Ranga Raju Vatsavai
Also known as: Raju
Machine Learning, Data Mining, Spatial and Temporal, Remote Sensing, Image and Video Understanding, Computer Vision, Crop Biomass Monitoring, Settlement Mapping, HPC, Spatial Databases
Works (46)
Updated: April 3rd, 2024 16:39
2023 article
Cloud Imputation for Multi-sensor Remote Sensing Imagery with Style Transfer
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES: APPLIED DATA SCIENCE AND DEMO TRACK, ECML PKDD 2023, PT VII, Vol. 14175, pp. 37–53.
author keywords: Cloud imputation; Multi-sensor; Deep learning; Style transfer
Sources: Web Of Science, ORCID
Added: February 26, 2024
2023 article
Context Retrieval via Normalized Contextual Latent Interaction for Conversational Agent
2023 23RD IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS, ICDMW 2023, pp. 1543–1550.
TL;DR:
A novel method is presented, PK-NCLI, that is able to accurately and efficiently identify relevant auxiliary information to improve the quality of conversational responses by learning the relevance among persona, chat history, and knowledge background through lowlevel normalized contextual latent interaction.
(via Semantic Scholar)
arxiv.org (repository)
Sources: Web Of Science, ORCID
Added: March 18, 2024
2023 article
Harmonization-guided deep residual network for imputing under clouds with multi-sensor satellite imagery
PROCEEDINGS OF 2023 18TH INTERNATIONAL SYMPOSIUM ON SPATIAL AND TEMPORAL DATA, SSTD 2023, pp. 151–160.
author keywords: Neural Networks; Imputation; Remote Sensing; Multi-sensor; Knowledge-guided ML
TL;DR:
This work presents a knowledge-guided harmonization model that maps the reflectance response from one satellite collection to another based on the spectral distribution of the cloud-free pixels, and presents a novel harmonization-guided residual network to impute the areas under clouds.
(via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: January 8, 2024
2023 article
NOVEL DEEP LEARNING FRAMEWORK FOR IMPUTING HOLES IN ORTHORECTIFIED VHR IMAGES
IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, pp. 5158–5161.
TL;DR:
A new deep learning architecture based on Wide Activation Super Resolution (WDSR) network combined with an Adaptive Instance Normalization (AdaIN) based style transfer for imputing holes (missing pixels) in orthorectified images is presented.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(OpenAlex)
Sources: Web Of Science, ORCID
Added: March 25, 2024
2023 article
Persona-Coded Poly-Encoder: Persona-Guided Multi-Stream Conversational Sentence Scoring
2023 IEEE 35TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, ICTAI, pp. 250–257.
author keywords: Conversational AI; Dialogue Systems; Persona; Personalization; Multi-Modal Data
TL;DR:
This paper presents a novel Persona-Coded Poly-Encoder method that leverages persona information in a multi-stream encoding scheme to improve the quality of response generation for conversations and offers a path to better utilization of multi-modal data in conversational tasks.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(OpenAlex)
Sources: Web Of Science, ORCID
Added: March 4, 2024
2023 conference paper
Q-learning Based Simulation Tool for Studying Effectiveness of Dynamic Application of Fertilizer on Crop Productivity
Mei, Z., Vatsavai, R., & Chirkova, R. (2023, November 13).
TL;DR:
This work proposes a simple Q-learning-based simulation tool for studying the dynamic application of fertilizer and shows that the approach is computationally efficient while matching or performing better than other approaches.
(via Semantic Scholar)
Source: ORCID
Added: January 26, 2024
2023 journal article
Remote Sensing Based Crop Type Classification Via Deep Transfer Learning
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 16, 4699–4712.
author keywords: Agriculture; crop classification; deep learning; remote sensing; transfer learning
TL;DR:
The findings indicate that deep neural networks pretrained on a different domain dataset cannot be used as off-the-shelf feature extractors and that using the pretrained network weights as initial weights for training on the remote sensing dataset or freezing the early layers of the Pretrained network improves the performance compared to training the network from scratch.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: July 3, 2023
2022 journal article
A Survey of Single-Scene Video Anomaly Detection
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 44(5), 2293–2312.
