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When you want the answer in the next five minutes.
The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →A 5-family dataset on depthwise separable convolution accelerators: who filed, where, and what the filing trend can and cannot show.
17 published records collapse into 5 simple (DOCDB) families; the difference is the same invention filed in more than one country. In force = 7 of 17 records still granted and maintained at the data cut-off; the rest are pending, withdrawn, refused or lapsed.
This page reports a search for depthwise separable convolution and depthwise convolution accelerator designs matched against convolutional neural network or CNN terminology, read across titles, abstracts and claims. The search carries no date limit, so every matching record the database holds is in scope regardless of when it was filed. It returns 17 published records that de-duplicate down to 5 simple patent families, with legal status recorded at retrieval for each published document.
With only 5 families in scope, this is a small pool: a starting point for scoping a further search rather than a map of the field. Figures below should be read as what this specific search string returned, not as a census of accelerator designs for depthwise separable convolution.
Ordered by volume only, not by importance or claim strength. Counted in simple (DOCDB) patent families, so one invention filed in several countries counts once. Names come from Patsnap's standardised assignee field as recorded on each document; subsidiaries and group companies are not merged. The icon before each name is read from the name itself (words such as University, Institute or Ltd); the data carries no organisation-type field, so treat it as a reading aid rather than a classification. Filings held by named individuals rather than organisations are removed where they can be identified (7 here); that identification is not exhaustive, so an individually held filing can still appear below. Either way those filings stay inside the totals above. This table shows the top 4 of the 4 filers returned for this search; the data endpoint returns at most 100 entities, so even that 4 is not the complete set of filers. A single family can name more than one filer, so these counts overlap and do not add up to the total.
The figures below are drawn directly from the search results: a filing trend counted in published records, and an IPC breakdown counted in simple patent families.
Records run from 2021 (6) to a 2022 peak of 7, then decline toward 2026 (0). The years from 2022 onward are still filling in as later publications arrive, so this recent stretch understates eventual totals and should not be read as a falloff in filing.
Counted in published records by earliest filing year, not de-duplicated into families. A filing is counted in the year it was filed, but it only becomes visible after it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. 2022 onwards are therefore still filling in and are shaded; no growth figure on this page uses them. Because this series counts documents rather than inventions, a rise can mean more inventions or the same inventions filed in more countries; this dataset cannot separate the two.
G06N (computing based on AI models) appears on 80.0% of families, the highest share here, followed by G06F (electric digital data processing) at 60.0%. G06J, H03K and H03M each appear on 20.0% of families. Because a single family can carry more than one IPC class, these shares add up to more than 100%.
Shares are the percentage of the 5 patent families in scope. One patent family can carry several IPC classes, so the shares add up to more than 100%.
This page is one run against one query. Ask Eureka your own question about depthwise separable convolution accelerator design patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaThe abstract describes configuring one or more signal processing units (SPUs) of a machine learning task accelerator to process a machine learning model, providing model input data to the configured SPUs, processing that data with the model, and receiving output data from the SPUs.US20220414443A1 is the first record returned under the database's default ordering, not a ranking by citations, novelty or relevance. It is shown to illustrate what one filing in this dataset actually claims to do.


Selected as the first record the search returns under the database default order, then shown in full. It is not ranked by citations, claim breadth or commercial importance, and it is not a judgement about which filing in this space matters most.
When you want the answer in the next five minutes.
The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →When it has to run inside your own pipeline.
Patent search, landscape analysis and assignee resolution as MCP tools. Drop them into any agent framework, or call REST directly.
Browse MCP servers →Three figures from this dataset, reported with the limits that come attached to each one.
The search returns 17 published records that collapse to 5 simple patent families once duplicate country filings of the same invention are merged. Any share or count quoted elsewhere on this page is relative to one of these two totals, never both.
