13,707 research outputs found
Turning Optical Complex Media into Universal Reconfigurable Linear Operators by Wavefront Shaping
Performing linear operations using optical devices is a crucial building
block in many fields ranging from telecommunication to optical analogue
computation and machine learning. For many of these applications, key
requirements are robustness to fabrication inaccuracies and reconfigurability.
Current designs of custom-tailored photonic devices or coherent photonic
circuits only partially satisfy these needs. Here, we propose a way to perform
linear operations by using complex optical media such as multimode fibers or
thin scattering layers as a computational platform driven by wavefront shaping.
Given a large random transmission matrix (TM) representing light propagation in
such a medium, we can extract a desired smaller linear operator by finding
suitable input and output projectors. We discuss fundamental upper bounds on
the size of the linear transformations our approach can achieve and provide an
experimental demonstration. For the latter, first we retrieve the complex
medium's TM with a non-interferometric phase retrieval method. Then, we take
advantage of the large number of degrees of freedom to find input wavefronts
using a Spatial Light Modulator (SLM) that cause the system, composed of the
SLM and the complex medium, to act as a desired complex-valued linear operator
on the optical field. We experimentally build several
complex-valued operators, and are able to switch from one to another at will.
Our technique offers the prospect of reconfigurable, robust and
easy-to-fabricate linear optical analogue computation units
Deep metric learning to rank
We propose a novel deep metric learning method by revisiting the learning to rank approach. Our method, named FastAP, optimizes the rank-based Average Precision measure, using an approximation derived from distance quantization. FastAP has a low complexity compared to existing methods, and is tailored for stochastic gradient descent. To fully exploit the benefits of the ranking formulation, we also propose a new minibatch sampling scheme, as well as a simple heuristic to enable large-batch training. On three few-shot image retrieval datasets, FastAP consistently outperforms competing methods, which often involve complex optimization heuristics or costly model ensembles.Accepted manuscrip
Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach
In this paper, the problem of compressive imaging is addressed using natural
randomization by means of a multiply scattering medium. To utilize the medium
in this way, its corresponding transmission matrix must be estimated. To
calibrate the imager, we use a digital micromirror device (DMD) as a simple,
cheap, and high-resolution binary intensity modulator. We propose a phase
retrieval algorithm which is well adapted to intensity-only measurements on the
camera, and to the input binary intensity patterns, both to estimate the
complex transmission matrix as well as image reconstruction. We demonstrate
promising experimental results for the proposed algorithm using the MNIST
dataset of handwritten digits as example images
The scholarly impact of TRECVid (2003-2009)
This paper reports on an investigation into the scholarly impact of the TRECVid (TREC Video Retrieval Evaluation) benchmarking conferences between 2003 and 2009. The contribution of TRECVid to research in video retrieval is assessed by analyzing publication content to show the development of techniques and approaches over time and by analyzing publication impact through publication numbers and citation analysis. Popular conference and journal venues for TRECVid publications are identified in terms of number of citations received. For a selection of participants at different career stages, the relative importance of TRECVid publications in terms of citations vis a vis their other publications is investigated. TRECVid, as an evaluation conference, provides data on which research teams âscoredâ highly against the evaluation criteria and the relationship between âtop scoringâ teams at TRECVid and the âtop scoringâ papers in terms of citations is analysed. A strong relationship was found between âsuccessâ at TRECVid and âsuccessâ at citations both for high scoring and low scoring teams. The implications of the study in terms of the value of TRECVid as a research activity, and the value of bibliometric analysis as a research evaluation tool, are discussed
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