… a Deep Learning (DL) model to detect unconscious bias in … Lexical based systems and
traditional machine learning … learning to deal with the small set of labelled data and detect …

… a Deep Learning (DL) model to detect unconscious bias in … Lexical based systems and
traditional machine learning … learning to deal with the small set of labelled data and detect …

… considerations in the development and deployment of deep learning models. It highlights
the … [31] discuss deep learning for bias detection and its deployment. Cha et al. [32] analyze …

… We start this section with a short recapitulation of the fundamentals of … This is particularly
worrisome considering recent reports of Russia deploying tools that detect people’s ethnicity [61…

… or amplify biases introduced in the many steps from model inception to deployment, resulting
in a … This type of bias occurs when machine learning models are used to generate inputs for …

… bias (eg, gender, race, age, disability, elitism and religion) across their various functions…
We propose a deep learning model with a transfer learning based language model to learn …

… the bias … testing accuracy was significantly worse for ResNet-50 compared to all other
models. As a module for Google Net, Inception v3 began as a CNN for aiding with object detection …

… In order to avoid bias in our pre-trained models, the data was … inception V3 but it requires
large memory space for the mobile … We deployed the model on mobile phone with capability to …

… To reduce the deployment and maintenance costs, while improving the safety and … detection
based on deep learning has become a research hotspot. A zero bias anomaly detection …

… challenges encountered in deploying deep learning models in … treatment initiation. For
instance, in the case of cancer, early … Deep learning models trained on biased or unrepresentative …