author keywords: Anomaly detection; Computational modeling; Cameras; Training; Buildings; Legged locomotion; Feeds; Video anomaly detection; abnormal event detection; surveillance
MeSH headings : Algorithms
TL;DR:
This article summarizes research trends on the topic of anomaly detection in video feeds of a single scene and categorizes and situates past research into an intuitive taxonomy, and provides a comprehensive comparison of the accuracy of many algorithms on standard test sets.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
Sources: Web Of Science, ORCID
Added: May 23, 2022
2022 article
Deep Residual Network with Multi-Image Attention for Imputing Under Clouds in Satellite Imagery
2022 26TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), pp. 643–649.
TL;DR:
A novel deep learning-based imputation technique for inferring spectral values under the clouds using nearby cloud-free satellite image observations is presented and it is demonstrated that the ECA method is consistently better than all other methods.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
15. Life on Land
(OpenAlex)
Sources: Web Of Science, ORCID
Added: February 20, 2023
2022 article
Multi-stream Deep Residual Network for Cloud Imputation Using Multi-resolution Remote Sensing Imagery
2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA, pp. 97–104.
author keywords: Remote sensing; Cloud imputation; Benchmark; Multi-resolution; Deep learning
TL;DR:
A new benchmark data set consisting of images from two widely used and publicly available satellite images, Landsat-8 and Sentinel-2, and a new multi-stream deep residual network (MDRN) fills an important gap in the existing benchmark datasets, which allows exploitation of multi-resolution spectral information from the cloud-free regions of temporally nearby images.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science; OpenAlex)
Sources: Web Of Science, ORCID
Added: June 5, 2023
2022 article
Persona-Based Conversational AI: State of the Art and Challenges
2022 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS, ICDMW, pp. 993–1001.
TL;DR:
This study evaluates two strong baseline methods, the Ranking Profile Memory Network and the Poly-Encoder, on the NeurIPS ConvAI2 benchmark dataset and elucidates the importance of incorporating persona information into conversational systems.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(OpenAlex)
Sources: Web Of Science, ORCID
Added: May 30, 2023
2022 article
Real-Time Change Detection At the Edge
2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA, pp. 776–781.
author keywords: edge computing; Gaussian Mixture Models; change detection; precision agriculture; real time computing
TL;DR:
This paper demonstrates how an unsupervised GMM-based real-time change detection method at the edge can be used to identify weeds in real- time, and evaluates the scalability of the method on edge computing and traditional devices such as NVIDIA Jetson TX2, RTX 2080, and traditional Intel CPUs.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
2. Zero Hunger
(Web of Science)
Sources: Web Of Science, ORCID
Added: June 5, 2023
2021 article
A Scalable System for Searching Large-scale Multi-sensor Remote Sensing Image Collections
2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), pp. 3780–3783.
author keywords: SpatioTemporal Asset Catalog (STAC); Spatiotemporal Indexing; Remote Sensing Data Discovery
TL;DR:
Experimental evaluation shows that the spatiotemporal indexing based queries of this highly scalable STAC API based system are 1000x faster than standard STACAPI server.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
Sources: Web Of Science, ORCID
Added: July 5, 2022
2021 article
Local Clustering with Mean Teacher for Semi-supervised learning
2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), pp. 6243–6250.
TL;DR:
This work proposes a simple yet effective method called Local Clustering (LC) to mitigate the effect of confirmation bias in the Mean Teacher model and demonstrates on semi-supervised benchmark datasets SVHN and CIFAR-10 that adding the LC loss to MT yields significant improvements compared to MT and performance comparable to the state of the art in semi- supervised learning.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
4. Quality Education
(OpenAlex)
Sources: Web Of Science, ORCID
Added: August 30, 2021
2021 journal article
Perceptual metric learning for video anomaly detection
MACHINE VISION AND APPLICATIONS, 32(3).
