Zobrazeno 1 - 10
of 505
pro vyhledávání: '"Feature Descriptors"'
Publikováno v:
INCAS Bulletin, Vol 16, Iss 3, Pp 3-18 (2024)
The present paper aims to conduct an experiment that compares different methods of detecting objects in images. Programs were developed to evaluate the efficiency of SURF, BRISK, MSER, and ORB object detection methods. Four static gray images with su
Externí odkaz:
https://doaj.org/article/bb13a7d6226543b38466ee8054809ae1
Publikováno v:
In Expert Systems With Applications 1 April 2025 267
Publikováno v:
In Acta Physico-Chimica Sinica February 2025 41(2)
Publikováno v:
International Journal of Cognitive Computing in Engineering, Vol 5, Iss , Pp 398-405 (2024)
Accurately classifying petrol and diesel fuel using an image processing method is crucial for fuel-related industries such as petrol pumps, refineries, and fuel storage facilities. However, distinguishing between these fuels using traditional methods
Externí odkaz:
https://doaj.org/article/2fc60b923d49494ca420007ae7942c15
Publikováno v:
Geodesy and Cartography, Vol 50, Iss 1 (2024)
This research seeks to assess the effect of different selected feature descriptors on the accuracy of an automatic image registration scheme. Three different feature descriptors were selected based on their peculiar characteristics, and implemented i
Externí odkaz:
https://doaj.org/article/02a258108b69463ea3cbe8fbe0101afb
Autor:
Shuting Chen, Yanfei Su, Baiqi Lai, Luwei Cai, Chengxi Hong, Li Li, Xiuliang Qiu, Hong Jia, Weiquan Liu
Publikováno v:
Remote Sensing, Vol 16, Iss 13, p 2493 (2024)
The cross-dimensional matching of 2D images and 3D point clouds is an effective method by which to establish the spatial relationship between 2D and 3D space, which has potential applications in remote sensing and artificial intelligence (AI). In thi
Externí odkaz:
https://doaj.org/article/defff0a05fd8420ca0293da909b213e0
Publikováno v:
Future Internet, Vol 16, Iss 5, p 174 (2024)
The problem of data enrichment to train visual SLAM and VO construction models using deep learning (DL) is an urgent problem today in computer vision. DL requires a large amount of data to train a model, and more data with many different contextual a
Externí odkaz:
https://doaj.org/article/4136df363b94474793667992fc753fa9
Publikováno v:
IEEE Access, Vol 11, Pp 44221-44233 (2023)
In recent years, pose-invariant face recognition has been mainly approached from a holistic insight. DCNNs (ArcFace, Elastic Face, FaceNet) are used to compute a face image embedding, which is used later to perform face recognition. This paper presen
Externí odkaz:
https://doaj.org/article/98dd9c193d0b48b68fcceb779add5110
Publikováno v:
IEEE Access, Vol 11, Pp 19725-19740 (2023)
RFD-like binary descriptors have been designed to be fast and demonstrate good quality in image-matching tasks. One of those descriptors, RFDoc, produces state-of-the art results when applied to document localization systems. However, the computation
Externí odkaz:
https://doaj.org/article/c66e95177c49447091c5acd069db1acc
Publikováno v:
IEEE Access, Vol 11, Pp 1104-1114 (2023)
In this paper, we propose a data-driven approach to training a memory-efficient local feature descriptor for identity documents location and classification on mobile and embedded devices. The proposed algorithm for retrieving a dataset of patches is
Externí odkaz:
https://doaj.org/article/7507a8d6f7e94ee08491c836670c1263