Zoekresultaten

Uncovering bias in the PlantVillage dataset.

Machine Vision and Social Media Images: Why Hashtags Matter

Studying images in social media poses specific methodological challenges, which in turn have directed scholarly attention toward the computational interpretation of visual data. When analyzing large numbers of images, both traditional content analysis as well as cultural analytics have proven valuable. However, these techniques do not take into account the contextualization of images within a socio-technical environment. As the meaning of social media images is co-created by online publics, bound through networked practices, these visuals should be analyzed on the level of their networked contextualization. Although machine vision is increasingly adept at recognizing faces and features, its performance in grasping the meaning of social media images remains limited. Combining automated analyses of images with platform data opens up the possibility to study images in the context of their resonance within and across online discursive spaces. This article explores the capacities of hashtags and retweet counts to complement the automated assessment of social media images, doing justice to both the visual elements of an image and the contextual elements encoded through the hashtag practices of networked publics.

MIMU PDR with bias estimation using an optimization-based approach.

Traditional IMU based PDR systems suffer from rapidly growing drift effects due to the inherent bias of the inertial sensor. Many existing solutions to mitigate this problem use aiding sensors or information as heuristics or map data. We propose a new optimization framework to solve the PDR estimation problem where the sensors biases are explicitly included as state variables and therefore be used to correct for bias effects in the PDR. By using a smoothing approach and exploiting the rigid structure of a MIMU array one can solve for the slowly varying sensor biases. This paper presents the method and gives an exemplary result of a walking trial. Good agreements in the position and orientation with an optical reference system were found. Moreover, accelerometer and gyroscope biases could be estimated accordingly. Further research includes the performance of more experiments under various conditions such that a more quantitative evaluation can be obtained. In addition, an exploration of a (pseudo) realtime filter version would be valuable such that the system can be applied online.

The duration of automation bias in a realistic setting

Whereas in most studies conducted previously the effect of automation bias has been investigated in terms of an instantaneous decision, this study is aimed at quantifying its duration.

Uncovering Bias in ASR Systems

It is crucial that ASR systems can handle the wide range of variations in speech of speakers from different demographic groups, with different speaking styles, and of speakers with (dis)abilities. A potential quality-of-service harm arises when ASR systems do not perform equally well for everyone. ASR systems may exhibit bias against certain types of speech, such as non-native accents, different age groups and gender. In this study, we evaluate two widely-used neural network-based architectures: Wav2vec2 and Whisper on potential biases for Dutch speakers. We used the Dutch speech corpus JASMIN as a test set containing read and conversational speech in a human-machine interaction setting. The results reveal a significant bias against non-natives, children and elderly and some regional dialects. The ASR systems generally perform slightly better for women than for men.

Managerial vision bias and cooperative governance

What causes firms to behave the way they do when they face different investment opportunities? We argue that both people and processes are behind the decision-making of project implementation. Member and professional CEOs of cooperatives differ regarding their managerial vision towards upstream and downstream projects. Cooperatives with member CEOs are upstream focused and it is reflected by the cascading effect of negative vision bias towards downstream projects. When downstream activities become more important, cooperatives need to replace the member CEOs with professional CEOs. However, a cooperative with a professional CEO may still be in a disadvantageous position if the member-dominated Board of Directors' negative bias towards downstream projects is too strong, which may result in an investor owned firm being the efficient governance structure.