activity
20172020
most citedApproximating meta-heuristics with homotopic recurrent neural networks

5 citations · 12 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV2020

Assessing The Importance Of Colours For CNNs In Object Recognition

Aditya Singh, Alessandro Bay, Andrea Mirabile

Humans rely heavily on shapes as a primary cue for object recognition. As secondary cues, colours and textures are also beneficial in this regard. Convolutional neural networks (CN…

cs.CV20192 cited

Filtering Point Targets via Online Learning of Motion Models

Mehryar Emambakhsh, Alessandro Bay, Eduard Vazquez

Filtering point targets in highly cluttered and noisy data frames can be very challenging, especially for complex target motions. Fixed motion models can fail to provide accurate p…

cs.CV2019

Real-time tracker with fast recovery from target loss

Alessandro Bay, Panagiotis Sidiropoulos, Eduard Vazquez +1

In this paper, we introduce a variation of a state-of-the-art real-time tracker (CFNet), which adds to the original algorithm robustness to target loss without a significant comput…

cs.CV2018

Convolutional Recurrent Predictor: Implicit Representation for Multi-target Filtering and Tracking

Mehryar Emambakhsh, Alessandro Bay, Eduard Vazquez

Defining a multi-target motion model, which is an important step of tracking algorithms, can be very challenging. Using fixed models (as in several generative Bayesian algorithms,…

cs.CV2018

Hide and Seek tracker: Real-time recovery from target loss

Alessandro Bay, Panagiotis Sidiropoulos, Eduard Vazquez +1

In this paper, we examine the real-time recovery of a video tracker from a target loss, using information that is already available from the original tracker and without a signific…

cs.CV2018

Deep Recurrent Neural Network for Multi-target Filtering

Mehryar Emambakhsh, Alessandro Bay, Eduard Vazquez

This paper addresses the problem of fixed motion and measurement models for multi-target filtering using an adaptive learning framework. This is performed by defining target tuples…