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Insect-Foundation: A Foundation Model and Large-scale 1M Dataset for Visual Insect Understanding
In precision agriculture, the detection and recognition of insects play an essential role in the ability of crops to grow healthy and produce a high-quality yield.
Quantum Vision Clustering
Unsupervised visual clustering has garnered significant attention in recent times, aiming to characterize distributions of unlabeled visual images through clustering based on a parameterized appearance approach.
Two-Dimensional Quantum Material Identification via Self-Attention and Soft-labeling in Deep Learning
In this work, we present a novel method to tackle the problem of missing annotation in instance segmentation in 2D quantum material identification.
OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptation
Unsupervised domain adaptation is one of the challenging problems in computer vision.
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