Works (9)
Updated: July 5th, 2023 15:41
2020 journal article
Enhancing the morphological segmentation of microscopic fossils through Localized Topology-Aware Edge Detection
AUTONOMOUS ROBOTS, 45(5), 709–723.
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
3. Good Health and Well-being
(Web of Science)
14. Life Below Water
(OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: November 30, 2020
2020 journal article
Short-term load demand forecasting through rich features based on recurrent neural networks
IET GENERATION TRANSMISSION & DISTRIBUTION, 15(5), 927–937.
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)
open access via ietresearch.onlinelibrary.wiley.com (publisher PDF)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(Web of Science; OpenAlex)
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.
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, NC State University Libraries, 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.
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, 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).
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, 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).
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, NC State University Libraries
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.
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
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
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.
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
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
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.
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, NC State University Libraries
Added: August 6, 2018
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