author keywords: Video anomaly detection; Metric learning; Video surveillance; Siamese neural networks
TL;DR:
This work introduces a new approach to localize anomalies in surveillance video using a Siamese convolutional neural network to learn a metric between a pair of video patches, which is used to measure the perceptual distance between each video patch in the testing video and the video patches found in normal training video.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
Sources: Web Of Science, ORCID
Added: April 5, 2021
2019 journal article
Anomalous cluster detection in spatiotemporal meteorological fields
STATISTICAL ANALYSIS AND DATA MINING, 12(2), 88–100.
author keywords: anomaly detection; clustering; spatiotemporal data mining
TL;DR:
This paper develops a method for extreme event detection in meteorological datasets that follows from well known distribution‐based anomaly detection approaches and generalizes the Mahalanobis distance across distributions of different dimensionalities.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(OpenAlex)
Sources: Web Of Science, ORCID
Added: April 9, 2019
2018 article
Deformable Part Models for Complex Object Detection in Remote Sensing Imagery
BIGSPATIAL 2018: PROCEEDINGS OF THE 7TH ACM SIGSPATIAL INTERNATIONAL WORKSHOP ON ANALYTICS FOR BIG GEOSPATIAL DATA (BIGSPATIAL-2018), pp. 57–62.
author keywords: Deformable part models (DPMs); complex geospatial objects
TL;DR:
The landscape of research regarding DPMs is investigated, how this class of methods for object detection have evolved, and what remains to be explored to make the method more suitable for high-level, complex geospatial object understanding.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID
Added: July 1, 2019
2018 article
FUTURES-DPE: Towards Dynamic Provisioning and Execution of Geosimulations in HPC environments
26TH ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS (ACM SIGSPATIAL GIS 2018), pp. 464–467.
author keywords: Geosimulation; Distributed Computing; Computational Steering
TL;DR:
A co-scheduling approach for geosimulations in a resource constrained HPC environment is designed and a second design is presented which allows dynamic provisioning of resources in an HPC environments based on run-time users' demands.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure
(Web of Science)
11. Sustainable Cities and Communities
(OpenAlex)
Sources: Web Of Science, ORCID
Added: December 2, 2019
2018 article
Machine Learning Approaches for Slum Detection Using Very High Resolution Satellite Images
2018 18TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW), pp. 1397–1404.
author keywords: remote-sensing; image-classification; informal-settlements
TL;DR:
This paper performs several experiments to compare and contrast how various per-pixel based classification methods, when combined with various features perform in detecting slums, and explored a deep neural network, which showed better accuracy than the pixel based methods.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science)
15. Life on Land
(Web of Science)
Sources: Web Of Science, ORCID
Added: June 17, 2019
2018 journal article
Real-Time Energy Audit of Built Environments: Simultaneous Localization and Thermal Mapping
JOURNAL OF INFRASTRUCTURE SYSTEMS, 24(3).
TL;DR:
Leveraging thermography for managing built environments has become prevalent as a robust tool for detecting, analyzing, and reporting their performance in a nondestructive manner.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(OpenAlex)
11. Sustainable Cities and Communities
(Web of Science)
Sources: Web Of Science, ORCID
Added: October 19, 2018
2017 conference paper
Hierarchical change detection framework for biomass monitoring
2017 ieee international geoscience and remote sensing symposium (igarss), 620–623.
TL;DR:
A nearest neighbor based hierarchical change detection methodology for analyzing multi-temporal remote sensing imagery and shows that K-Means over-detects changes in comparison to the proposed method.
(via Semantic Scholar)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018
2017 journal article
High performance GPU computing based approaches for oil spill detection from multi-temporal remote sensing data
REMOTE SENSING OF ENVIRONMENT, 202, 28–44.
author keywords: High performance computing (HPC); Graphics processing unit (GPU); Oil spill; Morphological attribute profiles
TL;DR:
This work is oil spill detection from voluminous multi-temporal LANDSAT-7 imagery using high performance computing technologies such as graphics processing units (GPUs) and Message Passing Interface (MPI) to speed up the detection process and provide rapid response.
