Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection | Paper Citation Record

Observation 03e7adf4-8a11-4643-9b86-d1d264f8e2cc · outbound

This paper cites Ship detection in spaceborne infrared image based on lightweight cnn and multisource feature cascade decision,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Ship detection in spaceborne infrared image based on lightweight cnn and multisource feature cascade decision,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.853967Z

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Observation f5fa73cf-99e7-4e02-a13b-be8cfcb94048 · outbound

This paper cites Fishing vessel classification in sar images using a novel deep learning model,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Fishing vessel classification in sar images using a novel deep learning model,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.841551Z

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Observation 63a28c03-e6d5-4cf3-87ba-4fc5a6a12779 · outbound

This paper cites Ship detection based on complex signal kurtosis in single-channel sar imagery,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Ship detection based on complex signal kurtosis in single-channel sar imagery,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.828502Z

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Observation 222bb89c-999e-4397-bc6d-222b1cdc4b61 · outbound

This paper cites Git: Graph interactive transformer for vehicle re-identification,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Git: Graph interactive transformer for vehicle re-identification,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.816151Z

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Observation fff6b3f3-43ad-4bdf-9e74-9aac67324362 · outbound

This paper cites Sar ship detection based on explainable evidence learning under intraclass imbalance,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Sar ship detection based on explainable evidence learning under intraclass imbalance,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.804625Z

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Observation 1e4da2ea-1aac-40f7-b738-2dd03d541578 · outbound

This paper cites Oriented gaussian function- based box boundary-aware vectors for oriented ship detection in mul- tiresolution sar imagery,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Oriented gaussian function- based box boundary-aware vectors for oriented ship detection in mul- tiresolution sar imagery,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.792066Z

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Observation ad6a87c0-18b1-43a5-a6ef-a03d1aa402fa · outbound

This paper cites An adaptive and fast cfar algorithm based on automatic censoring for target detection in high- resolution sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection An adaptive and fast cfar algorithm based on automatic censoring for target detection in high- resolution sar images,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.779382Z

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Observation 854f8e7e-5523-4d04-a36c-b4a9d4e6a362 · outbound

This paper cites Ship detection in sar images based on lognormal ρ -metric,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Ship detection in sar images based on lognormal ρ -metric,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.766855Z

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Observation e4f7c20a-388c-487f-9c26-28cd2f4bde17 · outbound

This paper cites Analysis of the ship target detection in high-resolution sar images based on information theory and harris corner detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Analysis of the ship target detection in high-resolution sar images based on information theory and harris corner detection,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.752866Z

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Observation f8cc92b2-c510-497f-bf49-7114d65303c4 · outbound

This paper cites A novel algorithm for ship detection in sar imagery based on the wavelet transform,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection A novel algorithm for ship detection in sar imagery based on the wavelet transform,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.740719Z

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Observation a22e2265-a61a-4642-b23e-5641af789f73 · outbound

This paper cites A novel ship detection method based on gradient and integral feature for single-polarization synthetic aperture radar imagery,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection A novel ship detection method based on gradient and integral feature for single-polarization synthetic aperture radar imagery,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.728169Z

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Observation 15b8f093-99f4-49b4-bdf2-795b33a43f5c · outbound

This paper cites An improved bilateral cfar ship detection algorithm for sar image in complex envi- ronment,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection An improved bilateral cfar ship detection algorithm for sar image in complex envi- ronment,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.715366Z

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Observation 9bf29bb1-1c1d-4ec3-b143-0beaa5581c37 · outbound

This paper cites A survey of convolutional neural networks: Analysis, applications, and prospects,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection A survey of convolutional neural networks: Analysis, applications, and prospects,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.702611Z

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Observation 897249c1-527a-488f-89dc-3e9e581e5d74 · outbound

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

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.728802Z

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Observation f832a88f-96fb-43b1-9c51-72959e8e22e2 · outbound

