37 citations · 40 across the 8 of their papers we have counts for
5 papers · 1 filter
Towards Creativity Characterization of Generative Models via Group-based Subset Scanning
Celia Cintas, Payel Das, Brian Quanz +3
Deep generative models, such as Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs), have been employed widely in computational creativity research. However,…
Out-of-Distribution Detection in Dermatology using Input Perturbation and Subset Scanning
Hannah Kim, Girmaw Abebe Tadesse, Celia Cintas +2
Recent advances in deep learning have led to breakthroughs in the development of automated skin disease classification. As we observe an increasing interest in these models in the…
Pattern Detection in the Activation Space for Identifying Synthesized Content
Celia Cintas, Skyler Speakman, Girmaw Abebe Tadesse +3
Generative Adversarial Networks (GANs) have recently achieved unprecedented success in photo-realistic image synthesis from low-dimensional random noise. The ability to synthesize…
Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets
Newton M. Kinyanjui, Timothy Odonga, Celia Cintas +4
Recent advances in computer vision and deep learning have led to breakthroughs in the development of automated skin image analysis. In particular, skin cancer classification models…
Smooth Grad-CAM++: An Enhanced Inference Level Visualization Technique for Deep Convolutional Neural Network Models
Daniel Omeiza, Skyler Speakman, Celia Cintas +1
Gaining insight into how deep convolutional neural network models perform image classification and how to explain their outputs have been a concern to computer vision researchers a…