(via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018
2017 article
Parallel Processing over Spatial-Temporal Datasets from Geo, Bio, Climate and Social Science Communities: A Research Roadmap
2017 IEEE 6TH INTERNATIONAL CONGRESS ON BIG DATA (BIGDATA CONGRESS 2017), pp. 232–250.
author keywords: High performance computing; Spatial data mining; Remote sensing data; Medical images; Spatial econometrics; Map-reduce systems; CyberGIS; Parallel algorithms and data structures
TL;DR:
This vision paper reviews the current state ofart and lays out emerging research challenges in parallel processing of spatial-temporal large datasets relevant to a variety of scientific communities and requires a multidisciplinary effort to significantly advance domain research and have a broad impact on the society.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
Sources: Web Of Science, ORCID
Added: August 6, 2018
2017 journal article
Semantics-Enabled Framework for Spatial Image Information Mining of Linked Earth Observation Data
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 10(1), 29–44.
author keywords: Description logic (DL); direction relations; image retrieval; linked data; reasoning; region connection calculus (RCC-8); resource description framework (RDF); semantic web rules language (SWRL); SPARQL; spatial image information mining (SIIM); spatial relations; topological relations; Web ontology language (OWL)
TL;DR:
A spatial IIM (SIIM) framework is proposed, which integrates a logic-based reasoning mechanism to extract the hidden spatial relationships (both topological and directional) and enables image retrieval based on spatial relationships.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
13. Climate Action
(OpenAlex)
Sources: Web Of Science, ORCID
Added: August 6, 2018
2017 conference paper
Semi-supervised deep generative models for change detection in very high resolution imagery
2017 ieee international geoscience and remote sensing symposium (igarss), 1063–1066.
TL;DR:
A semi-supervised deep generative model for change detection in very high resolution multispectral and bitemporal imagery is explored and an auxiliary variational autoencoder is constructed that infers class labels without incurring high sample complexity costs.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(OpenAlex)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018
2016 article
A Scalable Probabilistic Change Detection Algorithm for Very High Resolution (VHR) Satellite Imagery
2016 IEEE INTERNATIONAL CONGRESS ON BIG DATA - BIGDATA CONGRESS 2016, pp. 275–282.
author keywords: Probabilistic Change Detection; Satellite Image Processing; Spatial Data Mining; OpenMP
TL;DR:
This work presents a sliding window based approach that produces changes at the native image resolution through thread-level parallelization on shared memory architectures and shows a 91% performance improvement compared to its sequential counterpart.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science)
15. Life on Land
(Web of Science)
Sources: Web Of Science, ORCID
Added: August 6, 2018
2016 journal article
Detecting Extreme Events in Gridded Climate Data
Procedia Computer Science, 80, 2397–2401.
author keywords: spatio-temporal; co-location; anomaly detection; trend analysis
TL;DR:
This paper presents their computationally efficient algorithms for anomalous cluster detection on climate change big data, and provides results on detection and tracking of surface temperature and geopotential height anomalies, a trend analysis, and a study of relationships between the variables.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(OpenAlex)
Sources: Crossref, ORCID
Added: February 21, 2020
2016 article
Guest editorial: big spatial data
Vatsavai, R., & Chandola, V. (2016, October). GEOINFORMATICA, Vol. 20, pp. 797–799.
TL;DR:
The purpose of this special issue is to showcase some of the recent developments and novel applications of the big spatial data field, which has attracted eleven papers covering broad range of spatial big data technologies and applications.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
Sources: Web Of Science, ORCID
Added: August 6, 2018
2016 journal article
Mapping Magnetic Ordering With Aberrated Electron Probes in STEM
Microscopy and Microanalysis, 22(S3), 1676–1677.
Sources: Crossref, ORCID
Added: February 21, 2020
2016 journal article
Monitoring Land-Cover Changes A machine-learning perspective
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 4(2), 8–21.
