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∙ 09/15/2023

Biased Attention: Do Vision Transformers Amplify Gender Bias More than Convolutional Neural Networks?

Deep neural networks used in computer vision have been shown to exhibit ...

0 Abhishek Mandal, et al. ∙

∙ 09/10/2023

Gender Bias in Multimodal Models: A Transnational Feminist Approach Considering Geographical Region and Culture

Deep learning based visual-linguistic multimodal models such as Contrast...

0 Abhishek Mandal, et al. ∙

∙ 05/17/2023

An Ensemble Deep Learning Approach for COVID-19 Severity Prediction Using Chest CT Scans

Chest X-rays have been widely used for COVID-19 screening; however, 3D c...

0 Sidra Aleem, et al. ∙

∙ 04/26/2023

Multimodal Composite Association Score: Measuring Gender Bias in Generative Multimodal Models

Generative multimodal models based on diffusion models have seen tremend...

0 Abhishek Mandal, et al. ∙

∙ 04/22/2023

Constructing a meta-learner for unsupervised anomaly detection

Unsupervised anomaly detection (AD) is critical for a wide range of prac...

0 Małgorzata Gutowska, et al. ∙

∙ 10/03/2022

Random Data Augmentation based Enhancement: A Generalized Enhancement Approach for Medical Datasets

Over the years, the paradigm of medical image analysis has shifted from ...

10 Sidra Aleem, et al. ∙

∙ 09/08/2021

TrollsWithOpinion: A Dataset for Predicting Domain-specific Opinion Manipulation in Troll Memes

Research into the classification of Image with Text (IWT) troll memes ha...

2 Shardul Suryawanshi, et al. ∙

∙ 07/31/2020

Utilising Visual Attention Cues for Vehicle Detection and Tracking

Advanced Driver-Assistance Systems (ADAS) have been attracting attention...

1 Feiyan Hu, et al. ∙

∙ 05/14/2020

ECIR 2020 Workshops: Assessing the Impact of Going Online

ECIR 2020 https://ecir2020.org/ was one of the many conferences affected...

0 Sérgio Nunes, et al. ∙

∙ 10/25/2019

MediaEval 2019: Concealed FGSM Perturbations for Privacy Preservation

This work tackles the Pixel Privacy task put forth by MediaEval 2019. Ou...

0 Panagiotis Linardos, et al. ∙

∙ 11/15/2017

People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting

In this paper we propose a technique to adapt a convolutional neural net...

0 Mark Marsden, et al. ∙

∙ 05/30/2017

ResnetCrowd: A Residual Deep Learning Architecture for Crowd Counting, Violent Behaviour Detection and Crowd Density Level Classification

In this paper we propose ResnetCrowd, a deep residual architecture for s...

1 Mark Marsden, et al. ∙

∙ 12/01/2016

Fully Convolutional Crowd Counting On Highly Congested Scenes

In this paper we advance the state-of-the-art for crowd counting in high...

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