Paper Citation Record · LEDGER

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects

As of 5 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2604.07759.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2604.07759 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T18:11:54.801912Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T23:03:47.227656Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

51 of 51 outbound references displayed

verified exact14
verified fuzzy37
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8db45c19-eaf2-474f-a513-764978f74f1b · outbound

This paper cites Maritime environment perception based on deep learning.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Maritime environment perception based on deep learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.063836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2f31dfe1-e7b7-4915-b956-749569d99b25 · outbound

This paper cites A guide to image-and video-based small object detection using deep learning: Case study of maritime surveillance.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects A guide to image-and video-based small object detection using deep learning: Case study of maritime surveillance

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.053483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e49ff2d9-a45a-430e-8072-574d087e5b7e · outbound

This paper cites Mdd-shipnet: Math-data integrated defogging for fog-occlusion ship detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Mdd-shipnet: Math-data integrated defogging for fog-occlusion ship detection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.042803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 582165e6-328a-4efa-8ced-8821ce98e4e1 · outbound

This paper cites Deep-learning-empowered visual ship detection and tracking: Literature review and future direc- tion.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Deep-learning-empowered visual ship detection and tracking: Literature review and future direc- tion

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.153978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 631aff48-8683-4907-a650-827d8fe36d8d · outbound

This paper cites Aodemar: Attention-aware occlusion detection of vessels for maritime autonomous surface ships.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Aodemar: Attention-aware occlusion detection of vessels for maritime autonomous surface ships

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.137396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e8e76f03-e296-4f59-9555-871c6c3285b8 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.103592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d7ecfda3-24ff-49ec-970e-e3770c87c376 · outbound

This paper cites YOLOv3: An Incremental Improvement.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects YOLOv3: An Incremental Improvement

Reference 7

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 2026-08-05T06:32:48.257954+00:00.

Observation 813a9318-a161-44cb-9f31-c6471bf7cc65 · outbound

This paper cites YOLOv4: Optimal Speed and Accuracy of Object Detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-12T14:34:24.827997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b2e5b741-63fc-4104-a679-822fa0431a09 · outbound

This paper cites Ssd: Single shot multibox detector.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Ssd: Single shot multibox detector

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.071016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e1f0d0ce-3de4-4fb4-9ad9-6b1b6e3776fa · outbound

This paper cites Attention is all you need.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Attention is all you need

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.144142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ff6a5bc3-ddb4-4aa4-b7c1-bd22bbf43ab2 · outbound

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

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-11T05:20:59.730698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 88cbe44a-2ebf-48d5-b286-8dccceb86c36 · outbound

This paper cites End-to-end object detection with transformers.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects End-to-end object detection with transformers

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.165001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d32c49c3-0703-4219-9578-8e130bacf11e · outbound

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

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:47:17.069034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c1a88f92-137e-4c6e-853c-1efde695adbd · outbound

This paper cites Detrs beat yolos on real-time object detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Detrs beat yolos on real-time object detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.067445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fe37ec26-13ee-4115-a5c7-ebe60eb7a5bb · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Mamba: Linear-time sequence modeling with selective state spaces

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.060476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 23c1dac1-a225-403d-86ce-cbd0b0e7b626 · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:37:00.904611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 51a0bee3-f234-4195-9820-535581f821b5 · outbound

This paper cites Seaships: A large-scale precisely annotated dataset for ship detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Seaships: A large-scale precisely annotated dataset for ship detection

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.107044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bffa395a-e0b5-4268-aa5b-611c01a47e89 · outbound

This paper cites An image-based benchmark dataset and a novel object detector for water surface object detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects An image-based benchmark dataset and a novel object detector for water surface object detection

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.046522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ecbbe8cc-db86-4c91-8b32-504689c3b189 · outbound

This paper cites Waterscenes: A multi-task 4d radar- camera fusion dataset and benchmarks for autonomous driving on water surfaces.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Waterscenes: A multi-task 4d radar- camera fusion dataset and benchmarks for autonomous driving on water surfaces

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.087348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 31d899ec-9ceb-4f9d-8552-498c30e2c887 · outbound

This paper cites Video processing from electro-optical sensors for object detection and tracking in a maritime environment: A survey.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Video processing from electro-optical sensors for object detection and tracking in a maritime environment: A survey

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.056888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b33c3a87-7cc4-4e4c-856a-c376e2856600 · outbound

This paper cites Mcships: A large-scale ship dataset for detection and fine-grained categorization in the wild.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Mcships: A large-scale ship dataset for detection and fine-grained categorization in the wild

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.049824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a2695576-ef58-4a34-b23c-1873cd9509d1 · outbound

This paper cites Simuships-a high resolution simulation dataset for ship detection with precise annotations.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Simuships-a high resolution simulation dataset for ship detection with precise annotations

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.100678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2b685f3f-ac10-4ef4-a1b5-db35dce9c4c8 · outbound

This paper cites Asynchronous trajectory matching-based multimodal maritime data fusion for vessel traffic surveillance in inland waterways.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Asynchronous trajectory matching-based multimodal maritime data fusion for vessel traffic surveillance in inland waterways

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.168743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 391f68f0-0ae3-41fb-812f-45e54dc77b3f · outbound

This paper cites Marine vessel detection dataset and benchmark for unmanned surface vehicles.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Marine vessel detection dataset and benchmark for unmanned surface vehicles

