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frame semantic parsing copy move forgery Explore More

Frame Identification sentence examples within frame semantic parsing

frame semantic parsing 10.18653/v1/2021.acl-long.407

Frame Identification (FI) is a fundamental and challenging task in frame semantic parsing.

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frame semantic parsing 10.18653/v1/2021.findings-acl.227

Current researches on frame semantic parsing include three subtasks, namely frame identification, argument identification and role classification.

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Frame Identification sentence examples within copy move forgery

copy move forgery 10.1007/S12652-021-03386-4

In the past decades, although machine intelligence has been widely adopted to detect the forgery in digital images automatically, It still remains a very challenging detection task for carefully-crafted copy-move forgery in digital video for three reasons: (i) A video of medium length containing hundreds of frames already incurs a prohibitive computational cost; (ii) Similar backgrounds in contiguous frames are easily mistakenly detected as copy-move forgery regions, resulting to a large number of false alarms; (iii) Most state-of-the-art methods cannot detect video copy-move inter-frame or intra-frame forgeries; To effectively address these issues, a fast forgery frame detection method for video copy-move inter/intra-frame identification is proposed: (i) The sparse feature extraction and matching speed-up the algorithm processing and reduce the time cost greatly (Defect (i)); (ii) The adaptive two-pass filtering and copy-move frame-pair matching can address the similarity problem (Defect (ii)) to locate truly forgery frame-pairs (FFP); (iii) Based on the results of these FFP, the type of video copy-move forgery detection can be identified (Defect (iii)).

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Frame Identification sentence examples within Key Frame Identification

Key Frame Identification 10.1016/J.MATPR.2020.10.241

The first step proposes and uses a key frame identification algorithm to extract a set of optimal frames.

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Key Frame Identification 10.1109/TPAMI.2018.2866114

With the video imprint representation, it is convenient to reverse map back to both temporal and spatial locations in video frames, allowing for both key frame identification and key areas localization within each frame.

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Namely Frame Identification 10.18653/v1/2021.findings-acl.227

Current researches on frame semantic parsing include three subtasks, namely frame identification, argument identification and role classification.

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Namely Frame Identification 10.26615/978-954-452-056-4_109

This work explores how structural information from these lexical resources can lead to gains in a downstream task, namely frame identification.

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10.1016/J.IMU.2021.100517

Different from the previous studies, this study proposes novel methods which does not require any image segmentation to perform simultaneously key-frame identification and LAV estimation.

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Keywords related to Identification

Facilitate Identification Wireless Identification Phenotype Identification Materials Identification Ligand Identification Mimo Identification Service Identification Remote Identification Isomer Identification Mci Identification Gland Identification Stiffness Identification Material Identification Parametric Identification Pattern Identification Screening Identification Task Identification Numerical Identification Organizational Identification Timely Identification Camera Identification Correct Identification Vessel Identification Rna Identification Fracture Identification Biomarkers Identification Children Identification Part Identification Qtl Identification Structures Identification Blind Identification Function Identification Nonparametric Identification Voice Identification Employee Customer Identification Boundary Identification Conditions Identification Nerve Identification Radiological Identification Proteome Wide Identification Genome Wide Identification Selective Identification Radiofrequency Identification Region Identification Classification Identification Simultaneous Identification Response Identification Strain Identification Patients Identification Mechanism Identification Explore More

Frame Identification

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Oct 05, 2024

What is/are Frame Identification?

Frame Identification - Different from the previous studies, this study proposes novel methods which does not require any image segmentation to perform simultaneously key-frame identification and LAV estimation. ^[1]

frame semantic parsing

Frame Identification (FI) is a fundamental and challenging task in frame semantic parsing. ^[1] Current researches on frame semantic parsing include three subtasks, namely frame identification, argument identification and role classification. ^[2] Frame identification is one of the key challenges for frame-semantic parsing. ^[3]

copy move forgery

In the past decades, although machine intelligence has been widely adopted to detect the forgery in digital images automatically, It still remains a very challenging detection task for carefully-crafted copy-move forgery in digital video for three reasons: (i) A video of medium length containing hundreds of frames already incurs a prohibitive computational cost; (ii) Similar backgrounds in contiguous frames are easily mistakenly detected as copy-move forgery regions, resulting to a large number of false alarms; (iii) Most state-of-the-art methods cannot detect video copy-move inter-frame or intra-frame forgeries; To effectively address these issues, a fast forgery frame detection method for video copy-move inter/intra-frame identification is proposed: (i) The sparse feature extraction and matching speed-up the algorithm processing and reduce the time cost greatly (Defect (i)); (ii) The adaptive two-pass filtering and copy-move frame-pair matching can address the similarity problem (Defect (ii)) to locate truly forgery frame-pairs (FFP); (iii) Based on the results of these FFP, the type of video copy-move forgery detection can be identified (Defect (iii)). ^[1]

Key Frame Identification

The first step proposes and uses a key frame identification algorithm to extract a set of optimal frames. ^[1] With the video imprint representation, it is convenient to reverse map back to both temporal and spatial locations in video frames, allowing for both key frame identification and key areas localization within each frame. ^[2]

Namely Frame Identification

Current researches on frame semantic parsing include three subtasks, namely frame identification, argument identification and role classification. ^[1] This work explores how structural information from these lexical resources can lead to gains in a downstream task, namely frame identification. ^[2]