activity
20122016
most citedShape recognition and classification in electro-sensing

69 citations · 87 across the 5 of their papers we have counts for

collaborators

9 papers

q-bio.TO2016★ 15 cited

Mathematical modelling of the electric sense of fish: the role of multi-frequency measurements and movement

Habib Ammari, Thomas Boulier, Josselin Garnier +1

Understanding active electrolocation in weakly electric fish remains a challenging issue. In this article we propose a mathematical formulation of this problem, in terms of partial…

math.NA2014

Time-domain multiscale shape identification in electro-sensing

Habib Ammari, Han Wang

This paper presents premier and innovative time-domain multi-scale method for shape identification in electro-sensing using pulse-type signals. The method is based on transform-inv…

math.NA2013

Wavelet methods for shape perception in electro-sensing

Habib Ammari, Stéphane Mallat, Irène Waldspurger +1

This paper aims at presenting a new approach to the electro-sensing problem using wavelets. It provides an efficient algorithm for recognizing the shape of a target from micro-elec…

math.NA2013★ 2 cited

Shape identification and classification in echolocation

Habib Ammari, Minh Phuong Tran, Han Wang

The paper aims at proposing the first shape identification and classification algorithm in echolocation. The approach is based on first extracting geometric features from the refle…

math.AP2013★ 1 cited

Detection and classification from electromagnetic induction data

Habib Ammari, Junqing Chen, Zhiming Chen +2

In this paper we introduce an efficient algorithm for identifying conductive objects using induction data derived from eddy currents. Our method consists of first extracting geomet…

math-ph2013★ 69 cited

Shape recognition and classification in electro-sensing

Habib Ammari, Thomas Boulier, Josselin Garnier +1

This paper aims at advancing the field of electro-sensing. It exhibits the physical mechanism underlying shape perception for weakly electric fish. These fish orient themselves at…