Papers › ConvNets for Counting: Object Detection of Transient Phenomena in Steelpan Drums

ConvNets for Counting: Object Detection of Transient Phenomena in Steelpan Drums

1 Feb 2021arXiv:2102.00632archive 2025-07-28

Scott H. Hawley, Andrew C. Morrison

We train an object detector built from convolutional neural networks to count interference fringes in elliptical antinode regions in frames of high-speed video recordings of transient oscillations in Caribbean steelpan drums illuminated by electronic speckle pattern interferometry (ESPI). The annotations provided by our model aim to contribute to the understanding of time-dependent behavior in such drums by tracking the development of sympathetic vibration modes. The system is trained on a dataset of crowdsourced human-annotated images obtained from the Zooniverse Steelpan Vibrations Project. Due to the small number of human-annotated images and the ambiguity of the annotation task, we also evaluate the model on a large corpus of synthetic images whose properties have been matched to the real images by style transfer using a Generative Adversarial Network. Applying the model to thousands of unlabeled video frames, we measure oscillations consistent with audio recordings of these drum strikes. One unanticipated result is that sympathetic oscillations of higher-octave notes significantly precede the rise in sound intensity of the corresponding second harmonic tones; the mechanism responsible for this remains unidentified. This paper primarily concerns the development of the predictive model; further exploration of the steelpan images and deeper physical insights await its further application.

PaperPDFCode

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

Code

drscotthawley/SPNet officialmentioned in papermentioned on GitHubtf report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Object DetectionStyle Transferobject-detection

1 archive task tag without a task page not shown.

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Methods

1cycle1x1 ConvolutionAverage PoolingBatch NormalizationConvolutionCutoutCycle Consistency LossDense ConnectionsDepthwise ConvolutionDepthwise Separable ConvolutionDropoutGAN Least Squares LossGlobal Average PoolingInstance NormalizationMax PoolingPatchGANPointwise ConvolutionReLUResidual BlockResidual ConnectionSigmoid ActivationSoftmaxWeight DecayYOLOv2

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections