Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 18600487 | SYSTEM AND METHODS FOR AN ADAPTIVE MACHINE LEARNING MODEL SELECTION BASED ON DATA COMPLEXITY AND USER GOALS | March 2024 | May 2024 | Allow | 2 | 0 | 0 | No | No |
| 18565043 | IMAGE RECOGNITION METHOD AND APPARATUS, AND DEVICE AND MEDIUM | November 2023 | August 2024 | Allow | 9 | 1 | 0 | No | No |
| 18557361 | IMAGE STEGANOGRAPHY UTILIZING ADVERSARIAL PERTURBATIONS | October 2023 | February 2024 | Allow | 4 | 0 | 0 | No | No |
| 18355559 | METHODS FOR ARTHROSCOPIC SURGERY VIDEO SEGMENTATION AND DEVICES THEREFOR | July 2023 | January 2024 | Allow | 6 | 1 | 0 | No | No |
| 18312260 | MACHINE LEARNING DETECTION AND CLASSIFICATION OF MAXILLOFACIAL BONE LESIONS IN CBCT | May 2023 | August 2023 | Allow | 3 | 0 | 0 | No | No |
| 18135046 | ADVERSARIAL DETECTION USING DISCRIMINATOR MODEL OF GENERATIVE ADVERSARIAL NETWORK ARCHITECTURE | April 2023 | April 2024 | Allow | 13 | 1 | 0 | No | No |
| 18099444 | IMAGE COMPRESSION AND DECODING, VIDEO COMPRESSION AND DECODING: TRAINING METHODS AND TRAINING SYSTEMS | January 2023 | September 2023 | Allow | 7 | 0 | 0 | No | No |
| 18014869 | INFORMATION PROCESSING SYSTEM | January 2023 | July 2024 | Abandon | 19 | 2 | 0 | No | No |
| 18080704 | ULTRAFAST, ROBUST AND EFFICIENT DEPTH ESTIMATION FOR STRUCTURED-LIGHT BASED 3D CAMERA SYSTEM | December 2022 | May 2024 | Allow | 17 | 1 | 0 | No | No |
| 17971601 | GEOMETRICALLY CONSTRAINED, UNSUPERVISED TRAINING OF CONVOLUTIONAL AUTOENCODERS FOR EXTRACTION OF EYE LANDMARKS | October 2022 | June 2024 | Allow | 19 | 2 | 0 | No | No |
| 17970396 | SYSTEM AND METHOD FOR EVALUATING THE PERFORMANCE OF A USER IN CAPTURING AN ULTRASOUND IMAGE OF AN ANATOMICAL REGION | October 2022 | September 2023 | Allow | 11 | 2 | 0 | Yes | No |
| 17883499 | METHODS AND SYSTEMS FOR TAGGED IMAGE GENERATION | August 2022 | September 2023 | Abandon | 14 | 1 | 0 | No | No |
| 17864730 | NEURAL NETWORK MODEL TRAINING METHOD AND DEVICE, AND TIME-LAPSE PHOTOGRAPHY VIDEO GENERATING METHOD AND DEVICE | July 2022 | April 2024 | Allow | 21 | 1 | 0 | Yes | No |
| 17855886 | IMAGE RECOGNITION SYSTEM, SENSOR MODULE, AND METHOD FOR IMAGE RECOGNITION | July 2022 | August 2023 | Allow | 14 | 1 | 0 | No | No |
| 17855699 | ADVERSARIAL DETECTION USING DISCRIMINATOR MODEL OF GENERATIVE ADVERSARIAL NETWORK ARCHITECTURE | June 2022 | March 2023 | Allow | 9 | 2 | 0 | Yes | No |
| 17786684 | DEEP-LEARNING-BASED IDENTIFICATION CARD AUTHENTICITY VERIFICATION APPARATUS AND METHOD | June 2022 | January 2023 | Allow | 7 | 0 | 0 | No | No |
| 17735515 | SYSTEMS AND METHODS FOR SYNTHETIC IMAGE GENERATION | May 2022 | March 2024 | Allow | 23 | 1 | 0 | No | No |
| 17585108 | METHOD AND SYSTEM FOR PROVIDING GENERALIZED APPROACH FOR CROP MAPPING ACROSS REGIONS WITH VARYING CHARACTERISTICS | January 2022 | April 2024 | Allow | 26 | 0 | 0 | No | No |
| 17623894 | CONVOLUTION CALCULATION METHOD, CONVOLUTION CALCULATION APPARATUS, AND TERMINAL DEVICE | December 2021 | January 2023 | Allow | 12 | 1 | 0 | No | No |