CHONGQING UNIV OF POSTS & TELECOMM, GOOGLE LLC, VELLORE INSITUTE OF TECH and QUALCOMM INC are each named on 1 of the 5 families, so no row sits ahead of the others on count alone. The listed filer rows are organisations only; individual-inventor filings are excluded from this list but remain inside the family and record totals.
G06N (computing based on AI models) is named on 4 of the 4 families, the highest share of any IPC subclass here. G06F follows at 60.0% (3 of 5). Because one family can carry several IPC codes, these two shares overlap rather than add.
7 of the 17 published records were granted and still in force at the 2026-10-20 retrieval date. The remainder cover pending, withdrawn, refused, lapsed or indeterminate statuses that are not broken out individually in this dataset.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to depthwise separable convolution accelerator design patent landscape, with the prior art for and against each one.
This page sketches the shape of a small, specific search. Deeper work on any one filing or filer needs the primary documents.
A family count or an abstract cannot establish what a patent covers. Read the claim set of any family that matters to a decision before drawing conclusions about scope.
Explore in Patsnap EurekaThis result set reflects one specific combination of terms. Adjusting the string may surface adjacent filings that use different terminology for the same accelerator designs.
Run a new search in Patsnap EurekaCHONGQING UNIV OF POSTS & TELECOMM, GOOGLE LLC, VELLORE INSITUTE OF TECH and QUALCOMM INC each appear once in this dataset. Monitoring their later filings can show whether this topic recurs in their portfolios.
Set up monitoring in Patsnap EurekaThis specific search returns 17 published records, which de-duplicate to 5 simple patent families once the same invention filed in multiple countries is merged. That is a small pool, so it should be read as a scoped search result rather than a full count of every accelerator design that touches this topic. A broader or differently worded search string could return a different set of documents.
The dataset lists 4 organisation filers: CHONGQING UNIV OF POSTS & TELECOMM, GOOGLE LLC, VELLORE INSITUTE OF TECH and QUALCOMM INC. Each is named on 1 of the 5 simple patent families, so none sits ahead of the others by count. Individual inventors who filed outside these organisations are excluded from this filer list but are still counted in the overall family and record totals.
Published records run from 6 in 2021 to a peak of 7 in 2022, then taper toward 2026. The years from 2022 onward are still filling in because of publication lag, which runs roughly 18 months and up to 30 months for PCT applications entering national phase, so the recent decline shown on the chart reflects incomplete data rather than fewer filings. The chart counts published records, not de-duplicated inventions, so the same invention filed in several countries adds more than one mark to the line.
G06N, covering computing based on AI models, appears on 4 of the 4 simple patent families (80.0%), the highest share of any IPC subclass in this dataset. G06F, electric digital data processing, follows at 60.0% (3 of 5 families). Because a single family can carry more than one IPC code, these two shares overlap and add up to more than 100% together, so they cannot simply be summed as separate coverage.
This dataset is too small to support a concentration finding: with only 5 families and 4 listed filers each holding 1 or 2 families, a high top-row share is arithmetic rather than evidence of control. The filer rows also are not mutually exclusive, since one family can name more than one filer, so rows cannot be added into a combined share. A reliable read on concentration would need a larger, independently verified dataset.
Go past this page: query the whole depthwise separable convolution accelerator design patent landscape corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.
Search. Every figure on this page comes from one Patsnap search, run once and not edited afterwards. This is the exact search string:
TAC:(("depthwise separable convolution" OR "depthwise convolution") AND accelerator AND ("convolutional neural network" OR CNN))
Reading the field codes: TAC searches the title, abstract and claims of each record, not the full description. The search string sets no date limit, so the scope is every matching record in the database regardless of when it was filed. It is not restricted to recent years. How this string was built matters for how far the counts can be pushed. It was generated in batch from a topic list rather than hand-crafted for this page, and the result set is not manually screened. A keyword search over title, abstract and claims both over-captures (unrelated filings that happen to use the same words) and under-captures (the same invention written in different words). This page cannot measure either effect, so read every figure here as what this particular string returned, not as what exists in the field. One subclass (G06N) carries 80.0% of the patent families, so this search returned a classification-tight set.