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.147616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d8231d7c-cdad-47ff-9b52-c44dbd587f22 · outbound

This paper cites The pascal visual object classes (voc) challenge.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects The pascal visual object classes (voc) challenge

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.134116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7718fa3f-6dc1-4008-9e73-21cdc1d591c5 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Imagenet: A large-scale hierarchical image database

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.140890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c34e387d-3105-4399-a933-e414c4bcab60 · outbound

This paper cites Imagenet large scale visual recognition challenge.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Imagenet large scale visual recognition challenge

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.150847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 402b0d9a-7f8f-4d3f-b962-0b9d22e6fd0a · outbound

This paper cites Microsoft coco: Common objects in context.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Microsoft coco: Common objects in context

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.161085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1fd8615e-6462-4d90-87ab-cb0891aed7b8 · outbound

This paper cites The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.113891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2f0066a4-290c-49cf-bd1a-33f33a1c08ce · outbound

This paper cites Objects365: A large-scale, high-quality dataset for object detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Objects365: A large-scale, high-quality dataset for object detection

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.110465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f0c2a550-27ee-4b94-bc48-b0baa39b072f · outbound

This paper cites Fast image-based ob- stacle detection from unmanned surface vehicles.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Fast image-based ob- stacle detection from unmanned surface vehicles

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.120653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 39bbaa1d-1346-4e94-8cca-1b689ca06019 · outbound

This paper cites Cascade r-cnn: Delving into high quality object detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Cascade r-cnn: Delving into high quality object detection

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.127298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5047207f-3fc8-49b7-b3c3-e6a6fbcad5f4 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects YOLOX: Exceeding YOLO Series in 2021

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-13T10:31:31.716715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7868e0c1-3a0c-4541-bbcd-41a1af8b432e · outbound

This paper cites YOLOv12: Attention-Centric Real-Time Object Detectors.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects YOLOv12: Attention-Centric Real-Time Object Detectors

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:35:11.362323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0e771bb4-38e5-4eab-916b-8bca1df9d884 · outbound

This paper cites YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:20:59.707290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 369e33e8-74a1-44c9-9474-09f81f5d44db · outbound

This paper cites DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:20:59.755818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 15ddb013-2d08-4de1-bbb0-a75ca83d821c · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 37

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 2026-08-05T06:32:48.257954+00:00.

Observation de73d5f0-477a-4606-8009-93ab890a49cc · outbound

This paper cites D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:20:59.679627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation de4ef93d-cba4-4e01-8fea-7ace0f33945f · outbound

This paper cites Vmamba: Visual state space model.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Vmamba: Visual state space model

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.157653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4e7f42ac-c896-47c1-8299-c1f51dd6fd52 · outbound

This paper cites Mamba yolo: A simple baseline for object detection with state space model.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Mamba yolo: A simple baseline for object detection with state space model

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.130802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 20485d5e-e530-41d1-b22d-a51c474a8029 · outbound

This paper cites Ultralytics YOLO.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Ultralytics YOLO

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.074264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 66a02764-8bfc-49ad-8d75-0c575809f1e7 · outbound

This paper cites YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:20:59.717280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a3ab062d-0e59-4e0b-8630-301e9e5c69ff · outbound

This paper cites Hyper-yolo: When visual object detection meets hypergraph computation.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Hyper-yolo: When visual object detection meets hypergraph computation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.117401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 28aadfd1-6fe9-4469-bd49-674cdf1c79b5 · outbound

This paper cites Fbrt-yolo: Faster and better for real- time aerial image detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Fbrt-yolo: Faster and better for real- time aerial image detection

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.097687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c85cab0a-7a86-4ef9-81e2-31e1d6155eb8 · outbound

This paper cites Yolo-ms: Rethinking multi-scale representation learning for real-time object detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Yolo-ms: Rethinking multi-scale representation learning for real-time object detection

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.083269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 20447aa6-2c62-4c87-a878-a3c0a83c8b19 · outbound

This paper cites LW-DETR: A Transformer Replacement to YOLO for Real-Time Detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects LW-DETR: A Transformer Replacement to YOLO for Real-Time Detection

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:20:59.659841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e9239f9b-5bac-400e-a700-857a30a15a87 · outbound

This paper cites Deim: Detr with improved matching for fast convergence.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Deim: Detr with improved matching for fast convergence

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.077927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a8eaa747-4ebd-415f-a8e8-daafb3a721fa · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.123766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ea8a52f3-067b-405d-8950-0e91d8445226 · outbound

This paper cites Mobilemamba: Lightweight multi-receptive visual mamba network.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Mobilemamba: Lightweight multi-receptive visual mamba network

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.091375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e0cf7c93-5eb6-4666-9693-87190403701e · outbound

This paper cites Focal loss for dense object detection.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Focal loss for dense object detection

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T06:39:12.094474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 19593340-958c-480f-9eb9-c3b29463ecb5 · outbound

This paper cites Objects as Points.

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects Objects as Points

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:20:59.724936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

Observation 7f682b3c-1dd7-4069-9f2b-a083b78d1636 · inbound

NavEYE: Vision-Centered Multi-Sensor Fusion-Based Situational Awareness System for Intelligent Surface Vehicles cites this paper.

NavEYE: Vision-Centered Multi-Sensor Fusion-Based Situational Awareness System for Intelligent Surface Vehicles WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-11T23:03:47.227656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.