| 17563356 | CLOUD-EDGE-END COOPERATIVE CONTROL METHOD OF 5G NETWORKED UNMANNED AERIAL VEHICLE FOR SECURITY RESCUE | December 2021 | January 2023 | Allow | 13 | 2 | 0 | No | No |
| 17553885 | IMAGE SCALER | December 2021 | September 2023 | Allow | 21 | 0 | 0 | No | No |
| 17454605 | Self-Supervised Learning for Anomaly Detection and Localization | November 2021 | December 2023 | Allow | 25 | 0 | 0 | No | No |
| 17454472 | METHOD AND APPARATUS FOR IDENTIFYING IMAGE AND ELECTRONIC DEVICE | November 2021 | March 2024 | Abandon | 28 | 1 | 0 | No | No |
| 17514112 | FORMULA AND RECIPE GENERATION WITH FEEDBACK LOOP | October 2021 | October 2023 | Abandon | 24 | 1 | 0 | Yes | No |
| 17483713 | METHODS AND APPARATUS TO PROVIDE AN EFFICIENT SAFETY MECHANISM FOR SIGNAL PROCESSING HARDWARE | September 2021 | August 2023 | Allow | 23 | 1 | 0 | No | No |
| 17480053 | IMAGE PROCESSING AND TRAINING FOR A NEURAL NETWORK | September 2021 | July 2024 | Abandon | 34 | 1 | 0 | No | No |
| 17474489 | METHOD AND APPARATUS FOR ARBITRARY OUTPUT SHAPE PROCESSING OF AN IMAGE | September 2021 | October 2023 | Allow | 25 | 1 | 0 | No | No |
| 17439174 | METHOD FOR CONTROLLING THE POSITIONING OF A MOTOR VEHICLE ON A TRAFFIC LANE | September 2021 | September 2024 | Allow | 36 | 2 | 0 | No | No |
| 17469474 | COMPLEMENTARY LEARNING SYSTEM BASED EXPERIENCE REPLAY (CLS-ER) | September 2021 | July 2024 | Abandon | 34 | 0 | 1 | No | No |
| 17458896 | METHOD AND SYSTEM FOR OBJECT TRACKING USING ONLINE TRAINING | August 2021 | February 2024 | Allow | 29 | 1 | 0 | No | No |
| 17431345 | Efficient Training and Accuracy Improvement of Imaging Based Assay | August 2021 | October 2022 | Allow | 14 | 2 | 0 | No | No |
| 17399699 | PREDICTIVE OUTPUTS IN THE PRESENCE OF ENTITY-DEPENDENT CLASSES | August 2021 | January 2024 | Allow | 29 | 4 | 1 | No | No |
| 17362671 | ENHANCED TRAINING METHOD AND APPARATUS FOR IMAGE RECOGNITION MODEL | June 2021 | March 2022 | Allow | 9 | 1 | 1 | Yes | No |
| 17356409 | COMPUTER-IMPLEMENTED METHOD FOR DETERMINING SURVEY SAMPLING PARAMETERS FOR ENVIRONMENTAL NUCLEIC ACID | June 2021 | June 2024 | Allow | 35 | 2 | 0 | No | No |
| 17332773 | PERFORMING PATCH MATCHING GUIDED BY A TRANSFORMATION GAUSSIAN MIXTURE MODEL | May 2021 | July 2023 | Allow | 25 | 1 | 0 | Yes | No |
| 17303109 | Detailed Damage Determination with Image Cropping | May 2021 | November 2022 | Allow | 18 | 3 | 1 | No | Yes |
| 17293677 | METHOD OF ANOMALY DETECTION AND SYSTEM THEREOF | May 2021 | January 2022 | Allow | 9 | 1 | 0 | No | No |
| 17317780 | FORMULA AND RECIPE GENERATION WITH FEEDBACK LOOP | May 2021 | October 2021 | Allow | 5 | 1 | 0 | Yes | No |
| 17235992 | Supervised Contrastive Learning with Multiple Positive Examples | April 2021 | February 2022 | Allow | 9 | 2 | 0 | Yes | No |
| 17234522 | OBJECT TRACKING ASSISTED WITH HAND OR EYE TRACKING | April 2021 | October 2023 | Allow | 30 | 2 | 0 | Yes | No |
| 17224828 | MACHINE-LEARNED ENTITY FUNCTION MANAGEMENT | April 2021 | April 2022 | Allow | 12 | 2 | 1 | Yes | No |
