Zobrazeno 1 - 10
of 127
pro vyhledávání: '"Frintrop, Simone"'
We propose an approach for Open-World Instance Segmentation (OWIS), a task that aims to segment arbitrary unknown objects in images by generalizing from a limited set of annotated object classes during training. Our Segment Object System (SOS) explic
Externí odkaz:
http://arxiv.org/abs/2409.14627
Visual inspection, or industrial anomaly detection, is one of the most common quality control types in manufacturing. The task is to identify the presence of an anomaly given an image, e.g., a missing component on an image of a circuit board, for sub
Externí odkaz:
http://arxiv.org/abs/2408.15113
Autor:
Kelm, André, Hannemann, Niels, Heberle, Bruno, Schmidt, Lucas, Rolff, Tim, Wilms, Christian, Yaghoubi, Ehsan, Frintrop, Simone
This study introduces a novel expert generation method that dynamically reduces task and computational complexity without compromising predictive performance. It is based on a new hierarchical classification network topology that combines sequential
Externí odkaz:
http://arxiv.org/abs/2403.05601
Crop detection is integral for precision agriculture applications such as automated yield estimation or fruit picking. However, crop detection, e.g., apple detection in orchard environments remains challenging due to a lack of large-scale datasets an
Externí odkaz:
http://arxiv.org/abs/2311.05029
Autor:
Kelm, André Peter, Hannemann, Niels, Heberle, Bruno, Schmidt, Lucas, Rolff, Tim, Wilms, Christian, Yaghoubi, Ehsan, Frintrop, Simone
This paper introduces a novel network topology that seamlessly integrates dynamic inference cost with a top-down attention mechanism, addressing two significant gaps in traditional deep learning models. Drawing inspiration from human perception, we c
Externí odkaz:
http://arxiv.org/abs/2308.05128
Traffic light detection is a challenging problem in the context of self-driving cars and driver assistance systems. While most existing systems produce good results on large traffic lights, detecting small and tiny ones is often overlooked. A key pro
Externí odkaz:
http://arxiv.org/abs/2307.15191
This paper introduces an audio-visual speech enhancement system that leverages score-based generative models, also known as diffusion models, conditioned on visual information. In particular, we exploit audio-visual embeddings obtained from a self-su
Externí odkaz:
http://arxiv.org/abs/2306.01432
We investigate cross-quality knowledge distillation (CQKD), a knowledge distillation method where knowledge from a teacher network trained with full-resolution images is transferred to a student network that takes as input low-resolution images. As i
Externí odkaz:
http://arxiv.org/abs/2304.07593
Autor:
Li, Ke, Rolff, Tim, Schmidt, Susanne, Bacher, Reinhard, Frintrop, Simone, Leemans, Wim, Steinicke, Frank
Neural radiance field (NeRF), in particular its extension by instant neural graphics primitives, is a novel rendering method for view synthesis that uses real-world images to build photo-realistic immersive virtual scenes. Despite its potential, rese
Externí odkaz:
http://arxiv.org/abs/2211.13494
Autor:
Frintrop, Simone.
Thesis (Ph.D.)--University of Bonn, Germany.
Includes bibliographical references and index. Also available in print.
Includes bibliographical references and index. Also available in print.