This paper cites Enhancing landslide segmentation with guide attention mechanism and fast fourier transformer,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Enhancing landslide segmentation with guide attention mechanism and fast fourier transformer,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.681649Z

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Observation 6e75d871-4a14-4afa-bc9a-bd1c228265df · outbound

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

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Cascade r-cnn: Delving into high quality object detection,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.669306Z

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Observation e70b0954-2130-48a8-ae69-7c07f2554fa2 · outbound

This paper cites Ssd: Single shot multibox detector,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Ssd: Single shot multibox detector,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.656908Z

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Observation 0ab5acf6-0888-4454-b346-171e13b60404 · outbound

This paper cites You only look once: Unified, real-time object detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection You only look once: Unified, real-time object detection,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.643568Z

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Observation ed3ed5d3-8fc2-4539-a0a5-351eca2dd418 · outbound

This paper cites Yolov3: An incremental improvement,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Yolov3: An incremental improvement,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.631425Z

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Observation a8a28586-ece7-43d3-b581-dbd0fbdfa372 · outbound

This paper cites Yolov4: Optimal speed and accuracy of object detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Yolov4: Optimal speed and accuracy of object detection,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.619381Z

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Observation eec3838f-fecb-407c-9724-16d273a689c6 · outbound

This paper cites Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.607544Z

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Observation 3b0fe533-fe7a-42b8-abfe-f5a1028db1a5 · outbound

This paper cites Yolox: Exceeding yolo series in 2021,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Yolox: Exceeding yolo series in 2021,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.595339Z

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Observation 390f6476-b973-4bb0-98d5-e4ba4ef18419 · outbound

This paper cites Focal loss for dense object detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Focal loss for dense object detection,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.766871Z

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Observation d2bc2eaf-b452-4bf6-9bd8-b32661586694 · outbound

This paper cites Fcos: Fully convolutional one- stage object detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Fcos: Fully convolutional one- stage object detection,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.576815Z

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Observation 0f410ac6-32e0-419d-bf8a-0b425226922a · outbound

This paper cites Centernet: Keypoint triplets for object detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Centernet: Keypoint triplets for object detection,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.564445Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4dd5877f-09f6-4207-8c7f-3fd93858f8d8 · outbound

This paper cites Ship detection in large-scale sar images via spatial shuffle-group enhance attention,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Ship detection in large-scale sar images via spatial shuffle-group enhance attention,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.552329Z

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Observation 84c6d33f-e195-4c6e-b567-ca7fb1d0172a · outbound

This paper cites An improved deep neural network for small-ship detection in sar imagery,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection An improved deep neural network for small-ship detection in sar imagery,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.538495Z

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Observation 79215663-e52b-455c-a5b4-683bc9e827b7 · outbound

This paper cites High-speed lightweight ship detection algorithm based on yolo-v4 for three-channels rgb sar image,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection High-speed lightweight ship detection algorithm based on yolo-v4 for three-channels rgb sar image,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.526470Z

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Observation d164e3ca-8314-46f8-a4c6-e0f6f234bd00 · outbound

This paper cites Feature pyramid networks for object detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Feature pyramid networks for object detection,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.512285Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 66e3dd21-dfb3-48bc-a07c-fc63817cabf6 · outbound

This paper cites Path aggregation network for instance segmentation,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Path aggregation network for instance segmentation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.499243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7663d16b-e600-4151-9ba1-ef5280b55175 · outbound

This paper cites Ship detection in sar images based on an improved faster r-cnn,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Ship detection in sar images based on an improved faster r-cnn,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.486630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1236ac63-eaa6-4770-92fc-4bb98bc7eefa · outbound

This paper cites Hrsid: A high-resolution sar images dataset for ship detection and instance segmentation,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Hrsid: A high-resolution sar images dataset for ship detection and instance segmentation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.475114Z

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Observation 7a7e8cc0-1645-413f-ad15-ea0bc2647d4e · outbound