| 17215816 | FRAME-BASED BODY PART DETECTION IN VIDEO CLIPS | March 2021 | October 2023 | Allow | 31 | 2 | 0 | Yes | No |
| 17213789 | METHODS FOR TRAINING AND TESTING PERCEPTION NETWORK BY USING IMAGES OBTAINED FROM MULTIPLE IMAGING DEVICES HAVING DIVERSE SPECIFICATIONS AND LEARNING DEVICE AND TESTING DEVICE USING THE SAME | March 2021 | November 2021 | Allow | 7 | 1 | 0 | No | No |
| 17196062 | SYSTEMS AND METHODS FOR SYNTHETIC IMAGE GENERATION | March 2021 | January 2022 | Allow | 11 | 2 | 0 | Yes | No |
| 17193878 | DETERMINING TRAVERSABLE SPACE FROM SINGLE IMAGES | March 2021 | April 2023 | Allow | 25 | 4 | 0 | Yes | No |
| 17183075 | OPTIMIZING MACHINE LEARNING MODELS | February 2021 | September 2023 | Allow | 31 | 6 | 1 | Yes | No |
| 17173157 | SYSTEM AND METHOD FOR DETECTING OBJECTS IN IMAGES | February 2021 | August 2021 | Allow | 6 | 2 | 0 | Yes | No |
| 17122603 | AUTOMATED MULTIMODAL ADAPTATION OF MULTIMEDIA CONTENT | December 2020 | September 2023 | Allow | 33 | 2 | 0 | Yes | No |
| 17059678 | INFORMATION PROCESSING DEVICE, CONTROL METHOD, AND PROGRAM | November 2020 | March 2024 | Allow | 39 | 2 | 0 | No | No |
| 17083212 | METHOD FOR GENERATING ABNORMAL DATA | October 2020 | February 2023 | Allow | 27 | 4 | 0 | Yes | No |
| 17080884 | METHOD AND APPARATUS FOR DYNAMIC BLOCK PARTITION OF AN IMAGE | October 2020 | January 2024 | Allow | 39 | 3 | 0 | No | No |
| 17080585 | SYSTEM AND METHOD FOR AI-BASED EYE CONDITION DETERMINATIONS | October 2020 | October 2023 | Allow | 35 | 2 | 0 | No | No |
| 17074629 | SEMANTIC SEGMENTATION METHOD AND APPARATUS FOR THREE-DIMENSIONAL IMAGE, TERMINAL, AND STORAGE MEDIUM | October 2020 | August 2023 | Allow | 34 | 1 | 0 | Yes | No |
| 17067694 | METHOD FOR SEX SORTING OF MOSQUITOES AND APPARATUS THEREFOR | October 2020 | June 2023 | Allow | 32 | 5 | 0 | No | No |
| 17046355 | FILTER DESIGN FOR SMALL TARGET DETECTION ON INFRARED IMAGERY USING NORMALIZED-CROSS-CORRELATION LAYER IN NEURAL NETWORKS | October 2020 | August 2023 | Allow | 34 | 1 | 0 | No | No |
| 16977877 | IMAGE CLASSIFICATION SYSTEM, IMAGE CLASSIFICATION METHOD, AND IMAGE CLASSIFICATION PROGRAM | September 2020 | November 2023 | Allow | 38 | 1 | 0 | No | No |
| 16976412 | POLYNOMIAL CONVOLUTIONAL NEURAL NETWORK WITH LATE FAN-OUT | August 2020 | January 2024 | Allow | 40 | 4 | 0 | No | No |
| 16983064 | SYSTEM AND METHOD FOR PREPARING DIGITAL COMPOSITES FOR INCORPORATING INTO DIGITAL VISUAL MEDIA | August 2020 | December 2021 | Allow | 16 | 2 | 1 | No | No |
| 16943205 | OPTICAL MEASUREMENT DEVICE FOR INSPECTION OF DISCONTINUITIES IN AEROSTRUCTURES | July 2020 | November 2022 | Allow | 27 | 0 | 0 | No | No |
| 16930342 | METHODS AND SYSTEM FOR EFFICIENT PROCESSING OF GENERIC GEOMETRIC CORRECTION ENGINE | July 2020 | October 2022 | Allow | 27 | 0 | 0 | No | No |
| 16904161 | TRAINING METHOD AND SYSTEM OF OBJECTS DETECTION MODEL BASED ON ADAPTIVE ANNOTATION DESIGN | June 2020 | February 2022 | Allow | 20 | 0 | 1 | No | No |
