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A Rapid Test for Accuracy and Bias of Face Recognition Technology
Manuel Knott, Ignacio Serna, Ethan Mann +1
Measuring the accuracy of face recognition (FR) systems is essential for improving performance and ensuring responsible use. Accuracy is typically estimated using large annotated d…
Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce
Manuel Knott, Divinefavour Odion, Sameer Sontakke +2
Visual inspection for defect grading in agricultural supply chains is crucial but traditionally labor-intensive and error-prone. Automated computer vision methods typically require…
Social Perception of Faces in a Vision-Language Model
Carina I. Hausladen, Manuel Knott, Colin F. Camerer +1
We explore social perception of human faces in CLIP, a widely used open-source vision-language model. To this end, we compare the similarity in CLIP embeddings between different te…
A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification
Markus Marks, Manuel Knott, Neehar Kondapaneni +4
Self-supervised learning (SSL) is a machine learning approach where the data itself provides supervision, eliminating the need for external labels. The model is forced to learn abo…
Text-image Alignment for Diffusion-based Perception
Neehar Kondapaneni, Markus Marks, Manuel Knott +2
Diffusion models are generative models with impressive text-to-image synthesis capabilities and have spurred a new wave of creative methods for classical machine learning tasks. Ho…