Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models | Paper Citation Record

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This paper cites Principles of optics: elec- tromagnetic theory of propagation, interference and diffraction of light.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Principles of optics: elec- tromagnetic theory of propagation, interference and diffraction of light

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This paper cites Handbook of Optical Systems.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Handbook of Optical Systems

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Unresolved cited work

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Opto- Mechanical Systems Design, Two Volume Set

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models In collab

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This paper cites Automotive mass production of camera systems: Linking image quality to AI perfor- mance.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Automotive mass production of camera systems: Linking image quality to AI perfor- mance

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This paper cites Benchmark- ing Neural Network Robustness to Common Corrup- tions and Perturbations.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Benchmark- ing Neural Network Robustness to Common Corrup- tions and Perturbations

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This paper cites Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models 3D Common Corruptions and Data Augmentation

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Examining the Impact of Blur on Recognition by Convolutional Networks

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Classification Robustness to Common Optical Aber- rations

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This paper cites URL: https://www.zemax.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models URL: https://www.zemax

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models ImageNet Large Scale Visual Recognition Challenge

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This paper cites Microsoft COCO: Common Ob- jects in Context.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Microsoft COCO: Common Ob- jects in Context

Reference 14

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This paper cites nuScenes: A Multimodal Dataset for Autonomous Driving.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models nuScenes: A Multimodal Dataset for Autonomous Driving

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This paper cites Benchmarking Robustness of 3D Object Detection to Common Corruptions.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Benchmarking Robustness of 3D Object Detection to Common Corruptions

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This paper cites Reliable eval- uation of adversarial robustness with an ensemble of diverse parameter-free attacks.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Reliable eval- uation of adversarial robustness with an ensemble of diverse parameter-free attacks

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models DeepFool: A Simple and Ac- curate Method to Fool Deep Neural Networks

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search

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This paper cites Adversarial Ex- amples Are Not Easily Detected: Bypassing Ten De- tection Methods.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Adversarial Ex- amples Are Not Easily Detected: Bypassing Ten De- tection Methods

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This paper cites RobustBench: a standard- ized adversarial robustness benchmark.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models RobustBench: a standard- ized adversarial robustness benchmark

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Is RobustBench/AutoAttack a suit- able Benchmark for Adversarial Robustness?

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Improving robustness using gener- ated data

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models AutoAugment: Learning Aug- mentation Strategies From Data

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This paper cites AugMix: A Simple Data Processing Method to Improve Robustness and Un- certainty.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models AugMix: A Simple Data Processing Method to Improve Robustness and Un- certainty

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generaliza- tion

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Improving robustness against common corruptions with frequency biased models

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Do adversarially robust imagenet models transfer better?

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models ImageNet-Patch: A dataset for benchmarking machine learning robustness against ad- versarial patches

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Beugungstheorie des schneidenver- fahrens und seiner verbesserten form, der phasenkon- trastmethode

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Retinal image quality for virtual eyes generated by a statistical model of ocular wave- front aberrations

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Optimal modeling of corneal surfaces with Zernike polynomi- 14 als

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Lens design

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Direct determi- nation of aberration functions in microscopy by an artificial neural network

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Calibration of quasi-static aberra- tions in exoplanet direct-imaging instruments with a Zernike phase-mask sensor

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Wave-front reconstruction using a Shack–Hartmann sensor

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models prysm: A Python optics module

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models 3D PSF Models for Fluorescence Microscopy in ImageJ

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Phillips and Henrik Eliasson

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Handbook of Optical Systems

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Unresolved cited work

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Handbook of Optical Systems

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Fast iterative image restoration with a spatially varying PSF

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Unresolved cited work

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Unresolved cited work

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Correcting Misleading Image Quality Measurements

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Digital Image Processing, Third Edition

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Hand- buch Bauelemente der Optik

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models URL: https : / / github

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models ImageNet: A large-scale hierarchical image database

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Lens-Designs

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models 3D-Printed Portable Robotic Mobile Microscope for Remote Diagnosis of Global Health Diseases

Reference 53

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This paper cites URL: https://pytorch.org/vision/0.15/ models.html#classification (visited on 04/02/2024).