| 16902049 | LEARNING METHOD, COMPUTER PROGRAM, CLASSIFIER, GENERATOR, AND PROCESSING SYSTEM | June 2020 | August 2023 | Allow | 38 | 2 | 1 | Yes | No |
| 16898506 | PRODUCING A BIRD'S EYE VIEW IMAGE FROM A TWO DIMENSIONAL IMAGE | June 2020 | August 2024 | Allow | 50 | 5 | 0 | Yes | No |
| 16896367 | RECOGNITION SYSTEM FOR SECURITY CHECK AND CONTROL METHOD THEREOF | June 2020 | November 2022 | Allow | 29 | 1 | 0 | No | No |
| 16894123 | METHOD AND APPARATUS FOR DETECTING TARGET OBJECT IN IMAGE | June 2020 | July 2023 | Allow | 37 | 2 | 1 | No | No |
| 16892587 | NEURAL NETWORK MODEL TRAINING METHOD AND DEVICE, AND TIME-LAPSE PHOTOGRAPHY VIDEO GENERATING METHOD AND DEVICE | June 2020 | June 2022 | Allow | 24 | 1 | 1 | Yes | No |
| 16876228 | DOCUMENT EXTRACTION SYSTEM AND METHOD | May 2020 | November 2021 | Allow | 18 | 1 | 0 | No | No |
| 16877471 | LIGHT FIELD IMAGE RENDERING METHOD AND SYSTEM FOR CREATING SEE-THROUGH EFFECTS | May 2020 | November 2022 | Allow | 30 | 2 | 0 | No | No |
| 16875488 | SYSTEM AND METHOD FOR CONCURRENT ODOMETRY AND MAPPING | May 2020 | April 2023 | Allow | 35 | 2 | 1 | Yes | No |
| 16874175 | IMAGE PROCESSING SYSTEM USING RECURRENT NEURAL NETWORKS | May 2020 | December 2022 | Allow | 31 | 2 | 0 | No | No |
| 16869024 | METHOD AND APPARATUS FOR PROCESSING IMAGE | May 2020 | August 2022 | Allow | 27 | 1 | 1 | No | No |
| 16867576 | Device and Method of Handling Anomaly Detection | May 2020 | July 2023 | Allow | 38 | 3 | 1 | Yes | No |
| 16759383 | METHOD AND APPARATUS FOR TRAINING SEMANTIC SEGMENTATION MODEL, COMPUTER DEVICE, AND STORAGE MEDIUM | April 2020 | April 2022 | Allow | 24 | 2 | 0 | No | No |
| 16857337 | METHOD FOR TRAINING IMAGE GENERATION NETWORK, ELECTRONIC DEVICE, AND STORAGE MEDIUM | April 2020 | January 2023 | Abandon | 33 | 2 | 1 | No | No |
| 16853733 | IMAGE CLASSIFICATION METHOD, COMPUTER DEVICE, AND COMPUTER-READABLE STORAGE MEDIUM | April 2020 | March 2022 | Allow | 23 | 1 | 0 | Yes | No |
| 16851093 | ULTRAFAST, ROBUST AND EFFICIENT DEPTH ESTIMATION FOR STRUCTURED-LIGHT BASED 3D CAMERA SYSTEM | April 2020 | August 2022 | Allow | 28 | 2 | 1 | No | No |
| 15929255 | Representation learning-based star identification method | April 2020 | December 2021 | Allow | 21 | 1 | 0 | No | No |
| 16838037 | LEARNABLE DEFECT DETECTION FOR SEMICONDUCTOR APPLICATIONS | April 2020 | September 2022 | Allow | 30 | 2 | 1 | No | Yes |
| 16838256 | OBJECT RECOGNITION SYSTEM AND OBJECT RECOGNITION METHOD | April 2020 | August 2022 | Allow | 28 | 2 | 0 | No | No |
| 16784814 | IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD, AND IMAGE PROCESSING SYSTEM | February 2020 | March 2022 | Allow | 25 | 1 | 0 | No | No |
| 16778480 | METHOD OF AND SYSTEM FOR JOINT DATA AUGMENTATION AND CLASSIFICATION LEARNING | January 2020 | September 2021 | Allow | 19 | 0 | 0 | No | No |
| 16778384 | COMPUTER IMPLEMENTED METHOD FOR DETERMINING SURVEY SAMPLING PARAMETERS FOR ENVIRONMENTAL DNA DETECTION | January 2020 | February 2021 | Allow | 13 | 1 | 0 | No | No |
