Results 51 to 60 of about 3,740 (194)

Superpixel-based statistical anomaly detection for sense and avoid [PDF]

, 2016
This paper presents a novel preprocessing method for detecting small objects of interest within a high-resolution image, applied to the problem of visually detecting possible aircraft collisions (Sense and Avoid) for UAV platforms. The method is based on
Achim, Alin M, Bull, David, Pappas, Odysseas A   +2 more
core   +2 more sources

DeepCount: In-Field Automatic Quantification of Wheat Spikes Using Simple Linear Iterative Clustering and Deep Convolutional Neural Networks

Frontiers in Plant Science, 2019
Crop yield is an essential measure for breeders, researchers, and farmers and is composed of and may be calculated by the number of ears per square meter, grains per ear, and thousand grain weight. Manual wheat ear counting, required in breeding programs
Pouria Sadeghi-Tehran, N. Virlet, E. Ampe, P. Reyns, M. Hawkesford   +4 more
semanticscholar   +1 more source

Scalable Simple Linear Iterative Clustering (SSLIC) Using a Generic and Parallel Approach [PDF]

The insight journal, 2018
Superpixel algorithms have proven to be a useful initial step for segmentation and subsequent processing of images, reducing computational complexity by replacing the use of expensive per-pixel primitives with a higher-level abstraction, superpixels ...
Bradley C. Lowekamp, David T. Chen, Z. Yaniv, T. Yoo   +3 more
semanticscholar   +1 more source

Unsupervised Classification for Polarimetric Synthetic Aperture Radar Images Based on Wishart Mixture Models

Leida xuebao, 2017
Unsupervised classification is a significant step inthe automated interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, determining the number of clusters in this process is still a challenging problem. To this end, we propose
Zhong Neng, Yang Wen, Yang Xiangli, Guo Wei   +3 more
doaj   +1 more source

SLIC Based Digital Image Enlargement

, 2018
Low resolution image enhancement is a classical computer vision problem. Selecting the best method to reconstruct an image to a higher resolution with the limited data available in the low-resolution image is quite a challenge.
Amara, M. Z. F., Bandara, R., Silva, Thushari   +2 more
core   +1 more source

Superpixel segmentation based on anisotropic edge strength [PDF]

, 2019
Superpixel segmentation can benefit from the use of an appropriate method to measure edge strength. In this paper, we present such a method based on the first derivative of anisotropic Gaussian kernels.
De Baets, Bernard, WANG, Gang
core   +1 more source

Superpixels: An Evaluation of the State-of-the-Art

, 2017
Superpixels group perceptually similar pixels to create visually meaningful entities while heavily reducing the number of primitives for subsequent processing steps.
Hermans, Alexander, Leibe, Bastian, Stutz, David   +2 more
core   +1 more source

Purifying SLIC Superpixels to Optimize Superpixel-Based Classification of High Spatial Resolution Remote Sensing Image

Remote Sensing, 2019
Fast and accurate classification of high spatial resolution remote sensing image is important for many applications. The usage of superpixels in classification has been proposed to accelerate the speed of classification.
Hengjian Tong, Fei Tong, Wei Zhou, Yun Zhang   +3 more
doaj   +1 more source

Unsupervised Image Segmentation using the Deffuant-Weisbuch Model from Social Dynamics

, 2016
Unsupervised image segmentation algorithms aim at identifying disjoint homogeneous regions in an image, and have been subject to considerable attention in the machine vision community.
Kayal, Subhradeep
core   +1 more source

SMURFS: superpixels from multi-scale refinement of super-regions [PDF]

, 2016
Recent applications in computer vision have come to rely on superpixel segmentation as a pre-processing step for higher level vision tasks, such as object recognition, scene labelling or image segmentation.
Basham, Mark, French, Andrew P., Luengo, Imanol   +2 more
core   +1 more source