Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-08T14:20:15.084704Z
Paper Citation Record · LEDGER
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes
As of 7 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2605.06084.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
60 of 60 outbound references displayed
- verified exact3
- verified fuzzy57
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 7afd197e-5f5f-4554-bd4c-8b221755e231 · outbound
This paper cites A review of object detection: Datasets, performance evaluation, architecture, applications and current trends.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes A review of object detection: Datasets, performance evaluation, architecture, applications and current trends
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.620345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 50ed227d-01af-4e84-ad99-cf511ac4f156 · outbound
This paper cites An adaptive sample assignment network for tiny object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes An adaptive sample assignment network for tiny object detection
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.612639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation bb49ab6c-e0d3-421c-9933-22f048198ac6 · outbound
This paper cites Frfcnet: Feature refinement and flexible concatenation for object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Frfcnet: Feature refinement and flexible concatenation for object detection
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.673457Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1ac68770-2e71-4bff-abab-6f1dd081f9e6 · outbound
This paper cites Degradation modeling for restoration-enhanced object detection in adverse weather scenes.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Degradation modeling for restoration-enhanced object detection in adverse weather scenes
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.623240Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 44bbab43-a343-402a-b32a-df843cb1f83d · outbound
This paper cites Adaptive and background-aware vision transformer for real-time uav tracking.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Adaptive and background-aware vision transformer for real-time uav tracking
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.626503Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f7c8b603-b8d8-4737-a1e4-9ce309eca828 · outbound
This paper cites A lightweight framework for robust object detection in adverse weather based on dual-teacher feature alignment.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes A lightweight framework for robust object detection in adverse weather based on dual-teacher feature alignment
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.603157Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a925f6e0-1003-4185-9c1d-c691461960fd · outbound
This paper cites Microsoft coco: Common objects in context.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Microsoft coco: Common objects in context
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.648589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 7bb9fdd8-e914-479f-a8f5-08bd158c47d3 · outbound
This paper cites Pascal voc 2008 challenge.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Pascal voc 2008 challenge
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.600591Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation da32cd38-ac3c-4795-8300-015caf69a10a · outbound
This paper cites Toward fast, flexible, and robust low-light image enhancement.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Toward fast, flexible, and robust low-light image enhancement
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.619633Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8e5bf534-354e-4517-90ec-1ea7a0ab6436 · outbound
This paper cites Rethinking image resation for object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Rethinking image resation for object detection
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.589892Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4c997223-18be-4687-9f8a-20321e3839de · outbound
This paper cites Pe-yolo: Pyramid enhancement network for dark object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Pe-yolo: Pyramid enhancement network for dark object detection
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.592044Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8d475383-bef2-4ad2-903d-21a84255f116 · outbound
This paper cites Denet: Detection-driven enhancement network for object detection under adverse weather conditions.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Denet: Detection-driven enhancement network for object detection under adverse weather conditions
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.602864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4615530a-282a-44ab-82df-d9ab1e1ebbe9 · outbound
This paper cites Image-adaptive yolo for object detection in adverse weather conditions.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Image-adaptive yolo for object detection in adverse weather conditions
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.593168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 90b2b76c-bd45-4bfa-804c-d45cc2ed58bf · outbound
This paper cites Gdip: Gated differentiable image processing for object detection in adverse conditions.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Gdip: Gated differentiable image processing for object detection in adverse conditions
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.590443Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 14f9f564-0ef9-4906-89f1-6c5358727c73 · outbound
This paper cites Erup-yolo: Enhancing object detection robustness for adverse weather condition by unified image-adaptive processing.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Erup-yolo: Enhancing object detection robustness for adverse weather condition by unified image-adaptive processing
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.568356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9afb9132-251e-4960-80b9-d10bd0d71122 · outbound
This paper cites Toward highly efficient semantic-guided machine vision for low-light object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Toward highly efficient semantic-guided machine vision for low-light object detection
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.659534Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0fcee7fc-48c8-4d78-befe-1bb1e00f84a3 · outbound
This paper cites Lightstar-net: A pseudo-raw space enhancement for efficient low-light object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Lightstar-net: A pseudo-raw space enhancement for efficient low-light object detection
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.583396Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3ebf70f2-6e90-474a-9120-23f9d10319f4 · outbound
This paper cites Fcma-det: Low-light image object detection based on feature complementarity and multi-content aggregation.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Fcma-det: Low-light image object detection based on feature complementarity and multi-content aggregation
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.559913Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c5deb69d-d9ce-4f3d-88f9-b1f82cdb5931 · outbound