This paper cites Ls-ssdd-v1.0: A deep learning dataset dedicated to small ship detection from large-scale sentinel-1 sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Ls-ssdd-v1.0: A deep learning dataset dedicated to small ship detection from large-scale sentinel-1 sar images,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.464005Z

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Observation 59a9534d-5677-490d-8b23-29e1221119fb · outbound

This paper cites Srt- net: Scattering region topology network for oriented ship detection in large-scale sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Srt- net: Scattering region topology network for oriented ship detection in large-scale sar images,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.452719Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6867cae4-617b-4914-ad0e-fbd3d9ae6b93 · outbound

This paper cites Dense attention pyramid networks for multi-scale ship detection in sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Dense attention pyramid networks for multi-scale ship detection in sar images,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.819836Z

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Observation 8a806a5e-5eb8-4139-9b9d-2410ab76fb00 · outbound

This paper cites Cbam: Convolutional block attention module,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Cbam: Convolutional block attention module,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.434395Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c5776d9e-78ef-4433-ad7e-fd282190f067 · outbound

This paper cites A robust one-stage detector for multiscale ship detection with complex background in massive sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection A robust one-stage detector for multiscale ship detection with complex background in massive sar images,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.422211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 78a60491-0388-461e-8dcc-250fbb8980ba · outbound

This paper cites Banet: A balance attention network for anchor-free ship detection in sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Banet: A balance attention network for anchor-free ship detection in sar images,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.401652Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5b94d8be-b573-45c5-93f3-a4b56c5fbcbe · outbound

This paper cites Multi scale ship detection based on attention and weighted fusion model for high resolution sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Multi scale ship detection based on attention and weighted fusion model for high resolution sar images,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.388814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation da87627e-b88b-43aa-8cef-3aa566529e5f · outbound

This paper cites Coordinate attention for efficient mobile network design,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Coordinate attention for efficient mobile network design,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.375477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fa956744-3aa3-4d42-a109-db151edd8e94 · outbound

This paper cites Ppa-net: Pyramid pooling attention network for multi-scale ship detection in sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Ppa-net: Pyramid pooling attention network for multi-scale ship detection in sar images,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.363973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 456125ec-f911-40d8-81c1-0df0d61289f5 · outbound

This paper cites Imagpose: A unified conditional framework for pose-guided person generation,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Imagpose: A unified conditional framework for pose-guided person generation,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.847402Z

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Observation 673990fe-71ce-47dd-a2f0-1ac06e2ab9b2 · outbound

This paper cites IMAGDressing-v1: Customizable Virtual Dressing.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection IMAGDressing-v1: Customizable Virtual Dressing

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.851619Z

Source-reported events for the cited work

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Observation 32b855da-7a82-41b8-ad83-3729d9667550 · outbound

This paper cites Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.856077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11d8f04c-c8d2-4b4c-be15-c8af8c1c3674 · outbound

This paper cites Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.860254Z

Source-reported events for the cited work

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Observation 88ff9593-10fc-4503-84ba-61d912a399d5 · outbound

This paper cites Non-local neural net- works,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Non-local neural net- works,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.340238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation df243609-bdea-4855-a03f-642f4022a228 · outbound

This paper cites Gcnet: Non-local networks meet squeeze-excitation networks and beyond,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Gcnet: Non-local networks meet squeeze-excitation networks and beyond,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.326785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6cb6e9d2-c9ca-43af-adfe-35dd0da10008 · outbound

This paper cites Dual attention network for scene segmentation,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Dual attention network for scene segmentation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.315873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 15ad21e9-8aed-47fb-b697-9d74043d5718 · outbound

This paper cites Ccnet: Criss-cross attention for semantic segmentation,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Ccnet: Criss-cross attention for semantic segmentation,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.303512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cea8007f-d844-4b9f-8a59-8c5fbb230138 · outbound

This paper cites Squeeze and excitation rank faster r-cnn for ship detection in sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Squeeze and excitation rank faster r-cnn for ship detection in sar images,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.291434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 66cf86d4-0edc-46e3-b190-91d4debdc827 · outbound

