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2020 – today
- 2024
[j14]Harry Rogers
, Beatriz de la Iglesia, Tahmina Zebin, Grzegorz Cielniak, Ben Magri:
Advancing precision agriculture: domain-specific augmentations and robustness testing for convolutional neural networks in precision spraying evaluation. Neural Comput. Appl. 36(32): 20211-20229 (2024)- [c35]Violet Mayne, Harry Rogers, Saber Sami, Beatriz de la Iglesia:
Automating the Clock Drawing Test with Deep Learning and Saliency Maps. EPIA (2) 2024: 86-97 - [i2]Harry Rogers, Tahmina Zebin, Grzegorz Cielniak, Beatriz de la Iglesia, Ben Magri:
Deep Learning for Precision Agriculture: Post-Spraying Evaluation and Deposition Estimation. CoRR abs/2409.16213 (2024) - 2023
- [j13]Aliya Aleryani, Aaron Bostrom, Wenjia Wang, Beatriz de la Iglesia:
Multiple Imputation Ensembles for Time Series (MIE-TS). ACM Trans. Knowl. Discov. Data 17(3): 44:1-44:28 (2023) - [c34]Harry Rogers, Beatriz de la Iglesia, Tahmina Zebin, Grzegorz Cielniak, Ben Magri:
An Agricultural Precision Sprayer Deposit Identification System. CASE 2023: 1-6 - [c33]Harry Rogers, Beatriz de la Iglesia, Tahmina Zebin:
Evaluating the Use of Interpretable Quantized Convolutional Neural Networks for Resource-Constrained Deployment. KDIR 2023: 109-120 - [c32]Harry Rogers, Beatriz de la Iglesia, Tahmina Zebin, Grzegorz Cielniak, Ben Magri:
An Automated Precision Spraying Evaluation System. TAROS 2023: 26-37 - 2022
- [j12]Wedad Alahamade, Iain Lake, Claire E. Reeves, Beatriz de la Iglesia:
A multi-variate time series clustering approach based on intermediate fusion: A case study in air pollution data imputation. Neurocomputing 490: 229-245 (2022) - [j11]Tahani Alkhudaydi, Beatriz de la Iglesia:
Counting spikelets from infield wheat crop images using fully convolutional networks. Neural Comput. Appl. 34(20): 17539-17560 (2022) - [c31]Connor Pearson, Beatriz de la Iglesia, Saber Sami:
Detecting Cognitive Decline Using a Novel Doodle-Based Neural Network. MetroXRAINE 2022: 99-103 - [c30]Beatriz de la Iglesia, Kathapet Nawongs, Jack Dainty, Alexander MacGregor:
The Use of Clustering to Understand Disease Progression in Rheumatoid Arthritis. MetroXRAINE 2022: 444-448 - 2020
- [j10]Oduwa Edo-Osagie, Beatriz de la Iglesia, Iain Lake, Obaghe Edeghere:
A scoping review of the use of Twitter for public health research. Comput. Biol. Medicine 122: 103770 (2020) - [j9]Aliya Aleryani, Wenjia Wang, Beatriz de la Iglesia:
Multiple Imputation Ensembles (MIE) for Dealing with Missing Data. SN Comput. Sci. 1(3): 134 (2020) - [c29]Oduwa Edo-Osagie, Beatriz de la Iglesia, Iain Lake, Obaghe Edeghere:
An Evolutionary Approach to Automatic Keyword Selection for Twitter Data Analysis. HAIS 2020: 160-171 - [c28]Wedad Alahamade, Iain Lake, Claire E. Reeves, Beatriz de la Iglesia:
Clustering Imputation for Air Pollution Data. HAIS 2020: 585-597 - [c27]Benjamin Strickson, Beatriz de la Iglesia:
Legal Judgement Prediction for UK Courts. ICISS 2020: 204-209
2010 – 2019
- 2019
- [c26]Tahani Alkhudaydi, Ji Zhou, Beatriz de la Iglesia:
SpikeletFCN: Counting Spikelets from Infield Wheat Crop Images Using Fully Convolutional Networks. ICAISC (1) 2019: 3-13 - [c25]Oduwa Edo-Osagie, Beatriz de la Iglesia, Iain Lake, Obaghe Edeghere:
