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The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →94 records and 47 patent families on depthwise separable convolution for efficient neural networks, led by Google LLC with a long tail of single-filing
94 published records collapse into 47 simple (DOCDB) families; the difference is the same invention filed in more than one country. In force = 38 of 94 records still granted and maintained at the data cut-off; the rest are pending, withdrawn, refused or lapsed.
This page reports 94 published records and 47 simple patent families matching a search string that requires depthwise separable convolution or depthwise convolution, together with neural network, and at least one of efficient, lightweight or compress* in the title, abstract or claims. No date limit was set, so the set reflects whatever years the matching filings happen to carry rather than a chosen window. The filing-trend chart shown elsewhere on this page displays a recent slice only and should not be read as the full span of the dataset.
47 families is a small pool. Treat this page as a starting point for a search into depthwise separable convolution filings, not as a complete map of the field: a handful of missed terms or an unindexed filing could change the picture.
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 (16 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 30 of the 44 filers returned for this search; the data endpoint returns at most 100 entities, so even that 44 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.
Pick a task. Every answer cites the patents behind it.
The figures below are drawn directly from the search result set: publication counts by filing year, and IPC subclass counts against the 47 families in scope.
Records rose from 2 in 2017 to a peak of 17, reached in both 2021 and 2023, before easing toward 9 in 2026. The 2022-onward stretch is still filling in as later filings publish, so the most recent years understate their eventual count and should not be read as a decline.
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 covers 63.8% of the 47 families, ahead of G06V at 36.2%, G06F at 25.5% and G06T at 19.1%. A family can carry more than one subclass, so these shares add to more than 100%.
Shares are the percentage of the 47 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 efficient neural network design patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaThe abstract describes a radar target recognition method using a feature pyramid lightweight CNN built on a depthwise separable convolution layer, aimed at extracting and classifying high-resolution range profile (HRRP) features under low signal-to-noise ratio conditions. A multi-scale HRRP representation feeds a multi-channel model input to capture both local and global target information.This is the first record returned under the database's default ordering, not the most cited or most representative filing. What its granted claims actually require has to be read from the claim set itself; an abstract and a family count cannot establish claim scope.


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 the result set, reported as counted, no ranking beyond the single rows they come from.
Google LLC is named on 5 of the 47 simple patent families in scope (10.6%). This is the largest single-row share among the listed filers; it does not establish anything about claim scope, validity or the other rows, which are not added to it.
40 of the 44 listed filers hold 2 or fewer simple patent families each. The listed rows sum to more than the 47-family total because a family can name several filers, so no combined share can be read from this list.
G06N (computing based on AI models) appears on 30 of the 44 families (63.8%), the highest of any subclass tracked here. G06V, G06F and G06T follow at 36.2%, 25.5% and 19.1%; a family can carry more than one subclass so these do not sum to 100%.
38 of the 94 published records (40%) were granted and in force as of the 2026-10-15 retrieval date. Legal status changes continuously and is not broken down further here, so this figure should not be read as a success rate.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to depthwise separable convolution efficient neural network design patent landscape, with the prior art for and against each one.
This page surfaces the figures; a closer read of specific claims or filers needs a dedicated workspace.
Family counts and abstracts cannot establish what any single patent blocks. Checking a design against a specific filing means reading its granted claim set in Patsnap Eureka.
Explore in EurekaGoogle LLC's 5-family count and the long tail of smaller filers are a snapshot at retrieval date. Monitoring new publications against this filer list surfaces changes as they publish.
Set up monitoring in EurekaThis search returned 94 published records, which de-duplicate to 47 simple patent families once the same invention filed in multiple countries is counted once. No date limit was applied to the search, so this reflects every matching record regardless of filing year rather than a defined window. The two counts measure different things: records count every publication, families count underlying inventions, so neither number should be read as the other.
Google LLC is named on 5 of the 47 simple patent families in scope, the highest single-row count among the 44 listed filers (organisations only; individual inventors were removed from this list but remain in the totals). That is a count of families named, not a measure of claim scope or portfolio strength. 40 of the 44 listed filers hold 2 or fewer families each, so most of the field here is a long tail rather than a small number of large holders.
IPC subclass G06N (computing based on AI models) appears on 30 of the 44 families (63.8%), the largest share tracked on this page. G06V (image/video recognition), G06F (electric digital data processing) and G06T (image data processing) follow at 36.2%, 25.5% and 19.1% respectively. A single family can carry more than one subclass, so these percentages add to more than 100% and should not be read as mutually exclusive buckets.
38 of the 94 published records (40%) were granted and in force at the 2026-10-15 retrieval date. The remaining records cover a mix of pending, withdrawn, refused or lapsed statuses that are not broken out separately on this page. Legal status changes continuously, so this figure is a snapshot rather than a stable measure, and it says nothing about the quality or scope of any individual filing.
Published records in this set were filed across 12 receiving offices in total; the largest counts are at the United States (39 records), India (18), WIPO under the PCT route (14) and the European Patent Office (11), with smaller counts at Singapore and Austria. These figures count published records, not filers, and one invention can appear at more than one office if filed in multiple jurisdictions. No nationality or country-of-origin data for any filer is available in this dataset, only where applications were filed.
Go past this page: query the whole depthwise separable convolution efficient neural network 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 ("neural network") AND (efficient OR lightweight OR compress*))
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 63.8% 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 94 records and 47 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 (16 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 30 of the 44 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 44 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 2026-10-15.
Legal status. "In force" counts documents whose legal status at retrieval was granted and maintained (38 of 94). 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.
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