TL;DR:
A brief overview of the challenges in monitoring land-cover changes from the perspective of machine learning and some of the recent advances in machine learning that are relevant for addressing them are discussed.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science)
15. Life on Land
(Web of Science)
Sources: Web Of Science, ORCID
Added: August 6, 2018
2016 conference paper
Scalable nearest neighbor based hierarchical change detection framework for crop monitoring
2016 IEEE International Conference on Big Data (Big Data), 1309–1314.
UN Sustainable Development Goal Categories
13. Climate Action
(OpenAlex)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018
2016 journal article
Sliding Window-based Probabilistic Change Detection for Remote-sensed Images
Procedia Computer Science, 80, 2348–2352.
author keywords: Probabilistic Change Detection; Satellite Image Processing; Spatial Data Mining; Sliding Window; GMM
TL;DR:
This study proposes a sliding window-based extension of the probabilistic change detection approach to overcome artificial limitations of grid (patch)-based change detection.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science)
15. Life on Land
(Web of Science)
Sources: Crossref, ORCID
Added: February 21, 2020
2016 article
pFUTURES: A Parallel Framework for Cellular Automaton Based Urban Growth Models
GEOGRAPHIC INFORMATION SCIENCE, (GISCIENCE 2016), Vol. 9927, pp. 163–177.
TL;DR:
This paper presents a generic framework for co-ordinating I/O and computation for geospatial simulations in a distributed computing environment and demonstrates the performance and scalability benefits of the parallel implementation pFUTURES, an extension of the FUTURES open-source multi-level urban growth model.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science; OpenAlex)
15. Life on Land
(Web of Science)
Sources: Web Of Science, ORCID
Added: August 6, 2018
2015 article
A Scalable Complex Pattern Mining Framework for Global Settlement Mapping
2015 IEEE INTERNATIONAL CONGRESS ON BIG DATA - BIGDATA CONGRESS 2015, pp. 514–521.
author keywords: Very High-resolution Images; Multiple Instance Learning; Settlement Mapping; Complex Object Based Image Analysis
TL;DR:
This paper extends the Gaussian Multiple Instance (GMIL) learning by simplifying the model assumptions and shows that this method is computationally more efficient while maintaining similar accuracy as the GMIL algorithm.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science)
15. Life on Land
(Web of Science)
Sources: Web Of Science, ORCID
Added: August 6, 2018
2015 conference paper
Multitemporal data mining: From biomass monitoring to nuclear proliferation detection
2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multi-Temp).
TL;DR:
This paper describes the state-of-the-art data mining approaches with applications in biomass and critical infrastructure monitoring and shows how these approaches can be used to monitor the Earth to identify and characterize changes in near-real time.
(via Semantic Scholar)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018
2012 journal article
Probabilistic Change Detection Framework for Analyzing Settlement Dynamics Using Very High-resolution Satellite Imagery
Procedia Computer Science, 9, 907–916.
author keywords: Change Detection; pdf; Gaussian Distribution; Clustering
TL;DR:
A probabilistic framework to identify changes in human settlements using very high-resolution satellite imagery that provides comprehensible information about change areas, and minimizes the post-detection thresholding procedure often needed in traditional change detection algorithms.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(OpenAlex)
Sources: Crossref, ORCID
Added: September 10, 2020
2011 journal article
A hybrid classification scheme for mining multisource geospatial data
GeoInformatica, 15(1), 29–47.
author keywords: MLC; EM; Semi-supervised learning
TL;DR:
A hybrid semi-supervised learning algorithm is presented that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases and shows over 24% to 36% improvement in overall classification accuracy over conventional classification schemes.
(via Semantic Scholar)
Sources: Crossref, ORCID
Added: December 28, 2020
2011 journal article
A scalable gaussian process analysis algorithm for biomass monitoring
Statistical Analysis and Data Mining, 4(4), 430–445.
TL;DR:
A GP based online time series change detection algorithm is proposed and demonstrated in detecting different types of changes in Normalized Difference Vegetation Index data obtained from a study area in IA, USA and an efficient Toeplitz matrix based solution is proposed which significantly improves the computational complexity and memory requirements of the proposed GP based method.