This paper cites Trash to treasure: Low-light object detection via decomposition-and-aggregation.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Trash to treasure: Low-light object detection via decomposition-and-aggregation
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.642128Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1d50a0c6-5fbc-45e3-9142-dd126b276608 · outbound
This paper cites Multitask aet with orthogonal tangent regularity for dark object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Multitask aet with orthogonal tangent regularity for dark object detection
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.680536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ff59ecd4-31a7-46ce-8049-836992bdb4d7 · outbound
This paper cites 2pcnet: Two-phase consistency training for day-to-night unsupervised domain adaptive object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes 2pcnet: Two-phase consistency training for day-to-night unsupervised domain adaptive object detection
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.554093Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f17445e8-48cb-4f54-8992-b010da3c3427 · outbound
This paper cites Isp-teacher: Image signal process with disentanglement regularization for unsupervised domain adaptive dark object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Isp-teacher: Image signal process with disentanglement regularization for unsupervised domain adaptive dark object detection
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.551494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 109b041a-f51b-4b6d-a087-8e3442ee2c24 · outbound
This paper cites Boosting object detection with zero-shot day-night domain adaptation.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Boosting object detection with zero-shot day-night domain adaptation
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.565508Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6e18b103-9d79-4d4e-a1d1-9c9afa0664ba · outbound
This paper cites You only look around: Learning illumination-invariant feature for low-light object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes You only look around: Learning illumination-invariant feature for low-light object detection
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.634172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c0a079fa-bd03-472b-b28e-dcef16a6bde2 · outbound
This paper cites Mbllen: Low-light image/video enhancement using cnns.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Mbllen: Low-light image/video enhancement using cnns
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.615697Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 722e2565-b9c8-49ff-84c1-402df1c9ce50 · outbound
This paper cites Kindling the darkness: A practical low-light image enhancer.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Kindling the darkness: A practical low-light image enhancer
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.651733Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b87785b8-9b7f-42c6-883a-97c997482536 · outbound
This paper cites Zero-reference deep curve estimation for low-light image enhancement.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Zero-reference deep curve estimation for low-light image enhancement
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.629676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 2d3a6598-b498-47e1-8fb5-d43bbc060103 · outbound
This paper cites Information maximizing adaptation network with label distribution priors for unsupervised domain adaptation.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Information maximizing adaptation network with label distribution priors for unsupervised domain adaptation
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.542269Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 74cb725d-532b-429d-a0ef-2865779a6ade · outbound
This paper cites Dsll-face: Distributed supervision-integrated framework for low-light face detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Dsll-face: Distributed supervision-integrated framework for low-light face detection
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.606007Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e37251c7-7b2c-48ed-a68c-34423179e951 · outbound
This paper cites Recurrent exposure generation for low-light face detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Recurrent exposure generation for low-light face detection
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.609279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 13fc4afd-01ac-4db7-9e05-4caaec1a6a69 · outbound
This paper cites Ubtransformer: Uncertainty-based transformer model for complex scenarios detection in autonomous driving.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Ubtransformer: Uncertainty-based transformer model for complex scenarios detection in autonomous driving
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.612401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 2a6e76ea-781c-4027-b4a7-c21d63e0e622 · outbound
This paper cites Yolosr-ist: A deep learning method for small target detection in infrared remote sensing images based on super-resolution and yolo.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Yolosr-ist: A deep learning method for small target detection in infrared remote sensing images based on super-resolution and yolo
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.683774Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8f06025d-91e2-4ca4-b55c-3b76ad30d1b9 · outbound
This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Rich feature hierarchies for accurate object detection and semantic segmentation
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.600125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 239e9164-fb4b-4e51-9b11-c897bfddc527 · outbound
This paper cites Fast r-cnn.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Fast r-cnn
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.555701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b2d9ea73-796a-44d2-9059-5bc4f0462905 · outbound
This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Faster r-cnn: Towards real-time object detection with region proposal networks
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.546658Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1ad39ead-9d49-4800-abc7-804869adc26a · outbound
This paper cites Mask r-cnn.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Mask r-cnn
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.531233Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1aa67d73-c267-4f3e-9159-e5a482b9238c · outbound
This paper cites Superyolo: Super resolution assisted object detection in multimodal remote sensing imagery.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Superyolo: Super resolution assisted object detection in multimodal remote sensing imagery
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.514594Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5f6c695e-2534-479a-a8af-75c79d7e4a5a · outbound
This paper cites Crkd-yolo: Cross-resolution knowledge distillation for low-resolution remote sensing image object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Crkd-yolo: Cross-resolution knowledge distillation for low-resolution remote sensing image object detection
