Results 31 to 40 of about 4,217 (208)
IEEE Transactions on Image Processing, 2018 Superpixel segmentation is becoming ubiquitous in computer vision. In practice, an object can either be represented by a number of segments in finer levels of detail or included in a surrounding region at coarser levels of detail, and thus a superpixel segmentation hierarchy is useful for applications that require different levels of image segmentation
Xing Wei 0001 +4 more
openaire +4 more sources
Tumor localization in tissue microarrays using rotation invariant superpixel pyramids [PDF]
, 2015 Tumor localization is an important component of histopathology image analysis; it has yet to be reliably automated for breast cancer histopathology. This paper investigates the use of superpixel classification to localize tumor regions.
Akbar, Shazia +7 more
core +1 more source
Video Segmentation with Superpixels [PDF]
, 2013 Due to its importance, video segmentation has regained interest recently. However, there is no common agreement about the necessary ingredients for best performance. This work contributes a thorough analysis of various within- and between-frame affinities suitable for video segmentation.
Fabio Galasso +2 more
openaire +3 more sources
A Survey of Weakly-supervised Image Semantic Segmentation Based on Image-level Labels
Taiyuan Ligong Daxue xuebao, 2021 According to the different ways of image-level label location inference, the weakly-supervised image semantic segmentation methods with image-level labels were divided into superpixel-based methods and classification-network-prior based methods.
Xinlin XIE +5 more
doaj +1 more source
ALFO: Adaptive Light Field Over-Segmentation
IEEE Access, 2021 Automatic image over-segmentation into superpixels has attracted increasing attention from researchers to apply it as a pre-processing step for several computer vision applications.
Maryam Hamad +3 more
doaj +1 more source
Interpretable CRAM‑Enhanced Lightweight Dual‑Branch CNN for Real‑Time Breast Cancer Histopathology in Internet‑of‑Medical‑Things Environments. [PDF]
SmallThis study presents an interpretable, lightweight hybrid deep learning model for real‐time analysis of breast cancer histopathology in IoMT‐enabled diagnostic systems. By integrating MobileNetV2 and EfficientNet‐B0 with a novel contextual recurrent attention module (CRAM), the framework achieves near‐perfect accuracy while providing transparent Grad ...
Ogundokun RO +4 more
europepmc +2 more sources
Resolution-Independent Meshes of Superpixels [PDF]
, 2019 The over-segmentation into superpixels is an important pre-processing step to smartly compress the input size and speed up higher level tasks. A superpixel was traditionally considered as a small cluster of square-based pixels that have similar color ...
Smith, P +3 more
core +1 more source
Remote Sensing, 2020 In this paper, superpixel features and extended multi-attribute profiles (EMAPs) are embedded in a multiple kernel learning framework to simultaneously exploit the local and multiscale information in both spatial and spectral dimensions for hyperspectral
Lei Pan, Chengxun He, Yang Xiang, Le Sun
doaj +1 more source
Remote Sensing, 2018 Superpixels, as a state-of-the-art segmentation paradigm, have recently been widely used in computer vision and pattern recognition. Despite the effectiveness of these algorithms, there are still many limitations and challenges dealing with Very High ...
Zeinab Gharibbafghi +2 more
doaj +1 more source
Iterative Boundaries Implicit Identification for Superpixels Segmentation: A Real-Time Approach
IEEE Access, 2021 Superpixel algorithms group visually coherent pixels and form an alternative representation of the regular structure of the pixel grid. This fundamental low-level computer vision preprocessing step greatly reduces the complexity of subsequent image ...
Serge Bobbia +5 more
doaj +1 more source