What is being counted. Two different units appear on this page and they are not interchangeable. The filer list and the technology split are counted in simple (DOCDB) patent families: one invention counts once however many countries it was filed in. The total, the jurisdiction split and the filing-year chart are counted in published records: the same invention counts once per publication. For this search that is 17 records and 5 families. Record counts reward filing in many jurisdictions; family counts do not. Shares are only ever taken against a denominator in the same unit, and each one names it.
Who the filers are. Names come from Patsnap's standardised assignee field, as recorded on the documents themselves. They are not rolled up to corporate group: a parent and its subsidiaries appear as separate entries, and a portfolio acquired from another company stays under the name on the document unless the assignment is reflected there. This list is meant to carry organisations, not people. Filings held by a named individual are identified by matching the assignee against the inventors on the same search, and, for names written in Chinese, Japanese or Korean characters, by the name carrying no organisational suffix; those are removed from the list (7 of them here). Neither test is exhaustive: the inventor list it matches against is itself capped, and a personal name written in Latin script with no organisational wording in it cannot be told apart from a short company name by rule. So an individually held filing can still appear in the list. Those filings stay inside every total and share on this page either way, so the listed entries can add up to less than the total. A record shown in full further down still names its assignee exactly as the patent office records it, including where that is a person: that name is how the record is identified and checked. What is left out of the ranking is people as ranked entries, not people as cited sources. The table shows the top 4 of the 4 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 4 is not every filer. One patent family can name several filers and each is counted separately, so these rows are not slices of a divided whole: adding them together over-counts, and this page deliberately publishes no combined "top five" share for that reason. See every filer, individuals included
Dates. The year chart counts by earliest filing year, not publication year. A filing only becomes visible once it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. Measured across these pages, the year four back from today still holds only about 89% of its eventual count. 2022 onwards are therefore shaded on the chart as still filling in. The data behind this page was retrieved on 2026-10-20.
Legal status. "In force" counts documents whose legal status at retrieval was granted and maintained (7 of 17). Everything else is pending, withdrawn, refused, lapsed or not determinable, and those states are not broken out here because the underlying codes do not separate them cleanly. Legal status changes continuously and is reported per document, not per family. Get the status breakdown in Eureka
Classification. The technology split uses IPC subclasses (four characters, for example H01M). A single record usually carries several, so the shares add up to more than 100% and a record can appear in more than one bar. Subclass is a coarse grouping; it describes the field a record was classified into, not what the claims cover. Break the classes down to subgroup level
Who wrote the words. The tables, charts, counts, shares and patent numbers on this page are produced directly from the search result by a program; none of them are written or estimated by a language model. The surrounding prose, headings, FAQ answers and the answers in the question panel are drafted by a language model that is given those same figures and is not permitted to introduce others. Prose can still mis-describe a correct figure, so where the two disagree, the tables and charts are the record.
Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries limitations that apply to every figure above. Recent filings are under-counted, because an application is not public until roughly 18 months after filing and database loading adds further delay. The search string defines and constrains everything shown: records that use different terminology, or that sit outside the fields searched, are absent and cannot be counted. Applicant names, classification codes, legal-status codes and citation records are taken as recorded and may contain errors, duplicates, omissions or stale entries. Ordering by volume is not a measure of quality, scope, enforceability or commercial value, and a larger portfolio is not a stronger one. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, validity or infringement search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. No attorney-client relationship is created by it. Any patent, commercial, or strategic decision should be verified independently against the primary records and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
The question panel. The answers behind the suggested questions on this page were written when the page was generated, not in response to your click. The progress steps that play before an answer appears are an animation of how that analysis was done; nothing is being searched or computed at that moment. Typing your own question instead opens Patsnap Eureka, which does run it live.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company's registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.
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