| 16749263 | DETECTION AND IDENTIFICATION OF OBJECTS IN IMAGES | January 2020 | October 2022 | Allow | 33 | 2 | 1 | Yes | No |
| 16748817 | TRAINING METHOD OF NEURAL NETWORK AND CLASSIFICATION METHOD BASED ON NEURAL NETWORK AND DEVICE THEREOF | January 2020 | February 2023 | Allow | 37 | 3 | 1 | Yes | No |
| 16746674 | GENERATING TRAINING DATASETS FOR TRAINING NEURAL NETWORKS | January 2020 | October 2023 | Allow | 45 | 2 | 1 | Yes | No |
| 16630274 | METHODS AND SYSTEMS FOR LEARNING-BASED IMAGE EDGE ENHANCEMENT OF SAMPLE TUBE TOP CIRCLES | January 2020 | July 2022 | Allow | 30 | 2 | 0 | Yes | Yes |
| 16732640 | GEOMETRICALLY CONSTRAINED, UNSUPERVISED TRAINING OF CONVOLUTIONAL AUTOENCODERS FOR EXTRACTION OF EYE LANDMARKS | January 2020 | August 2022 | Allow | 32 | 2 | 0 | No | No |
| 16726880 | SEMANTIC SEGMENTATION MODEL TRAINING METHODS AND APPARATUSES, ELECTRONIC DEVICES, AND STORAGE MEDIA | December 2019 | February 2022 | Allow | 26 | 1 | 0 | No | No |
| 16720610 | AUTOMATIC VISUAL DATA GENERATION FOR OBJECT TRAINING AND EVALUATION | December 2019 | August 2023 | Abandon | 44 | 3 | 1 | No | No |
| 16718148 | STORAGE CONTROLLER HAVING DATA AUGMENTATION COMPONENTS FOR USE WITH NON-VOLATILE MEMORY DIE | December 2019 | February 2022 | Allow | 26 | 2 | 1 | Yes | Yes |
| 16709127 | METHOD AND SYSTEM FOR FILL LEVEL DETERMINATION | December 2019 | October 2020 | Allow | 10 | 1 | 1 | Yes | No |
| 16699738 | BIOMETRIC FEATURE RECONSTRUCTION METHOD, STORAGE MEDIUM AND NEURAL NETWORK | December 2019 | June 2022 | Allow | 31 | 2 | 0 | No | No |
| 16698252 | Learning Method, Computer Program, Classifier, And Generator | November 2019 | November 2022 | Allow | 36 | 2 | 1 | Yes | No |
| 16694286 | UNSUPERVISED TRAINING OF NEURAL NETWORK FOR HIGH DYNAMIC RANGE IMAGE COMPRESSION | November 2019 | November 2021 | Allow | 24 | 1 | 1 | No | No |
| 16614386 | METHOD AND APPARATUS FOR ANALYSING VIDEO CONTENT IN DIGITAL FORMAT | November 2019 | December 2022 | Abandon | 37 | 2 | 1 | No | No |
| 16683830 | UNRESOLVED OBJECT TARGET DETECTION USING A DEEP NEURAL NETWORK | November 2019 | January 2022 | Allow | 26 | 2 | 0 | Yes | No |
| 16680562 | SEQUENTIAL LEARNING MAINTAINING A LEARNED CONCEPT | November 2019 | March 2022 | Allow | 28 | 1 | 1 | No | No |
| 16678768 | TRAINING DATA GENERATION METHOD, TRAINING DATA GENERATION PROGRAM, TRAINING DATA GENERATION APPARATUS, AND PRODUCT IDENTIFICATION APPARATUS | November 2019 | August 2024 | Abandon | 58 | 3 | 1 | Yes | Yes |
| 16666631 | Method for Updating Neural Network and Electronic Device | October 2019 | January 2022 | Allow | 27 | 1 | 0 | No | No |
| 16660743 | DETECTION METHOD AND DETECTION DEVICE | October 2019 | September 2021 | Allow | 23 | 1 | 0 | No | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner LEE, JOHN W.
With a 37.5% reversal rate, the PTAB reverses the examiner's rejections in a meaningful percentage of cases. This reversal rate is above the USPTO average, indicating that appeals have better success here than typical.
