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Content‐Based Image Retrieval and Feature Extraction: A Comprehensive Review
Multimedia content analysis is applied in different real‐world computer vision applications,
and digital images constitute a major part of multimedia data. In last few years, the …
and digital images constitute a major part of multimedia data. In last few years, the …
From BoW to CNN: Two decades of texture representation for texture classification
Texture is a fundamental characteristic of many types of images, and texture representation
is one of the essential and challenging problems in computer vision and pattern recognition …
is one of the essential and challenging problems in computer vision and pattern recognition …
Retracted: Face recognition attendance system based on real-time video processing
H Yang, X Han - IEEE Access, 2020 - ieeexplore.ieee.org
With the advent of the era of big data in the world and the commercial value of face
recognition technology, the prospects for face recognition technology are very bright and …
recognition technology, the prospects for face recognition technology are very bright and …
A comprehensive database for benchmarking imaging systems
Cross-modality face recognition is an emerging topic due to the wide-spread usage of
different sensors in day-to-day life applications. The development of face recognition …
different sensors in day-to-day life applications. The development of face recognition …
Study of statistical methods for texture analysis and their modern evolutions
Texture analysis is widely performed in the current time as it is considered as an intimate
property of the surface. It is widely used in the field of image processing, remote sensing …
property of the surface. It is widely used in the field of image processing, remote sensing …
A novel key-frames selection framework for comprehensive video summarization
Video summarization (VSUMM) has become a popular method in processing massive video
data. The key point of VSUMM is to select the key frames to represent the effective contents …
data. The key point of VSUMM is to select the key frames to represent the effective contents …
Weakly supervised tracklet association learning with video labels for person re-identification
Supervised person re-identification (re-id) methods require expensive manual labeling
costs. Although unsupervised re-id methods can reduce the requirement of the labeled …
costs. Although unsupervised re-id methods can reduce the requirement of the labeled …
Uniformface: Learning deep equidistributed representation for face recognition
In this paper, we propose a new supervision objective named uniform loss to learn deep
equidistributed representations for face recognition. Most existing methods aim to learn …
equidistributed representations for face recognition. Most existing methods aim to learn …
SpaSSA: Superpixelwise adaptive SSA for unsupervised spatial–spectral feature extraction in hyperspectral image
Singular spectral analysis (SSA) has recently been successfully applied to feature extraction
in hyperspectral image (HSI), including conventional (1-D) SSA in spectral domain and 2-D …
in hyperspectral image (HSI), including conventional (1-D) SSA in spectral domain and 2-D …
Local feature descriptor for image matching: A survey
Image registration is an important technique in many computer vision applications such as
image fusion, image retrieval, object tracking, face recognition, change detection and so on …
image fusion, image retrieval, object tracking, face recognition, change detection and so on …