Pith. sign in

Paper Citation Record · LEDGER

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture

As of 14 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2607.09835.

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

pith.paper-citation-record.v1
2607.09835 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T15:11:58.861492Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

  • verified exact24
  • verified fuzzy0
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cab22f85-1276-4384-a128-dc24981cccfa · outbound

This paper cites World Aquaculture 2020 – A Brief Overview; FAO Fisheries and Aquaculture Circular No.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture World Aquaculture 2020 – A Brief Overview; FAO Fisheries and Aquaculture Circular No

Reference 1

Resolution
verified exact
doi, observed 2026-07-14T15:20:36.877269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:893dc2171920f51ae995e59177c72daf3beb107d8130fc3281144d93d38e4506

Observation 001692b3-ffb4-4ef4-88f9-84fdf0d20fe4 · outbound

This paper cites Recirculating aquaculture systems (RAS): Environmental solution and climate change adaptation.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Recirculating aquaculture systems (RAS): Environmental solution and climate change adaptation

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.893012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:5c21155f90528b307c4ece73f8886be01832555f2b53f22673737e2c8b85c89b

Observation 90f995d3-12fc-4ca8-a380-e631e27a9617 · outbound

This paper cites Environmental performance of marine net-pen aquaculture in the United States.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Environmental performance of marine net-pen aquaculture in the United States

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.862809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:e2642b1b1514eb13019eeb96b7d58de59d9c8914a6c5d0539c7a8672a402bdd1

Observation 3d8b8c4e-679e-4f15-bc2c-8285c2cc464d · outbound

This paper cites Aquaculture: Global status and trends.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Aquaculture: Global status and trends

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.856143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:ef0b33ea969c7c742b405bc1871c2e0cfc8f02d25057affd59e396899f4cd420

Observation 6f6ffde1-b39d-411c-ac3b-ff721a159ad9 · outbound

This paper cites an unresolved cited work.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Unresolved cited work

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:fcb1c0d9ae7d86b9afb09cfd7e29c964dd3a244a8bdf9d99221c23a6dbcd20f6

Observation a55ed840-fc32-4621-bc76-8fd0daa9b7a4 · outbound

This paper cites The economics of recirculating aquaculture systems.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture The economics of recirculating aquaculture systems

Reference 6

Resolution
verified exact
doi, observed 2026-07-14T15:20:36.867411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:bd1db944ee0fff40f0b900f86ff6a1a2a5c088a4a234692aafbfefc0f6da5535

Observation 2654d3c9-e86e-4fda-b942-fb2fb46b49a9 · outbound

This paper cites Precision aquaculture.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Precision aquaculture

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.873195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:df25283ef63f881bf42e8138bd41df27aab5605b06f96586f7760a9036669d47

Observation b5c88d34-ab69-4a52-82f9-65ae2775d858 · outbound

This paper cites Precision fish farming: A new framework to improve production in aquaculture.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Precision fish farming: A new framework to improve production in aquaculture

Reference 8

Resolution
verified exact
doi, observed 2026-07-14T15:20:36.885718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:75eda487fff31e6d55a8b9a9bed27b6c6fd1bc96297cf3e34ce58889fd98e48b

Observation 461fd097-bbf2-454d-9cb7-704a8b2afebc · outbound

This paper cites Detection of residual feed in aquaculture using YOLO and Mask RCNN.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Detection of residual feed in aquaculture using YOLO and Mask RCNN

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.849923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:00a2dcd17c8dbf8e6e047fa5014bbf73e67fa990137c650abc707fa7522143f1

Observation a15f8093-07cf-4c07-9664-df2399b7b466 · outbound

This paper cites Effects of image data quality on a convolutional neural network trained in-tank fish detection model for recirculating aquaculture systems.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Effects of image data quality on a convolutional neural network trained in-tank fish detection model for recirculating aquaculture systems

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.834321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:61f4c2ea689a36a5f06ff1e597d651d2001305bd93f6b6488108d5112239b2df