This paper cites Dynamic r-cnn: Towards high quality object detection via dynamic training.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Dynamic r-cnn: Towards high quality object detection via dynamic training

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.882313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9280b19-932d-4fcf-aa70-18cfabe274fa · outbound

This paper cites Rethinking classification and localization for object detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Rethinking classification and localization for object detection,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.277818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e5e8cc99-c1c8-485f-8d06-f8a8e881a055 · outbound

This paper cites A cascade rotated anchor-aided detector for ship detection in remote sensing images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection A cascade rotated anchor-aided detector for ship detection in remote sensing images,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.262743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 90a8381b-3ec3-4dcc-aafb-66034692766d · outbound

This paper cites Fcos: Fully convolutional one- stage object detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Fcos: Fully convolutional one- stage object detection,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.250621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ab8b660b-e8a4-428d-9dfa-81de3d46f646 · outbound

This paper cites Learning to match anchors for visual object detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Learning to match anchors for visual object detection,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.236954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0573b94f-a2e4-4010-a175-588862395aec · outbound

This paper cites Frequency- adaptive learning for sar ship detection in clutter scenes,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Frequency- adaptive learning for sar ship detection in clutter scenes,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.219674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d8c84053-2301-41dc-b445-4574152fd753 · outbound

This paper cites Yolov8: A novel object detection algorithm with enhanced performance and robustness,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Yolov8: A novel object detection algorithm with enhanced performance and robustness,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.905100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6be40b7a-877d-4032-bb90-a5171bb70b87 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection YOLOX: Exceeding YOLO Series in 2021

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-10T21:10:48.909668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be6f2af8-5de4-4611-95d0-675c2cdfc847 · outbound

This paper cites A sidelobe-aware small ship detection network for synthetic aperture radar imagery,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection A sidelobe-aware small ship detection network for synthetic aperture radar imagery,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.165165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c17e44df-7276-4c61-b553-c94ba6dfe927 · outbound

This paper cites Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.154019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a9f2f4c7-b819-4ba8-b897-6336b6d43fa1 · outbound

This paper cites Atsd: Anchor-free two-stage ship detection based on feature enhancement in sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Atsd: Anchor-free two-stage ship detection based on feature enhancement in sar images,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.141902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 55874331-5036-4a26-a6ff-ba7d856bfd67 · outbound

This paper cites Dbw-yolo: A high-precision sar ship detection method for complex environments,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Dbw-yolo: A high-precision sar ship detection method for complex environments,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.129752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 88df208a-69b7-49e9-9636-935819d8bb5b · outbound

This paper cites A rotational libra r-cnn method for ship detection,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection A rotational libra r-cnn method for ship detection,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.117696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d83f3438-4e9a-4c5c-ad16-5000efc74291 · outbound

This paper cites Deformable convolutional networks,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Deformable convolutional networks,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.102627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f16ebd42-d44c-4819-808c-89708ec3bbca · outbound

This paper cites Msif: Multisize inference fusion-based false alarm elimination for ship detection in large-scale sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Msif: Multisize inference fusion-based false alarm elimination for ship detection in large-scale sar images,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.089869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d4be33db-336b-45eb-8f68-4a64602fc855 · outbound

This paper cites Lemon-yolo: an efficient object detection method for lemons in the natural environment,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Lemon-yolo: an efficient object detection method for lemons in the natural environment,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.068350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5c6930bc-058e-447c-8291-0491b662340a · outbound

This paper cites Sii-net: Spatial information integration network for small target detection in sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection Sii-net: Spatial information integration network for small target detection in sar images,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.055153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e0246c4f-27d2-418a-8ec8-c1a93ac88979 · outbound

This paper cites A high-effective implementation of ship detector for sar images,.

Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection A high-effective implementation of ship detector for sar images,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:10:49.039980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Outbound references

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