Processing images using self-attention based neural networks
US-12125247-B2 · Oct 22, 2024 · US
Sequence processing for a dataset with frame dropping
US12530878B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12530878-B2 |
| Application number | US-202118033305-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 15, 2021 |
| Priority date | Dec 15, 2020 |
| Publication date | Jan 20, 2026 |
| Grant date | Jan 20, 2026 |
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Abstract
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A computer-implemented method for restoring a sequence for a dataset with frame dropping includes receiving an input sequence. A set of features is extracted from the input sequence. A frequency distribution is determined for the input sequence based on the extracted features. Time domain information for the sequence is restored and in turn, data for the input sequence is augmented based on the restored time domain information. Additionally, noise is removed from the input sequence.
First claim
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What is claimed is: 1 . A computer-implemented method comprising: receiving an input sequence; extracting a set of features from the input sequence; determining a frequency distribution for the input sequence based on the extracted features; restoring time domain information for the input sequence by performing an inverse fast Fourier transformation on the frequency distribution; augmenting data for the input sequence by decoding the restored time domain information; and classifying the input sequence based on the augmented data. 2 . The computer-implemented method of claim 1 , in which a full input sequence is restored. 3 . The computer-implemented method of claim 2 , in which the full input sequence is restored based at least in part on an average sample dropping ratio for the input sequence. 4 . The computer-implemented method of claim 1 , further comprising restoring an order of the input sequence. 5 . The computer-implemented method of claim 1 , in which the input sequence comprises a sequence of range-Doppler images. 6 . The computer-implemented method of claim 5 , in which the range-Doppler images correspond to one or more hand gestures. 7 . The computer-implemented method of claim 1 , further comprising determining a length of a cycle of the input sequence. 8 . The computer-implemented method of claim 1 , further comprising extracting at least one noise portion from the input sequence.
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involving the use of neural networks · CPC title
Identification of targets based on measurements of movement associated with the target · CPC title
using classification, e.g. of video objects · CPC title
using neural networks · CPC title
Recognition of hand or arm movements, e.g. recognition of deaf sign language (static hand signs G06V40/113) · CPC title
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- What does patent US12530878B2 cover?
- A computer-implemented method for restoring a sequence for a dataset with frame dropping includes receiving an input sequence. A set of features is extracted from the input sequence. A frequency distribution is determined for the input sequence based on the extracted features. Time domain information for the sequence is restored and in turn, data for the input sequence is augmented based on the…
- Who is the assignee on this patent?
- Qualcomm Inc
- What technology area does this patent fall under?
- Primary CPC classification G06V10/776. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Tue Jan 20 2026 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).