Deep Learning for Relevance Filtering in Syndromic Surveillance: A Case Study in Asthma/Difficulty Breathing. ICPRAM 2019: 491-500 - [c24]Oduwa Edo-Osagie, Iain Lake, Obaghe Edeghere, Beatriz de la Iglesia:
Attention-Based Recurrent Neural Networks (RNNs) for Short Text Classification: An Application in Public Health Monitoring. IWANN (1) 2019: 895-911 - 2018
- [c23]Aliya Aleryani, Wenjia Wang, Beatriz de la Iglesia:
Dealing with Missing Data and Uncertainty in the Context of Data Mining. HAIS 2018: 289-301 - 2017
- [j8]Aalaa Mojahed, Beatriz de la Iglesia:
An adaptive version of k-medoids to deal with the uncertainty in clustering heterogeneous data using an intermediary fusion approach. Knowl. Inf. Syst. 50(1): 27-52 (2017) - 2016
- [p1]Joao H. Bettencourt-Silva, Gurdeep S. Mannu, Beatriz de la Iglesia:
Visualisation of Integrated Patient-Centric Data as Pathways: Enhancing Electronic Medical Records in Clinical Practice. Machine Learning for Health Informatics 2016: 99-124 - 2015
- [c22]Aalaa Mojahed, Joao H. Bettencourt-Silva, Wenjia Wang, Beatriz de la Iglesia:
Applying Clustering Analysis to Heterogeneous Data Using Similarity Matrix Fusion (SMF). MLDM 2015: 251-265 - [i1]Tarek Amr Abdallah, Beatriz de la Iglesia:
Survey on Feature Selection. CoRR abs/1510.02892 (2015) - 2014
- [j7]Khaled Alotaibi, Victor J. Rayward-Smith, Beatriz de la Iglesia:
Nonmetric multidimensional scaling: A perturbation model for privacy-preserving data clustering. Stat. Anal. Data Min. 7(3): 175-193 (2014) - [c21]Tarek Amr Abdallah, Beatriz de la Iglesia:
URL-based Web Page Classification - A New Method for URL-based Web Page Classification Using n-Gram Language Models. KDIR 2014: 14-21 - [c20]Tarek Amr Abdallah, Beatriz de la Iglesia:
URL-Based Web Page Classification: With n-Gram Language Models. IC3K (Selected Papers) 2014: 19-33 - [c19]Aalaa Mojahed, Beatriz de la Iglesia:
A Fusion Approach to Computing Distance for Heterogeneous Data. KDIR 2014: 269-276 - [c18]Ghadah Aldehim, Beatriz de la Iglesia, Wenjia Wang:
Heuristic Ensemble of Filters for Reliable Feature Selection. ICPRAM 2014: 175-182 - 2013
- [j6]Jon Hills, Anthony J. Bagnall, Beatriz de la Iglesia, Graeme Richards:
BruteSuppression: a size reduction method for Apriori rule sets. J. Intell. Inf. Syst. 40(3): 431-454 (2013) - [j5]Beatriz de la Iglesia:
Evolutionary computation for feature selection in classification problems. WIREs Data Mining Knowl. Discov. 3(6): 381-407 (2013) - [c17]Oliver Kirkland, Beatriz de la Iglesia:
MOEA for clustering: comparison of mutation operators. GECCO (Companion) 2013: 91-92 - [c16]Oliver Kirkland, Beatriz de la Iglesia:
Experimental evaluation of cluster quality measures. UKCI 2013: 236-243 - 2012
- [c15]Khaled Alotaibi, Victor J. Rayward-Smith, Wenjia Wang, Beatriz de la Iglesia:
Non-linear Dimensionality Reduction for Privacy-Preserving Data Classification. SocialCom/PASSAT 2012: 694-701 - 2011
- [c14]Khaled Alotaibi, Victor J. Rayward-Smith, Beatriz de la Iglesia:
Non-metric Multidimensional Scaling for Privacy-Preserving Data Clustering. IDEAL 2011: 287-298 - [c13]Oliver Kirkland, Victor J. Rayward-Smith, Beatriz de la Iglesia:
A Novel Multi-Objective Genetic Algorithm for Clustering. IDEAL 2011: 317-326
2000 – 2009
- 2009
- [j4]Alan P. Reynolds, Beatriz de la Iglesia:
