14 citations · 28 across the 7 of their papers we have counts for
7 papers
Finding Dino: A Plug-and-Play Framework for Zero-Shot Detection of Out-of-Distribution Objects Using Prototypes
Poulami Sinhamahapatra, Franziska Schwaiger, Shirsha Bose +3
Detecting and localising unknown or out-of-distribution (OOD) objects in any scene can be a challenging task in vision, particularly in safety-critical cases involving autonomous s…
Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypes
Poulami Sinhamahapatra, Suprosanna Shit, Anjany Sekuboyina +7
Vertebral fracture grading classifies the severity of vertebral fractures, which is a challenging task in medical imaging and has recently attracted Deep Learning (DL) models. Only…
Towards Human-Interpretable Prototypes for Visual Assessment of Image Classification Models
Poulami Sinhamahapatra, Lena Heidemann, Maureen Monnet +1
Explaining black-box Artificial Intelligence (AI) models is a cornerstone for trustworthy AI and a prerequisite for its use in safety critical applications such that AI models can…
Is it all a cluster game? -- Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space
Poulami Sinhamahapatra, Rajat Koner, Karsten Roscher +1
It is essential for safety-critical applications of deep neural networks to determine when new inputs are significantly different from the training distribution. In this paper, we…
Scenes and Surroundings: Scene Graph Generation using Relation Transformer
Rajat Koner, Poulami Sinhamahapatra, Volker Tresp
Identifying objects in an image and their mutual relationships as a scene graph leads to a deep understanding of image content. Despite the recent advancement in deep learning, the…
OODformer: Out-Of-Distribution Detection Transformer
Rajat Koner, Poulami Sinhamahapatra, Karsten Roscher +2
A serious problem in image classification is that a trained model might perform well for input data that originates from the same distribution as the data available for model train…
Relation Transformer Network
Rajat Koner, Suprosanna Shit, Volker Tresp
The extraction of a scene graph with objects as nodes and mutual relationships as edges is the basis for a deep understanding of image content. Despite recent advances, such as mes…