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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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12 results for over-segmentation

Stochastic Sparse Subspace Clustering improves subspace clustering by reducing over-segmentation through dropout.

problem Over-segmentation in subspace clustering.
method Introducing dropout regularization to enforce denser connections between points from the same subspace.
result Stochastic Sparse Subspace Clustering effectively handles large datasets and reduces over-segmentation.

We investigate the performance of features that can capture nonlinear recurrence dynamics embedded in the speech signal for the task of Speech Emotion Recognition (SER). Reconstruction of the phase space of each speech frame and the computation of its respective Recurrence Plot (RP) reveals complex structures which can…

2018-11-09abs ↗pdf ↗

Synthetic learning improves neonatal brain MRI segmentation robustness.

problem Challenges in neonatal brain MRI segmentation due to image contrast and anatomical variations.
method Synthetic learning model trained on few T2-weighted volumes, then enhanced with motion artifacts and over-segmentation.
result Synthetic learning robust to image contrast and improves segmentation of both T1- and T2-weighted images.

Many real-world vision problems suffer from inherent ambiguities. In clinical applications for example, it might not be clear from a CT scan alone which particular region is cancer tissue. Therefore a group of graders typically produces a set of diverse but plausible segmentations. We consider the task of learning a di…

2018-06-13abs ↗pdf ↗

With the recent advances in complex networks theory, graph-based techniques for image segmentation has attracted great attention recently. In order to segment the image into meaningful connected components, this paper proposes an image segmentation general framework using complex networks based community detection algo…

2019-07-04abs ↗pdf ↗

We consider the problem of speaker diarization, the problem of segmenting an audio recording of a meeting into temporal segments corresponding to individual speakers. The problem is rendered particularly difficult by the fact that we are not allowed to assume knowledge of the number of people participating in the meeti…

2009-05-15abs ↗pdf ↗

Previously in 2014, we proposed the Nearest Descent (ND) method, capable of generating an efficient Graph, called the in-tree (IT). Due to some beautiful and effective features, this IT structure proves well suited for data clustering. Although there exist some redundant edges in IT, they usually have salient features …

2015-09-09abs ↗pdf ↗