Prosecution Insights
Last updated: April 19, 2026
Application No. 18/756,176

CARD-CENTERED ABNORMALITY DETECTION SYSTEM USING CAMERA AND SHOE

Non-Final OA §101§DP
Filed
Jun 27, 2024
Examiner
DEODHAR, OMKAR A
Art Unit
3715
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Angel Group Co. Ltd.
OA Round
1 (Non-Final)
80%
Grant Probability
Favorable
1-2
OA Rounds
2y 7m
To Grant
99%
With Interview

Examiner Intelligence

Grants 80% — above average
80%
Career Allow Rate
1025 granted / 1284 resolved
+9.8% vs TC avg
Strong +19% interview lift
Without
With
+19.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
40 currently pending
Career history
1324
Total Applications
across all art units

Statute-Specific Performance

§101
18.7%
-21.3% vs TC avg
§103
36.6%
-3.4% vs TC avg
§102
22.4%
-17.6% vs TC avg
§112
8.5%
-31.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1284 resolved cases

Office Action

§101 §DP
Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Procedural Summary This is responsive to the claims filed 6/27/2024. Claims 1-20 are pending. Signed copies of the IDS’ are attached. The Drawings filed 6/27/2024 are noted. Double Patenting A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957). A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101. Claims 1-20 are rejected under 35 U.S.C. 101 as claiming the same invention as that of claims 1-20 of prior U.S. Patent No. 12,051,302 B2. This is a statutory double patenting rejection. For example, see the claim chart below with pending and patented claims verbatim. Pending Claims 1-20: Patented Claim 1: 1. A system comprising: a camera configured to capture a plurality of images of a game table where a game is played using cards; a card recognition device configured to: use artificial intelligence or deep learning to recognize the cards based on the plurality of images captured by the camera; and recognize ranks and positions of the recognized cards; a controller configured to identify a card hand of a player of the table game using a recognition result of the card recognition device; and a chip recognition device configured to recognize a chip bet in a bet area on the game table by using the artificial intelligence or the deep learning to recognize the chips based on the plurality of images generated by the camera, wherein the controller is further configured to identify a bet amount in the bet area based on a recognition result of the chip recognizing device. 2. The system according to claim 1, wherein the recognition result indicates, for at least one card of the recognized cards, a rank of the at least one card, a position of the at least one card, or a combination thereof. 3. The system according to claim 1, wherein: a player area where the card hand of the player is to be placed is arranged on the game table; and the controller is further configured to identify cards located in the player area as the card hand of the player. 4. The system according to claim 1, wherein the controller is further configured to determine whether cards to be the card hand of the player have been correctly dealt into a player area or not. 5. The system according to claim 1, further comprising: a card dealing device that reads ranks of cards dealt into the game table; and wherein the controller is further configured to determine whether or not ranks read from cards to be the card hand of the player by the card dealing device correspond to ranks of cards identified as the card hand of the player using the recognition result of the card recognition device. 6. The system according to claim 1, wherein the controller is further configured to identify a card hand of a dealer using the recognition result of the card recognition device. 7. The system according to claim 6, wherein: a dealer area where the card hand of the dealer is to be placed is arranged on the game table; and the controller is further configured to identify cards located in the dealer area as the card hand of the dealer. 8. The system according to claim 6, wherein the controller is further configured to determine a game result according to game rules based on the identified card hand of the player and the identified card hand of the dealer. 9. The system according to claim 1, wherein by using the artificial intelligence or the deep learning, the card recognizing device is configured to recognize a rank of a card that is folded or dirty. 10. The system according to claim 1, wherein: each time one of the cards is dealt, the camera is configured to capture an image of the card; the card recognition device is configured to recognize each of the positions of the cards dealt in order; and the controller is further configured to determine whether a combination of the order of dealing of the cards and the positions is correct or not using the recognition result of the card recognizing device. 11. The system according to claim 1, further comprising: a chip recognition device configured to: use artificial intelligence or deep learning to recognize chips from the plurality of images captured by the camera; and recognize a chip bet in a bet area on the game table based on the recognized chips; and wherein the controller is further configured to identify a bet amount in the bet area based on a recognition result of the chip recognizing device. 12. A system comprising: a camera configured to capture a plurality of images of a game table where a game is played using cards; a card recognition device configured to: use artificial intelligence or deep learning to recognize the cards based on the plurality of images captured by the camera; and recognize ranks and positions of the recognized cards; a controller configured to identify a card hand of a player of the table game using a recognition result of the card recognition device; a chip recognition device configured to: use artificial intelligence or deep learning to recognize chips from the plurality of images captured by the camera; and recognize a chip bet in a bet area on the game table based on the recognized chips, wherein the controller is further configured to identify a bet amount in the bet area based on a recognition result of the chip recognizing device. 13. The system according to claim 12, wherein the recognition result indicates, for at least one card of the recognized cards, a rank of the at least one card, a position of the at least one card, or a combination thereof. 14. The system according to claim 12, wherein: a player area where the card hand of the player is to be placed is arranged on the game table; and the controller is further configured to identify cards located in the player area as the card hand of the player. 15. The system according to claim 12, wherein the controller is further configured to determine whether cards to be the card hand of the player have been correctly dealt into a player area or not. 16. The system according to claim 12, further comprising: a card dealing device that reads ranks of cards dealt into the game table; and wherein the controller is further configured to determine whether or not ranks read from cards to be the card hand of the player by the card dealing device correspond to ranks of cards identified as the card hand of the player using the recognition result of the card recognition device. 17. The system according to claim 12, wherein the controller is further configured to identify a card hand of a dealer using the recognition result of the card recognition device. 18. The system according to claim 17, wherein: a dealer area where the card hand of the dealer is to be placed is arranged on the game table; and the controller is further configured to identify cards located in the dealer area as the card hand of the dealer. 