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.676986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6d17adc7-3df1-480b-9a5b-e2541b2ba9ba · outbound
This paper cites Frfcnet: Feature refinement and flexible concatenation for object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Frfcnet: Feature refinement and flexible concatenation for object detection
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.524713Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c9bf568f-25e3-4e94-9e8e-9c37d599043c · outbound
This paper cites Ssd: Single shot multibox detector.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Ssd: Single shot multibox detector
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.569036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c5e6c701-5d66-46c2-b292-31cf3cf6fc44 · outbound
This paper cites Focal loss for dense object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Focal loss for dense object detection
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.571807Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6e5d3051-958f-43a9-921e-045d73571294 · outbound
This paper cites Feature pyramid networks for object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Feature pyramid networks for object detection
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.584247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3f25c7ae-f20b-4953-8bf0-41d371b53c92 · outbound
This paper cites Attention is all you need.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Attention is all you need
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.638152Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 08835603-341e-4cfd-9b49-3f66393bbbb7 · outbound
This paper cites End-to-end object detection with transformers.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes End-to-end object detection with transformers
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.552958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6a4437ee-4dba-4cd8-bfa5-f045b68361d9 · outbound
This paper cites Detrs beat yolos on real-time object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Detrs beat yolos on real-time object detection
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.574927Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e16f1b12-4ad3-4728-b556-319361d218c4 · outbound
This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T19:53:25.827023Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b9303278-06a7-450d-928b-ef447c3ea085 · outbound
This paper cites Learning transferable visual models from natural language supervision.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Learning transferable visual models from natural language supervision
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.578022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 43e141d5-e386-4a6b-ba47-47eb57759ada · outbound
This paper cites A survey of zero-shot object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes A survey of zero-shot object detection
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.587564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9e3c8578-2ce6-488c-8671-62761b26ec33 · outbound
This paper cites Ha-fgovd: Highlighting fine-grained attributes via explicit linear composition for open-vocabulary object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Ha-fgovd: Highlighting fine-grained attributes via explicit linear composition for open-vocabulary object detection
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.528388Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 811d8050-0359-4e96-aa08-709d15eec2de · outbound
This paper cites Research on marker recognition method for substation engineering progress monitoring based on grounding dino.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Research on marker recognition method for substation engineering progress monitoring based on grounding dino
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.511645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b6985ac7-0aa9-42bf-bf35-7134142794ef · outbound
This paper cites M2fnet: Mask-guided multi-level fusion for rgb-t pedestrian detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes M2fnet: Mask-guided multi-level fusion for rgb-t pedestrian detection
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.655812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 2555f349-a92f-4173-ab91-16ffe5eca250 · outbound
This paper cites Detection-friendly dehazing: Object detection in real-world hazy scenes.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Detection-friendly dehazing: Object detection in real-world hazy scenes
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.596325Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 70118a84-3909-422d-b151-c312e41ff850 · outbound
This paper cites Lightness and retinex theory.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Lightness and retinex theory
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.669164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 25a2cb57-e4b3-4794-b2e3-453354dd5b4c · outbound
This paper cites Getting to know low-light images with the exclusively dark dataset.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Getting to know low-light images with the exclusively dark dataset
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.630525Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e7b83801-e798-4476-9393-4b10e86822f0 · outbound
This paper cites Advancing image understanding in poor visibility environments: A collective benchmark study.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Advancing image understanding in poor visibility environments: A collective benchmark study
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.662856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 853b1181-a451-46f8-a56a-1e964d6c64a8 · outbound
This paper cites Llvip: A visible-infrared paired dataset for low-light vision.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Llvip: A visible-infrared paired dataset for low-light vision
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.623026Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b03f0e50-1c79-4ca6-b4f4-ee6319f6dae3 · outbound
This paper cites Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.549985Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3e6a382b-d0c6-4711-9a2c-050226755569 · outbound
This paper cites YOLOv3: An Incremental Improvement.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes YOLOv3: An Incremental Improvement
Reference 58
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T11:37:52.054572Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a0674668-ab38-4612-a269-e2e5a705a329 · outbound
This paper cites Stochastic gradient descent tricks.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Stochastic gradient descent tricks
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T11:37:38.645251Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9ce3e040-8075-4d1a-a188-8dd48783b8a5 · outbound
This paper cites Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks.
AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T18:41:11.517585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Pith citing papers
No inbound Pith citation observations are available.