activity
20142024
most citedRegularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning

546 citations · 740 across the 23 of their papers we have counts for

collaborators

26 papers

cs.CV2024★ 1 cited

Joint Audio-Visual Idling Vehicle Detection with Streamlined Input Dependencies

Xiwen Li, Rehman Mohammed, Tristalee Mangin +4

Idling vehicle detection (IVD) can be helpful in monitoring and reducing unnecessary idling and can be integrated into real-time systems to address the resulting pollution and harm…

cs.CV2023★ 1 cited

Analyzing the Domain Shift Immunity of Deep Homography Estimation

Mingzhen Shao, Tolga Tasdizen, Sarang Joshi

Homography estimation serves as a fundamental technique for image alignment in a wide array of applications. The advent of convolutional neural networks has introduced learning-bas…

cs.CV2022

Localization supervision of chest x-ray classifiers using label-specific eye-tracking annotation

Ricardo Bigolin Lanfredi, Joyce D. Schroeder, Tolga Tasdizen

Convolutional neural networks (CNNs) have been successfully applied to chest x-ray (CXR) images. Moreover, annotated bounding boxes have been shown to improve the interpretability…

cs.CV2022

Stain Based Contrastive Co-training for Histopathological Image Analysis

Bodong Zhang, Beatrice Knudsen, Deepika Sirohi +2

We propose a novel semi-supervised learning approach for classification of histopathology images. We employ strong supervision with patch-level annotations combined with a novel co…

cs.LG2022

Adversarially Robust Classification by Conditional Generative Model Inversion

Mitra Alirezaei, Tolga Tasdizen

Most adversarial attack defense methods rely on obfuscating gradients. These methods are successful in defending against gradient-based attacks; however, they are easily circumvent…

cs.CV2021★ 3 cited

Comparing radiologists' gaze and saliency maps generated by interpretability methods for chest x-rays

Ricardo Bigolin Lanfredi, Ambuj Arora, Trafton Drew +2

The interpretability of medical image analysis models is considered a key research field. We use a dataset of eye-tracking data from five radiologists to compare the outputs of int…