activity
20162025
most citedDeep Convolutional Neural Network Ensembles using ECOC

8 citations · 8 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2025

Pub-Guard-LLM: Detecting Retracted Biomedical Articles with Reliable Explanations

Lihu Chen, Shuojie Fu, Gabriel Freedman +6

A significant and growing number of published scientific articles is found to involve fraudulent practices, posing a serious threat to the credibility and safety of research in fie…

cs.LG2021

A unifying approach on bias and variance analysis for classification

Cemre Zor, Terry Windeatt

Standard bias and variance (B&V) terminologies were originally defined for the regression setting and their extensions to classification have led to several different models / defi…

cs.LG2020★ 8 cited

Deep Convolutional Neural Network Ensembles using ECOC

Sara Atito Ali Ahmed, Cemre Zor, Berrin Yanikoglu +2

Deep neural networks have enhanced the performance of decision making systems in many applications including image understanding, and further gains can be achieved by constructing…

q-bio.NC2019

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology

Neil P. Oxtoby, Fabio S. Ferreira, Agoston Mihalik +12

We predicted residual fluid intelligence scores from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions acr…

q-bio.NC2019

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression

Agoston Mihalik, Mikael Brudfors, Maria Robu +12

We applied several regression and deep learning methods to predict fluid intelligence scores from T1-weighted MRI scans as part of the ABCD Neurocognitive Prediction Challenge (ABC…

cs.LG2016

Delta divergence: A novel decision cognizant measure of classifier incongruence

Josef Kittler, Cemre Zor

Disagreement between two classifiers regarding the class membership of an observation in pattern recognition can be indicative of an anomaly and its nuance. As in general classifie…