Observation fe58c82f-eb9a-43d1-aa95-1958a1eae771 · outbound

This paper cites Real-time detection of uneaten feed pellets in underwater images for aquaculture using an improved YOLO-V4 network.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Real-time detection of uneaten feed pellets in underwater images for aquaculture using an improved YOLO-V4 network

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.815276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:701440a66d00cdc2f178af06aca50a95334b35424ace3cea255d87192979dd96

Observation 517dc194-cc71-4ef3-85db-442f99fab0f1 · outbound

This paper cites Real -time detection and tracking of fish abnormal behavior based on improved YOLOV5 and SiamRPN++.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Real -time detection and tracking of fish abnormal behavior based on improved YOLOV5 and SiamRPN++

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.789980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:bef9fec0b6fd4e84546798cccde162d75f1069da5b8f9250fa8994673938af9d

Observation 104530c8-7a86-432c-ae66-9005a82f63d2 · outbound

This paper cites Abnormal behavior monitoring method of Larimichthys crocea in recirculating aquaculture system based on computer vision.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Abnormal behavior monitoring method of Larimichthys crocea in recirculating aquaculture system based on computer vision

Reference 13

Resolution
verified exact
doi, observed 2026-07-14T15:20:36.796511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:1755db9d7f2eee7d795c72f4ebaa4bf8d51d63b5398c332550afa09b958b4741

Observation 3358e002-b697-4bfe-a8fb-5f57c7458a40 · outbound

This paper cites Fully automatic system for fish biomass estimation based on deep neural network.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Fully automatic system for fish biomass estimation based on deep neural network

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.809895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:b9548113e502ca01fb41c70a02b1325d7affb38107cbdd93eef94d5354558a68

Observation 1739fc37-9cd0-4495-9172-7f3b6c297b84 · outbound

This paper cites Rapid detection of fish with SVC symptoms based on machine vision combined with a NAM-YOLO v7 hybrid model.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Rapid detection of fish with SVC symptoms based on machine vision combined with a NAM-YOLO v7 hybrid model

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.822375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:19c55c5a83bae5ce7e5769e67b6599ede7eaad67b8f839d58cbe7cbf6bc49c56

Observation e56f186c-3c66-4b4d-96e9-4e92fd1a339e · outbound

This paper cites MortCam: An artificial intelligence-aided fish mortality detection and alert system for recirculating aquaculture.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture MortCam: An artificial intelligence-aided fish mortality detection and alert system for recirculating aquaculture

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.831823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:560d2f02649969c82de09860243b6fa4099f05cdea5864aa46c479987e2727b4

Observation ec894ce5-d340-49e6-bbe2-6610bfc063b0 · outbound

This paper cites An automated lightweight approach for detecting dead fish in a recirculating aquaculture system.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture An automated lightweight approach for detecting dead fish in a recirculating aquaculture system

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.858266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:3b480a7790b7b22fce706a71cadf04449e02997606b3bb442d43908f155b4063

Observation 469a142f-1188-4cc7-b9de-56d96197e0ab · outbound

This paper cites Inspection operations and hole detection in fish net cages through a hybrid underwater intervention system using deep learning techniques.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Inspection operations and hole detection in fish net cages through a hybrid underwater intervention system using deep learning techniques

Reference 18

Resolution
verified exact
doi, observed 2026-07-14T15:20:36.803924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:e2f79c2fcab0115ef102e694ed77131610b8ba20ce31887fc08bc1f5516045c6

Observation d14b0f1a-5d3c-45eb-825b-504689a38009 · outbound

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

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Faster R -CNN: Towards real-time object detection with region proposal networks

Reference 19

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:b9d582f2465cc08ca018eeb45ad19e87c629be058eaa226dd4e8f411de8ea4c0

Observation 34b4ff1a-0633-4523-b38e-76a373e5dd81 · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Rich feature hierarchies for accurate object detection and semantic segmentation

Reference 20

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:b4c6059990f26fa2b94836d2dca50ed8fb791f69d412530d5944af474998678f

Observation 48448bf0-791e-4db5-8465-302708acb711 · outbound

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

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture You only look once: Unified, real-time object detection

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:7e755d4a71c580aa44ff87014cf6a0b0a5daa9e9619a498402f72662951a4a76

Observation 3ba931b6-8617-4933-a401-c661f9297a45 · outbound

This paper cites Making Faster R-CNN Faster! Available online: https://jkjung-avt.github.io/making-frcn- faster/ (ac cessed on 15 April 2026 ).

