3 citations · 3 across the 8 of their papers we have counts for
8 papers
Text region detection in historical astronomical diagrams
Zeynep Sonat Baltacı, Raphaël Baena, Fei Meng +4
Text detection is a crucial task in the analysis of historical documents. While datasets and benchmarks exist for text detection in manuscripts and maps, the study of text in mathe…
PoM: A Linear-Time Replacement for Attention with the Polynomial Mixer
David Picard, Nicolas Dufour, Lucas Degeorge +14
This paper introduces the Polynomial Mixer (PoM), a novel token mixing mechanism with linear complexity that serves as a drop-in replacement for self-attention. PoM aggregates inpu…
Deep Sprite-based Image Models: An Analysis
Zeynep Sonat Baltacı, Romain Loiseau, Mathieu Aubry
While foundation models drive steady progress in image segmentation and diffusion algorithms compose always more realistic images, the seemingly simple problem of identifying recur…
Intrinsic Dimensionality as a Model-Free Measure of Class Imbalance
Çağrı Eser, Zeynep Sonat Baltacı, Emre Akbaş +1
Imbalance in classification tasks is commonly quantified by the cardinalities of examples across classes. This, however, disregards the presence of redundant examples and inherent…
Historical Printed Ornaments: Dataset and Tasks
Sayan Kumar Chaki, Zeynep Sonat Baltaci, Elliot Vincent +5
This paper aims to develop the study of historical printed ornaments with modern unsupervised computer vision. We highlight three complex tasks that are of critical interest to boo…
Generalized Mask-aware IoU for Anchor Assignment for Real-time Instance Segmentation
Barış Can Çam, Kemal Öksüz, Fehmi Kahraman +3
This paper introduces Generalized Mask-aware Intersection-over-Union (GmaIoU) as a new measure for positive-negative assignment of anchor boxes during training of instance segmenta…
Class Uncertainty: A Measure to Mitigate Class Imbalance
Z. S. Baltaci, K. Oksuz, S. Kuzucu +5
Class-wise characteristics of training examples affect the performance of deep classifiers. A well-studied example is when the number of training examples of classes follows a long…
Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation
Kemal Oksuz, Baris Can Cam, Fehmi Kahraman +3
This paper presents Mask-aware Intersection-over-Union (maIoU) for assigning anchor boxes as positives and negatives during training of instance segmentation methods. Unlike conven…