(via Semantic Scholar)
Sources: Crossref, ORCID
Added: September 10, 2020
2011 journal article
Data Mining in Earth System Science (DMESS 2011)
Procedia Computer Science, 4, 1450–1455.
author keywords: Data mining; remote sensing; high performance computing; segmentation; change detection; synthesis; visualization
TL;DR:
This workshop will demonstrate how data mining techniques are applied in the Earth sciences and describe innovative computer science methods that support analysis and discovery in theEarth sciences.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(OpenAlex)
Sources: Crossref, ORCID
Added: September 10, 2020
2011 journal article
GX-Means: A model-based divide and merge algorithm for geospatial image clustering
Procedia Computer Science, 4, 186–195.
author keywords: Clustering; EM; GMM; K-means; G-means; X-means
TL;DR:
A computationally effcient model-based split and merge clustering algorithm that incrementally finds model parameters and the number of clusters that avoids certain limitations of these well-known clustering algorithms that are pertinent when dealing with geospatial data.
(via Semantic Scholar)
Sources: Crossref, ORCID
Added: September 10, 2020
2009 chapter
Incremental Clustering Algorithm for Earth Science Data Mining
In G. Allen, J. Nabrzyski, E. Seidel, G. D. van Albada, J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2009 (pp. 375–384).
Ed(s): G. Allen, J. Nabrzyski, E. Seidel, G. van Albada, J. Dongarra & P. Sloot
TL;DR:
This paper provides an extension of G-means algorithm which automatically learns the number of clusters present in the data and avoids over estimation of thenumber of clusters.
(via Semantic Scholar)
Sources: Crossref, ORCID
Added: December 28, 2020
2008 chapter
A Learning Scheme for Recognizing Sub-classes from Model Trained on Aggregate Classes
In Lecture Notes in Computer Science (pp. 967–976).
TL;DR:
A novel learning scheme that automatically learns sub-classes from the user given aggregate classes using finite Gaussian mixture instead of classical assumption of unimodal Gaussian per class is presented.
(via Semantic Scholar)
Sources: Crossref, ORCID
Added: September 10, 2020
2007 journal article
An efficient spatial semi-supervised learning algorithm
International Journal of Parallel, Emergent and Distributed Systems, 22(6), 427–437.
author keywords: Semi-supervised learning; MLC; MAP; EM; Random fields; image analysis; 62M40; 68U10
TL;DR:
This study shows that although, in general, classification accuracy improves with the addition of unlabeled training samples, it is not guaranteed to achieve consistently higher accuracies unless sufficient care is exercised when designing a semi-supervised classifier.
(via Semantic Scholar)
Sources: Crossref, ORCID
Added: September 10, 2020
2006 chapter
Improving DB2 Performance Expert – A Generic Analysis Framework
In Lecture Notes in Computer Science (pp. 1097–1101).
TL;DR:
This paper describes a component which is capable of doing early performance problem detection by analyzing the sensor values over a long period of time and showcases a trends plotter and workload characterizer which allows a DBA to have a better understanding of the resource usages.
(via Semantic Scholar)
Sources: Crossref, ORCID
Added: September 10, 2020
2006 chapter
UMN-MapServer: A High-Performance, Interoperable, and Open Source Web Mapping and Geo-spatial Analysis System
In Geographic Information Science (pp. 400–417).
TL;DR:
This paper presents a load balancing client/server Web-based spatial analysis system, UMN-MapServer, and evaluates its performance in a regional natural resource mapping and analysis (NRAMS) application which utilizes biweekly AVHRR imagery and several other raster and vector geo-spatial datasets.
(via Semantic Scholar)
Sources: Crossref, ORCID
Added: September 10, 2020
2004 chapter
Comparing Exact and Approximate Spatial Auto-regression Model Solutions for Spatial Data Analysis
In Geographic Information Science (pp. 140–161).
TL;DR:
Two candidate approximate-semi-sparse solutions of the SAR model based on Taylor series expansion and Chebyshev polynomials are presented, showing that these new techniques scale well for very large data sets, such as remote sensing images having millions of pixels.
(via Semantic Scholar)
Sources: Crossref, ORCID
Added: September 10, 2020
Employment
Updated: November 15th, 2019 12:47
2014 - present
North Carolina State University Raleigh, North Carolina, US
Associate Professor
Computer Science
Education
Updated: November 15th, 2019 12:49
1999 - 2008
University of Minnesota System Minneapolis, MN, US
Ph.D.
Computer Science
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