A multi-objective GRASP for partial classification. Soft Comput. 13(3): 227-243 (2009) - [c12]Alan P. Reynolds, David W. Corne, Beatriz de la Iglesia:
A multiobjective GRASP for rule selection. GECCO 2009: 643-650 - 2007
- [c11]Alan P. Reynolds, Beatriz de la Iglesia:
Managing Population Diversity Through the Use of Weighted Objectives and Modified Dominance: An Example from Data Mining. MCDM 2007: 99-106 - [c10]Alan P. Reynolds, Beatriz de la Iglesia:
Rule Induction for Classification Using Multi-objective Genetic Programming. EMO 2007: 516-530 - 2006
- [j3]Beatriz de la Iglesia, Graeme Richards, M. S. Philpott, Victor J. Rayward-Smith:
The application and effectiveness of a multi-objective metaheuristic algorithm for partial classification. Eur. J. Oper. Res. 169(3): 898-917 (2006) - [j2]Alan P. Reynolds, Graeme Richards, Beatriz de la Iglesia, Victor J. Rayward-Smith:
Clustering Rules: A Comparison of Partitioning and Hierarchical Clustering Algorithms. J. Math. Model. Algorithms 5(4): 475-504 (2006) - [c9]Fathi H. Saad, Beatriz de la Iglesia, Duncan G. Bell:
Effect of Document Representation on the Performance of Medical Document Classification. DMIN 2006: 83-89 - [c8]Fathi H. Saad, Beatriz de la Iglesia, Duncan G. Bell:
A Comparison of Two Document Clustering Approaches for Clustering Medical Documents. DMIN 2006: 425-431 - [c7]Alan P. Reynolds, Beatriz de la Iglesia:
Rule Induction Using Multi-Objective Metaheuristics: Encouraging Rule Diversity. IJCNN 2006: 3343-3350 - [c6]Fathi H. Saad, Beatriz de la Iglesia, Duncan G. Bell:
Comparison of Documents Classification Techniques to Classify Medical Reports. PAKDD 2006: 285-291 - 2005
- [c5]Hong Yan Yi, Beatriz de la Iglesia, Victor J. Rayward-Smith:
Using Concept Taxonomies for Effective Tree Induction. CIS (2) 2005: 1011-1016 - [c4]Beatriz de la Iglesia, Alan P. Reynolds, Victor J. Rayward-Smith:
Developments on a Multi-objective Metaheuristic (MOMH) Algorithm for Finding Interesting Sets of Classification Rules. EMO 2005: 826-840 - [r1]Graeme Richards, Beatriz de la Iglesia:
Discovery of Classification Rules from Databases. Encyclopedia of Information Science and Technology (II) 2005: 892-896 - 2003
- [c3]Beatriz de la Iglesia, M. S. Philpott, Anthony J. Bagnall, Victor J. Rayward-Smith:
Data mining rules using multi-objective evolutionary algorithms. IEEE Congress on Evolutionary Computation 2003: 1552-1559 - [c2]Alan P. Reynolds, Jo L. Dicks, Ian N. Roberts, Jan-Jaap Wesselink, Beatriz de la Iglesia, Vincent Robert, Teun Boekhout, Victor J. Rayward-Smith:
Algorithms for Identification Key Generation and Optimization with Application to Yeast Identification. EvoWorkshops 2003: 107-118 - 2002
- [j1]Jan-Jaap Wesselink, Beatriz de la Iglesia, Stephen A. James, Jo L. Dicks, Ian N. Roberts, Victor J. Rayward-Smith:
Determining a unique defining DNA sequence for yeast species using hashing techniques. Bioinform. 18(7): 1004-1010 (2002) - 2001
- [b1]Beatriz de la Iglesia:
The development and application of heuristic techniques for the data mining task of nugget discovery. University of East Anglia, UK, 2001
1990 – 1999
- 1996
- [c1]Beatriz de la Iglesia, Justin C. W. Debuse, Victor J. Rayward-Smith:
Discovering Knowledge in Commercial Databases Using Modern Heuristic Techniques. KDD 1996: 44-49
Coauthor Index
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