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Making Faster R-CNN Faster! Available online: https://jkjung-avt.github.io/making-frcn- faster/ (ac cessed on 15 April 2026 )

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:f0cb5800ebb220646f2f6d42172cb7dac68f8ead52426f83cebb2e1757733b4d

Observation 231f33b5-b322-4224-8eef-8752b66176fb · outbound

This paper cites Progress in object detection: An in- depth analysis of methods and use cases.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Progress in object detection: An in- depth analysis of methods and use cases

Reference 23

Resolution
verified exact
doi, observed 2026-07-14T15:20:36.846513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:daa3cd0152a4de83fcdcf5ae52bd954c5299d2f24024391a291b5fe95e3ebc49

Observation e4e6f7bd-9ce4-438a-8307-fda481e40131 · outbound

This paper cites YOLOv3: An Incremental Improvement.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture YOLOv3: An Incremental Improvement

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:a075b6bf81f3fd45fee4c13e2c0f3b64af8b1fc847440bddd275ba704f02ff56

Observation e3e6d748-fcce-401c-9c43-6e3f643681b0 · outbound

This paper cites Ultralytics YOLOv5 ; Ultralytics, 2020.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Ultralytics YOLOv5 ; Ultralytics, 2020

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:3cca8ef329b855f466deda28acd516954a19f471a132e138efc939f318ddf1ed

Observation 865696b0-8fc2-4a0f-897e-898b314c5141 · outbound

This paper cites Chaurasia, A.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Chaurasia, A

Reference 26

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:86ba33eacfd401f4bf409cceebc24e8e781dcb4ebca9345f12cbe21d1541ecf5

Observation c7aff049-7ccd-4c57-a146-715162f0ba46 · outbound

This paper cites A novel detection model and platform for dead juvenile fish from the perspective of multi-task.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture A novel detection model and platform for dead juvenile fish from the perspective of multi-task

Reference 27

Resolution
verified exact
doi, observed 2026-07-14T15:20:36.765987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:78a3e628f0e12a3989f0d3809d565ebf9cb4414d9f9829dd34f8534cf1a73b97

Observation 0e9a79cc-fe01-4a7d-b154-b35a25869305 · outbound

This paper cites Real -time detection of dead fish for unmanned aquaculture by YOLOv8-based UA V.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Real -time detection of dead fish for unmanned aquaculture by YOLOv8-based UA V

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.767495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:6a712e5f3f472b48cd23f4281a9066f3bbd052a62dfaf486510acf2341fc0002

Observation 8f0b4091-6b53-4a1c-b93f-4b9a79a4744b · outbound

This paper cites YOLO in precision aquaculture: A decadal bibliometric and systematic review of applications, architectural adaptations, and deployment challenges.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture YOLO in precision aquaculture: A decadal bibliometric and systematic review of applications, architectural adaptations, and deployment challenges

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-07-14T15:20:36.787035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:2d61100851a0746e7e0a2058d68d39d55eb17eb129e3624f3aea9846c061b369

Observation 4cc9eac6-1382-479a-bedc-763e8823deb8 · outbound

This paper cites Analyzing fish detection and classification in IoT-based aquatic ecosystems through deep learning.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Analyzing fish detection and classification in IoT-based aquatic ecosystems through deep learning

Reference 30

Resolution
verified exact
doi, observed 2026-07-14T15:20:36.760205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:307e3071da26bc214477b695a4d571b38c6cd6e09a97c254398d9b77755d3c42

Observation 9a2bf85f-2d6f-49d8-9ab7-d76c699d8de0 · outbound

This paper cites IoT-enabled communication network for real-time disease alerts in smart aquaculture systems.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture IoT-enabled communication network for real-time disease alerts in smart aquaculture systems

