@inproceedings{vu2018advent, title={ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation}, author={Vu, Tuan-Hung and Jain, Himalaya and Bucher, Maxime and Cord, ...

Abstract: Semantic segmentation is one of the fundamental tasks of pixel-level remote sensing image analysis. Currently, most high-performance semantic segmentation methods are trained in a supervised ...

Sustainable heritage management requires understanding visitors’ perceptions beyond technological approaches. This study integrates deep learning (DL), data mining, and spatial grid analysis to ...

Abstract: One-shot semantic segmentation poses the challenging task of segmenting object regions from unseen categories with only one annotated example as guidance. Thus, how to effectively construct ...

Visual perception is one of the core technologies for achieving unmanned and intelligent mining in underground mines. However, the harsh environment unique to underground mines poses significant ...

Segmentation and classification are fundamental tasks in image processing and computer vision. In addition to having ubiquitous applications in a variety of different fields, segmentation and ...

SOLO is a flexible framework for instance segmentation that categorises each pixel based on its location and size. Introduced by researchers from The University of Adelaide and ByteDance AI Lab, SOLO ...

Various pre-trained deep learning models for the segmentation of bioimages have been made available as developer-to-end-user solutions. They are optimized for ease of use and usually require neither ...

1 Oceanography Department, Geoscience Institute of the Federal University of Bahia (UFBA), Salvador, Brazil. 2 Earth and Environmental Physics Department, Physics Institute of the Federal University ...

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