Our study introduces a novel, low-cost, and reproducible framework for
real-time, object-level structural assessment and geolocation of roadside
vegetation and infrastructure with commonly available but underutilized
dashboard camera (dashcam) vide... read more
Cross-subject electroencephalography (EEG) decoding remains a fundamental
challenge in brain-computer interface (BCI) research due to substantial
inter-subject variability and the scarcity of subject-invariant
representations. This paper proposed P... read more
Grasping is a fundamental task in robot-assisted surgery (RAS), and
automating it can reduce surgeon workload while enhancing efficiency, safety,
and consistency beyond teleoperated systems. Most prior approaches rely on
explicit object pose tracki... read more
Image segmentation is an important and widely performed task in computer
vision. Accomplishing effective image segmentation in diverse settings often
requires custom model architectures and loss functions. A set of models that
specialize in segment... read more
Deep neural networks have become the go-to method for biomedical instance
segmentation. Generalist models like Cellpose demonstrate state-of-the-art
performance across diverse cellular data, though their effectiveness often
degrades on domains that... read more
Effective and efficient agricultural manipulation and harvesting depend on
accurately understanding the current state of the grasp. The agricultural
environment presents unique challenges due to its complexity, clutter, and
occlusion. Additionally,... read more
Cognitive science and neuroscience have long faced the challenge of
disentangling representations of language from representations of conceptual
meaning. As the same problem arises in today's language models (LMs), we
investigate the relationship b... read more
Historical handwritten text recognition (HTR) is essential for unlocking the
cultural and scholarly value of archival documents, yet digitization is often
hindered by scarce transcriptions, linguistic variation, and highly diverse
handwriting style... read more
We introduce G-CUT3R, a novel feed-forward approach for guided 3D scene
reconstruction that enhances the CUT3R model by integrating prior information.
Unlike existing feed-forward methods that rely solely on input images, our
method leverages auxil... read more
Accurate and scalable cancer diagnosis remains a critical challenge in modern
pathology, particularly for malignancies such as breast, prostate, bone, and
cervical, which exhibit complex histological variability. In this study, we
propose a transfo... read more
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