Reference 31

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:ef581415e956e05763dba20eaae45b52206b1d5ae6c36a9d5f1a8d3734afd00a

Observation 359003d4-8a20-4f09-b42e-1d8247070671 · outbound

This paper cites Ultralytics YOLO26 ; Ultralytics, 2026.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Ultralytics YOLO26 ; Ultralytics, 2026

Reference 32

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:af948611eba7812398c0528bc57bd06a3e4fdece77b587b9fad25ad419b9b95c

Observation bf02bc27-4161-401a-8eb4-adcfad8756df · outbound

This paper cites Jocher, G.; Qiu, J.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Jocher, G.; Qiu, J

Reference 33

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:7ae72dd5e4e7fc467aed4595bbafa346d297f3e05754cf1788401650f3e28c1f

Observation fbc2408f-1011-4168-ab66-6bc9b6782f5e · outbound

This paper cites Ultralytics YOLO evolution: An overview of YOLO26, YOLO11, YOLOv8 and YOLOv5 object detectors for computer vision and pattern recognition.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Ultralytics YOLO evolution: An overview of YOLO26, YOLO11, YOLOv8 and YOLOv5 object detectors for computer vision and pattern recognition

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:5613994e90cd97fa036bf98432f4a44c2e519b960e861258272afcae5b545b86

Observation 9984ec1a-6810-4498-8931-32c9e1d8f96d · outbound

This paper cites YOLO26: Key architectural enhancements and performance benchmarking for real-time object detection.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture YOLO26: Key architectural enhancements and performance benchmarking for real-time object detection

Reference 35

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:a2c76d567bcf2597d1e2b12ef3baf67456c24093b01a3112e899595241b7973d

Observation 6fed29dc-5104-4ff5-931f-a621c42cc449 · outbound

This paper cites YOLOv11: An Overview of the Key Architectural Enhancements.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture YOLOv11: An Overview of the Key Architectural Enhancements

Reference 36

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:baf22a3283f5e4a0c5edff839739508451a52e101f1e0b92401262e7a774a9c8

Observation 7dd45778-87b9-40a6-b1ec-a60fed030102 · outbound

This paper cites YOLOv10: Real-time end-to-end object detection.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture YOLOv10: Real-time end-to-end object detection

Reference 37

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:197cebe94f693acbc94e7ec7c98bcbea5345b3358043ffb4f097d6452bf31714

Observation de41504c-6e15-47cd-8c8d-aca10b8b0881 · outbound

This paper cites Improving smart home surveillance through YOLO model with transfer learning and quantization for enhanced accuracy and efficiency.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Improving smart home surveillance through YOLO model with transfer learning and quantization for enhanced accuracy and efficiency

Reference 38

Resolution
verified exact
doi, observed 2026-07-14T15:20:36.753325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:02d66ff75bb67738f5e9c88da8f59d1e5a340e658371f58975b94cb68937c22e

Observation 290239f1-3b8a-4be6-9f06-c14466b872ef · outbound

This paper cites YOLO26: An analysis of NMS-free end to end framework for real- time object detection.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture YOLO26: An analysis of NMS-free end to end framework for real- time object detection

Reference 39

Resolution
unresolved
no resolver link, observed 2026-07-14T15:11:58.861492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:5f91bcc83634876c73c4e53e1fb1e67be335323da04c46a4b634c843b337c357

Observation b43c483c-cdc7-4a5b-b189-552264dc7818 · outbound

This paper cites Accelerating Deep Learning Model Inference on Arm CPUs with Ultra-Low Bit Quantization and Runtime.

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture Accelerating Deep Learning Model Inference on Arm CPUs with Ultra-Low Bit Quantization and Runtime

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-07-14T15:20:36.799962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-14T15:11:58.861492Z digest=sha256:e7930edd4508329dbd3f88331c2dd4d7c0f8214f28f0aac91cf61169084ccc82

Pith citing papers

No inbound Pith citation observations are available.