Filing a Notice of Appeal can sometimes lead to allowance even before the appeal is fully briefed or decided by the PTAB. This occurs when the examiner or their supervisor reconsiders the rejection during the mandatory appeal conference (MPEP § 1207.01) after the appeal is filed.
In this dataset, 59.1% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is in the top 25% across the USPTO, indicating that filing appeals is particularly effective here. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.
✓ Appeals to PTAB show good success rates. If you have a strong case on the merits, consider fully prosecuting the appeal to a Board decision.
✓ Filing a Notice of Appeal is strategically valuable. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.
Examiner LEE, JOHN W works in Art Unit 2664 and has examined 227 patent applications in our dataset. With an allowance rate of 82.4%, this examiner has an above-average tendency to allow applications. Applications typically reach final disposition in approximately 32 months.
Examiner LEE, JOHN W's allowance rate of 82.4% places them in the 55% percentile among all USPTO examiners. This examiner has an above-average tendency to allow applications.
On average, applications examined by LEE, JOHN W receive 2.46 office actions before reaching final disposition. This places the examiner in the 71% percentile for office actions issued. This examiner issues a slightly above-average number of office actions.
The median time to disposition (half-life) for applications examined by LEE, JOHN W is 32 months. This places the examiner in the 51% percentile for prosecution speed. Prosecution timelines are slightly faster than average with this examiner.
Conducting an examiner interview provides a +11.8% benefit to allowance rate for applications examined by LEE, JOHN W. This interview benefit is in the 47% percentile among all examiners. Recommendation: Interviews provide a below-average benefit with this examiner.
When applicants file an RCE with this examiner, 28.2% of applications are subsequently allowed. This success rate is in the 51% percentile among all examiners. Strategic Insight: RCEs show above-average effectiveness with this examiner. Consider whether your amendments or new arguments are strong enough to warrant an RCE versus filing a continuation.
This examiner enters after-final amendments leading to allowance in 28.4% of cases where such amendments are filed. This entry rate is in the 40% percentile among all examiners. Strategic Recommendation: This examiner shows below-average receptiveness to after-final amendments. You may need to file an RCE or appeal rather than relying on after-final amendment entry.
When applicants request a pre-appeal conference (PAC) with this examiner, 37.5% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 35% percentile among all examiners. Note: Pre-appeal conferences show below-average success with this examiner. Consider whether your arguments are strong enough to warrant a PAC request.
This examiner withdraws rejections or reopens prosecution in 69.2% of appeals filed. This is in the 55% percentile among all examiners. Of these withdrawals, 50.0% occur early in the appeal process (after Notice of Appeal but before Appeal Brief). Strategic Insight: This examiner shows above-average willingness to reconsider rejections during appeals. The mandatory appeal conference (MPEP § 1207.01) provides an opportunity for reconsideration.
When applicants file petitions regarding this examiner's actions, 24.5% are granted (fully or in part). This grant rate is in the 13% percentile among all examiners. Strategic Note: Petitions are rarely granted regarding this examiner's actions compared to other examiners. Ensure you have a strong procedural basis before filing a petition, as the Technology Center Director typically upholds this examiner's decisions.
Examiner's Amendments: This examiner makes examiner's amendments in 0.0% of allowed cases (in the 21% percentile). This examiner rarely makes examiner's amendments compared to other examiners. You should expect to make all necessary claim amendments yourself through formal amendment practice.
Quayle Actions: This examiner issues Ex Parte Quayle actions in 8.6% of allowed cases (in the 87% percentile). Per MPEP § 714.14, a Quayle action indicates that all claims are allowable but formal matters remain. This examiner frequently uses Quayle actions compared to other examiners, which is a positive indicator that once substantive issues are resolved, allowance follows quickly.
Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:
Not Legal Advice: The information provided in this report is for informational purposes only and does not constitute legal advice. You should consult with a qualified patent attorney or agent for advice specific to your situation.
No Guarantees: We do not provide any guarantees as to the accuracy, completeness, or timeliness of the statistics presented above. Patent prosecution statistics are derived from publicly available USPTO data and are subject to data quality limitations, processing errors, and changes in USPTO practices over time.
Limitation of Liability: Under no circumstances will IronCrow AI be liable for any outcome, decision, or action resulting from your reliance on the statistics, analysis, or recommendations presented in this report. Past prosecution patterns do not guarantee future results.
Use at Your Own Risk: While we strive to provide accurate and useful prosecution statistics, you should independently verify any information that is material to your prosecution strategy and use your professional judgment in all patent prosecution matters.