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models URL: https://pytorch.org/vision/0.15/ models.html#classification (visited on 04/02/2024)

Reference 54

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This paper cites CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features

Reference 55

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models mixup: Beyond Empirical Risk Minimization

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Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models NoisyMix: Boosting Model Robustness to Common Corruptions

Reference 57

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This paper cites A ConvNet for the 2020s.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models A ConvNet for the 2020s

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.289449Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7b502949-3ca8-4b6b-a5a6-a46bce6d5d61 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-16T10:19:30.335736Z

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Observation de1d1876-afda-4abc-a005-e0c2f16c77e4 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Deep Residual Learning for Image Recognition

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.278207Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 470ce990-c0b0-4567-b5dd-c3a2141905e2 · outbound

This paper cites Densely Connected Convolutional Networks.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Densely Connected Convolutional Networks

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.265657Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 29eb6fb9-9763-4d63-a33e-62a8c5a78209 · outbound

This paper cites Aggregated Residual Transforma- tions for Deep Neural Networks.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Aggregated Residual Transforma- tions for Deep Neural Networks

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.255333Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 36a34f77-3462-4fd7-afb9-d48e98f86cef · outbound

This paper cites Swin Transformer V2: Scaling Up Capacity and Resolution.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Swin Transformer V2: Scaling Up Capacity and Resolution

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.244699Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9636837f-3050-46da-82d5-b7431ed4d74c · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.235073Z

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Observation ec85494e-13b8-4f3f-9781-2b16ea4bc725 · outbound

This paper cites Vision Transformers for Dense Prediction.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Vision Transformers for Dense Prediction

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.224501Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ad82efa2-e7c7-40b4-9244-7de250d22d69 · outbound

This paper cites The Treatment of Ties in Ranking Problems.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models The Treatment of Ties in Ranking Problems

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.213620Z

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Observation e4ee8148-105d-4e96-9f4e-5019b5f1688c · outbound

This paper cites Au- tomated Flower Classification over a Large Number of Classes.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Au- tomated Flower Classification over a Large Number of Classes

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.203439Z

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Observation f79cfe53-321d-4f01-9815-2552a55aac1a · outbound

This paper cites 3D Object Representations for Fine-Grained Categorization.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models 3D Object Representations for Fine-Grained Categorization

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.192128Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ee81c8ca-56a1-47d2-9a1d-b2925fd05049 · outbound

This paper cites TIDE: A General Toolbox for Identifying Object Detection Errors.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models TIDE: A General Toolbox for Identifying Object Detection Errors

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.180456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a23d3bf5-ca79-4653-a87d-c81217dbc899 · outbound

This paper cites Cascade R- CNN: High Quality Object Detection and Instance Segmentation.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Cascade R- CNN: High Quality Object Detection and Instance Segmentation

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.169250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dacede3c-fd33-4053-8f4e-cf626168f46c · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.158243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 799cec29-ff7d-4470-b725-2c114e735fae · outbound

This paper cites DINO: DETR with Improved De- Noising Anchor Boxes for End-to-End Object Detec- tion.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models DINO: DETR with Improved De- Noising Anchor Boxes for End-to-End Object Detec- tion

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.148577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 10522812-522a-4ce5-b2d8-92323019fe9e · outbound

This paper cites Feature Pyramid Networks for Object Detection.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Feature Pyramid Networks for Object Detection

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.137389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 40936562-95c6-4352-8032-b4b7773710fb · outbound

This paper cites Mask R-CNN.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Mask R-CNN

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.127049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c084f814-d6b7-4200-8b05-40f4230dd5fb · outbound

This paper cites Focal Loss for Dense Object Detection.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Focal Loss for Dense Object Detection

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.116413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cf198995-5986-4c6d-8b8c-fe941e594be1 · outbound

This paper cites YOLOX: Exceeding YOLO Series in.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models YOLOX: Exceeding YOLO Series in

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.106166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9dc714d3-6363-424b-bd8d-e8da0c042e78 · outbound

This paper cites Does Robustness on ImageNet Transfer to Downstream Tasks?.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Does Robustness on ImageNet Transfer to Downstream Tasks?

