1 code implementation • 29 Apr 2024 • Alexis Guichemerre, Soufiane Belharbi, Tsiry Mayet, Shakeeb Murtaza, Pourya Shamsolmoali, Luke McCaffrey, Eric Granger
A WSOL model initially trained on some labeled source image data can be adapted using unlabeled target data in cases of significant domain shifts caused by variations in staining, scanners, and cancer type.
1 code implementation • 16 Mar 2023 • Soufiane Belharbi, Shakeeb Murtaza, Marco Pedersoli, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
This paper proposes a novel CAM method for WSVOL that exploits spatiotemporal information in activation maps during training without constraining an object's position.
1 code implementation • 30 Aug 2022 • Soufiane Belharbi, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
Our proposed TCAM method achieves a new state-of-art in WSVOL accuracy, and visual results suggest that it can be adapted for subsequent tasks like visual object tracking and detection.
1 code implementation • 12 May 2022 • Soufiane Belharbi, Jérôme Rony, Jose Dolz, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
Our method is composed of two networks: a localizer that yields segmentation mask, followed by a classifier.
1 code implementation • 7 Jan 2022 • Soufiane Belharbi, Marco Pedersoli, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
The CNN is exploited to collect both positive and negative evidence at the pixel level to train the decoder.
1 code implementation • 15 Sep 2021 • Soufiane Belharbi, Aydin Sarraf, Marco Pedersoli, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
Interpolation is required to restore full size CAMs, yet it does not consider the statistical properties of objects, such as color and texture, leading to activations with inconsistent boundaries, and inaccurate localizations.
2 code implementations • 14 Nov 2020 • Soufiane Belharbi, Jérôme Rony, Jose Dolz, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
We propose novel regularization terms, which enable the model to seek both non-discriminative and discriminative regions, while discouraging unbalanced segmentations.
1 code implementation • 10 Oct 2020 • Soufiane Belharbi, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
CNN visualization and interpretation methods, like class-activation maps (CAMs), are typically used to highlight the image regions linked to class predictions.
1 code implementation • 25 Nov 2019 • Soufiane Belharbi, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
We propose a new constrained-optimization formulation for deep ordinal classification, in which uni-modality of the label distribution is enforced implicitly via a set of inequality constraints over all the pairs of adjacent labels.
Ranked #1 on Historical Color Image Dating on HCI (MAE metric)
1 code implementation • 8 Sep 2019 • Jérôme Rony, Soufiane Belharbi, Jose Dolz, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
Four key challenges are identified for the application of deep WSOL methods in histology -- under/over activation of CAMs, sensitivity to thresholding, and model selection.
1 code implementation • 25 Jul 2019 • Soufiane Belharbi, Jérôme Rony, Jose Dolz, Ismail Ben Ayed, Luke McCaffrey, Eric Granger
Pointwise localization allows more precise localization and accurate interpretability, compared to bounding box, in applications where objects are highly unstructured such as in medical domain.