as the input then some form of padding is required around the image boundary, meaning tha…
Contextual Interference Reduction by Selective Fine-Tuning of Neural Networks
Mahdi Biparva, John Tsotsos
Feature disentanglement of the foreground target objects and the background surrounding context has not been yet fully accomplished. The lack of network interpretability prevents a…
PESAO: Psychophysical Experimental Setup for Active Observers
Markus D. Solbach, John K. Tsotsos
Most past and present research in computer vision involves passively observed data. Humans, however, are active observers outside the lab; they explore, search, select what and how…
Two-Stream Networks for Lane-Change Prediction of Surrounding Vehicles
David Fernández-Llorca, Mahdi Biparva, Rubén Izquierdo-Gonzalo +1
In highway scenarios, an alert human driver will typically anticipate early cut-in and cut-out maneuvers of surrounding vehicles using only visual cues. An automated system must an…
Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs
Amir Rasouli, Iuliia Kotseruba, John K. Tsotsos
One of the major challenges for autonomous vehicles in urban environments is to understand and predict other road users' actions, in particular, pedestrians at the point of crossin…
Compact Neural Representation Using Attentive Network Pruning
Mahdi Biparva, John Tsotsos
Deep neural networks have evolved to become power demanding and consequently difficult to apply to small-size mobile platforms. Network parameter reduction methods have been introd…
Do Saliency Models Detect Odd-One-Out Targets? New Datasets and Evaluations
Iuliia Kotseruba, Calden Wloka, Amir Rasouli +1
Recent advances in the field of saliency have concentrated on fixation prediction, with benchmarks reaching saturation. However, there is an extensive body of works in psychology a…
Selective Segmentation Networks Using Top-Down Attention
Mahdi Biparva, John Tsotsos
Convolutional neural networks model the transformation of the input sensory data at the bottom of a network hierarchy to the semantic information at the top of the visual hierarchy…