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.095621Z

Source-reported events for the cited work

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Observation 426e2dcf-7a1b-459b-a243-e1d6b2f4c6ad · outbound

This paper cites Proper Reuse of Image Classification Fea- tures Improves Object Detection.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Proper Reuse of Image Classification Fea- tures Improves Object Detection

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.084575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 35ca0267-4885-46ec-94d9-1f6e35e177b7 · outbound

This paper cites Contrastive Multiview Coding.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Contrastive Multiview Coding

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.073612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 086166d9-b912-4ee5-b632-5099169836ab · outbound

This paper cites Emerging Properties in Self- Supervised Vision Transformers.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Emerging Properties in Self- Supervised Vision Transformers

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.063464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 11ad2d93-2ca6-4d67-b96d-a4862f5e3afc · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.052010Z

Source-reported events for the cited work

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Observation 83937bf0-75bb-4056-beb6-61815da40c5a · outbound

This paper cites ConvNets Match Vision Transformers at Scale.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models ConvNets Match Vision Transformers at Scale

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-16T10:19:30.426590Z

Source-reported events for the cited work

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Observation 77307735-c788-4e78-a3a1-45712112c406 · outbound

This paper cites Faster R-CNN: Towards Real- Time Object Detection with Region Proposal Net- works.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Faster R-CNN: Towards Real- Time Object Detection with Region Proposal Net- works

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.039898Z

Source-reported events for the cited work

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Observation 431fcc57-ba34-4439-9706-41d583d42c50 · outbound

This paper cites You Only Look Once: Unified, Real-Time Object Detection.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models You Only Look Once: Unified, Real-Time Object Detection

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.029044Z

Source-reported events for the cited work

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Observation 04034c82-0fef-4f16-9198-ab1b6034fea2 · outbound

This paper cites YOLO-World: Real-Time Open- Vocabulary Object Detection.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models YOLO-World: Real-Time Open- Vocabulary Object Detection

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.018389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4cc22661-0020-4535-99d3-8464d099f7a0 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-16T10:19:30.441678Z

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Observation d9725a6c-f9af-48b8-8924-c7e828c03572 · outbound

This paper cites Grid R-CNN.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Grid R-CNN

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:31.006675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2cdad129-64b4-4c9b-96d9-62e09600b9cf · outbound

This paper cites Swin Transformer: Hierarchical Vision Transformer using Shifted Windows.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.996000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d9983a9a-2857-4604-b44d-212b05542c81 · outbound

This paper cites YOLOv3: An Incremental Improvement.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models YOLOv3: An Incremental Improvement

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-16T10:19:30.453217Z

Source-reported events for the cited work

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Observation c12b3fec-b905-4bb6-948d-79ee8314954b · outbound

This paper cites Hybrid Task Cascade for Instance Segmentation.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Hybrid Task Cascade for Instance Segmentation

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.984789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3409afc3-a99b-4c66-850a-3d9f6c1dee64 · outbound

This paper cites End-to-End Object Detection with Transformers.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models End-to-End Object Detection with Transformers

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.972385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6ed69a62-42bb-49cd-8449-9facf7dda297 · outbound

This paper cites FoveaBox: Beyound Anchor-Based Object Detection.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models FoveaBox: Beyound Anchor-Based Object Detection

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.960524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ea3ddb0c-1790-4578-b978-ae05f46c47a6 · outbound

This paper cites FCOS: Fully Convolutional One-Stage Object Detection.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models FCOS: Fully Convolutional One-Stage Object Detection

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.949994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8bb452a6-0ca1-48ae-a6c6-7f3c42de653c · outbound

This paper cites Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adap- tive Training Sample Selection.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adap- tive Training Sample Selection

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.939521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8c65ef97-fb9e-46ce-ae27-e89b33961380 · outbound

This paper cites Zernike polynomials: a guide.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Zernike polynomials: a guide

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.929483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0d2220c0-16d1-4fc8-8508-78353b987a6c · outbound

This paper cites Simulating op- tical properties to access novel metrological parameter ranges and the impact of different model approxima- tions.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Simulating op- tical properties to access novel metrological parameter ranges and the impact of different model approxima- tions

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.919449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ee9923b5-7062-48f7-bcd7-7918bcbdf78a · outbound

This paper cites Image Quality Assessment: From Error Visibility to Structural Similarity.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Image Quality Assessment: From Error Visibility to Structural Similarity

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.909304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1dacf537-dd9d-4273-8b15-7c690b0aa028 · outbound

This paper cites IEEE Standard for Camera Phone Image Quality.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models IEEE Standard for Camera Phone Image Quality

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.898048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e166595a-4b43-452f-b9e6-261cc4942119 · outbound

This paper cites Standard.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Standard

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.887468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b96c044c-7646-43d3-b7ab-7bf35303a5b1 · outbound

This paper cites Texture-based measurement of spatial frequency response using the dead leaves target: extensions, and application to real camera systems.

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Texture-based measurement of spatial frequency response using the dead leaves target: extensions, and application to real camera systems

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:30.877323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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