19. The system according to claim 17, wherein the controller is further configured to determine a game result according to game rules based on the identified card hand of the player and the identified card hand of the dealer. 20. The system according to claim 12, wherein by using the artificial intelligence or the deep learning, the card recognizing device is configured to recognize a rank of a card that is folded or dirty. 1. A system comprising: a camera configured to capture a plurality of images of a game table where a game is played using cards; a card recognition device configured to: use artificial intelligence or deep learning to recognize the cards based on the plurality of images captured by the camera; and recognize ranks and positions of the recognized cards; a controller configured to identify a card hand of a player of the table game using a recognition result of the card recognition device; and a chip recognition device configured to recognize a chip bet in a bet area on the game table by using the artificial intelligence or the deep learning to recognize the chips based on the plurality of images generated by the camera, wherein the controller is further configured to identify a bet amount in the bet area based on a recognition result of the chip recognizing device. 2. The system according to claim 1, wherein the recognition result indicates, for at least one card of the recognized cards, a rank of the at least one card, a position of the at least one card, or a combination thereof. 3. The system according to claim 1, wherein: a player area where the card hand of the player is to be placed is arranged on the game table; and the controller is further configured to identify cards located in the player area as the card hand of the player. 4. The system according to claim 1, wherein the controller is further configured to determine whether cards to be the card hand of the player have been correctly dealt into a player area or not. 5. The system according to claim 1, further comprising: a card dealing device that reads ranks of cards dealt into the game table; and wherein the controller is further configured to determine whether or not ranks read from cards to be the card hand of the player by the card dealing device correspond to ranks of cards identified as the card hand of the player using the recognition result of the card recognition device. 6. The system according to claim 1, wherein the controller is further configured to identify a card hand of a dealer using the recognition result of the card recognition device. 7. The system according to claim 6, wherein: a dealer area where the card hand of the dealer is to be placed is arranged on the game table; and the controller is further configured to identify cards located in the dealer area as the card hand of the dealer. 8. The system according to claim 6, wherein the controller is further configured to determine a game result according to game rules based on the identified card hand of the player and the identified card hand of the dealer. 9. The system according to claim 1, wherein by using the artificial intelligence or the deep learning, the card recognizing device is configured to recognize a rank of a card that is folded or dirty. 10. The system according to claim 1, wherein: each time one of the cards is dealt, the camera is configured to capture an image of the card; the card recognition device is configured to recognize each of the positions of the cards dealt in order; and the controller is further configured to determine whether a combination of the order of dealing of the cards and the positions is correct or not using the recognition result of the card recognizing device. 11. The system according to claim 1, further comprising: a chip recognition device configured to: use artificial intelligence or deep learning to recognize chips from the plurality of images captured by the camera; and recognize a chip bet in a bet area on the game table based on the recognized chips; and wherein the controller is further configured to identify a bet amount in the bet area based on a recognition result of the chip recognizing device. 12. A system comprising: a camera configured to capture a plurality of images of a game table where a game is played using cards; a card recognition device configured to: use artificial intelligence or deep learning to recognize the cards based on the plurality of images captured by the camera; and recognize ranks and positions of the recognized cards; a controller configured to identify a card hand of a player of the table game using a recognition result of the card recognition device; a chip recognition device configured to: use artificial intelligence or deep learning to recognize chips from the plurality of images captured by the camera; and recognize a chip bet in a bet area on the game table based on the recognized chips, wherein the controller is further configured to identify a bet amount in the bet area based on a recognition result of the chip recognizing device. 13. The system according to claim 12, wherein the recognition result indicates, for at least one card of the recognized cards, a rank of the at least one card, a position of the at least one card, or a combination thereof. 14. The system according to claim 12, wherein: a player area where the card hand of the player is to be placed is arranged on the game table; and the controller is further configured to identify cards located in the player area as the card hand of the player. 15. The system according to claim 12, wherein the controller is further configured to determine whether cards to be the card hand of the player have been correctly dealt into a player area or not. 16. The system according to claim 12, further comprising: a card dealing device that reads ranks of cards dealt into the game table; and wherein the controller is further configured to determine whether or not ranks read from cards to be the card hand of the player by the card dealing device correspond to ranks of cards identified as the card hand of the player using the recognition result of the card recognition device. 17. The system according to claim 12, wherein the controller is further configured to identify a card hand of a dealer using the recognition result of the card recognition device. 18. The system according to claim 17, wherein: a dealer area where the card hand of the dealer is to be placed is arranged on the game table; and the controller is further configured to identify cards located in the dealer area as the card hand of the dealer. 19. The system according to claim 17, wherein the controller is further configured to determine a game result according to game rules based on the identified card hand of the player and the identified card hand of the dealer. 20. The system according to claim 12, wherein by using the artificial intelligence or the deep learning, the card recognizing device is configured to recognize a rank of a card that is folded or dirty. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to OMKAR A DEODHAR whose telephone number is (571)272-1647. The examiner can normally be reached on M-F, generally 9am-5:30 pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, David Lewis can be reached on 571-272-7673. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /OMKAR A DEODHAR/Primary Examiner, Art Unit 3715
Read full office action

Prosecution Timeline

Jun 27, 2024
Application Filed
Mar 09, 2026
Non-Final Rejection — §101, §DP (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
80%
Grant Probability
99%
With Interview (+19.3%)
2y 7m
Median Time to Grant
Low
PTA Risk
Based on 1284 resolved cases by this examiner. Grant probability derived from career allow rate.

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