Works (9)

Updated: July 5th, 2023 15:41

2021 journal article

Enhancing the morphological segmentation of microscopic fossils through Localized Topology-Aware Edge Detection

AUTONOMOUS ROBOTS, 45(5), 709–723.

By: Q. Ge n, T. Richmond n, B. Zhong n, T. Marchitto* & E. Lobaton n

author keywords: Edge detection; Topological structure; Morphological segmentation
TL;DR: A homology-based detector of local structural difference between two edge maps with a tolerable deformation is employed as a new criterion for the training and design of data-driven approaches that focus on enhancing these structural differences. (via Semantic Scholar)
UN Sustainable Development Goal Categories
14. Life Below Water (OpenAlex)
Sources: Web Of Science, ORCID
Added: November 30, 2020

2021 journal article

Short-term load demand forecasting through rich features based on recurrent neural networks

IET GENERATION TRANSMISSION & DISTRIBUTION, 15(5), 927–937.

By: D. Zhao*, Q. Ge n, Y. Tian*, J. Cui*, B. Xie* & T. Hong*

TL;DR: A recurrent neural network based sequence to sequence (Seq2Seq) model to forecast the short-term power loads is presented and a feature attention mechanism, which is along channel and time directions, is developed to improve the quality of feature learning. (via Semantic Scholar)
Source: Web Of Science
Added: January 25, 2021

2019 journal article

Automated species-level identification of planktic foraminifera using convolutional neural networks, with comparison to human performance

MARINE MICROPALEONTOLOGY, 147, 16–24.

By: R. Mitra*, T. Marchitto*, Q. Ge n, B. Zhong n, B. Kanakiya n, M. Cook*, J. Fehrenbacher*, J. Ortiz*, A. Tripati*, E. Lobaton n

author keywords: Foraminifera; Identification; Automation; Artificial intelligence; Neural network
TL;DR: Using machine learning techniques to train convolutional neural networks to identify six species of extant planktic foraminifera that are widely used by paleoceanographers, and to distinguish the six species from other taxa, demonstrates that the approach can provide a versatile ‘brain’ for an eventual automated robotic picking system. (via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science)
Sources: Web Of Science, ORCID
Added: April 15, 2019

2017 conference paper

A comparative study of image classification algorithms for foraminifera identification

2017 IEEE Symposium Series on Computational Intelligence (SSCI), 3199–3206.

By: B. Zhong n, Q. Ge n, B. Kanakiya n, R. Mitra*, T. Marchitto & E. Lobaton*

TL;DR: A foram identification pipeline is proposed to automatic identify forams based on computer vision and machine learning techniques, and the classification algorithms provide competitive results when compared to human experts labeling of the data set. (via Semantic Scholar)
UN Sustainable Development Goal Categories
14. Life Below Water (OpenAlex)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2017 conference paper

Coarse-to-fine Foraminifera image segmentation through 3d and deep features

2017 IEEE Symposium Series on Computational Intelligence (SSCI).

By: Q. Ge n, B. Zhong n, B. Kanakiya n, R. Mitra*, T. Marchitto* & E. Lobaton n

TL;DR: A learning-based edge detection pipeline is proposed, using a coarse-to-fine strategy, to extract the vague edges from foraminifera images for segmentation using a relatively small training set and has the potential to provide useful features for species identification and other applications such as morphological study of foraminifa shells and foraminifiera dataset labeling. (via Semantic Scholar)
UN Sustainable Development Goal Categories
14. Life Below Water (OpenAlex)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2017 conference paper

Obstacle detection in outdoor scenes based on multi-valued stereo disparity maps

2017 IEEE Symposium Series on Computational Intelligence (SSCI).

By: Q. Ge n & E. Lobaton n

TL;DR: This paper proposes a methodology for robust obstacle detection in outdoor scenes for autonomous driving applications using a multi-valued stereo disparity approach that can recover the correct structure of obstacles on the scene when traditional estimation approaches fail. (via Semantic Scholar)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2016 article

Consensus-Based Image Segmentation via Topological Persistence

PROCEEDINGS OF 29TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, (CVPRW 2016), pp. 1050–1057.

By: Q. Ge n & E. Lobaton n

TL;DR: A new approach to capture the consensus of information from a set of segmentations generated by varying parameters of different algorithms is proposed and a robust segmentation is obtained with the detection of certain segmentation curves guaranteed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 6, 2018

2015 article

Non-Rigid Image Registration under Non-Deterministic Deformation Bounds

(E. Romero & N. Lepore, Eds.). 10TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION PROCESSING AND ANALYSIS, Vol. 9287.

By: Q. Ge n, N. Lokare n & E. Lobaton n

Ed(s): E. Romero & N. Lepore

author keywords: Non-rigid image registration; Lipschitz deformation; Uncertainty quantification
TL;DR: An approach for identifying point correspondences with zero false-negative rate and high precision is introduced under the assumption that two images of the same anatomic structure are related via a Lipschitz non-rigid deformation (the registration map). (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 6, 2018

2015 conference paper

Robust multi-target tracking in outdoor traffic scenarios via persistence topology based robust motion segmentation

2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 805–809.

By: S. Chattopadhyay n, Q. Ge n, C. Wei n & E. Lobaton n

TL;DR: This paper presents a motion segmentation based robust multi-target tracking technique for on-road obstacles that uses depth imaging information, and integrates persistence topology for segmentation and min-max network flow for tracking. (via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018

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