Paper Citation Record · LEDGER

Active Learning for UAV-based Semantic Mapping

As of 16 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:1908.11157.

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

pith.paper-citation-record.v1
1908.11157 v2

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:26:02.877320Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:38:43.540276Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T15:38:46.819386Z

Reference resolution

25 of 25 outbound references displayed

verified exact4
verified fuzzy13
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1cc0358f-056d-46aa-abd7-10d700227bf8 · outbound

This paper cites The ﬁshyscapes benchmark: Measuring blind spots in semantic segmentation,.

Active Learning for UAV-based Semantic Mapping The ﬁshyscapes benchmark: Measuring blind spots in semantic segmentation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.288183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b6530c2a-c4a9-4009-93b0-762b9bab375c · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

Active Learning for UAV-based Semantic Mapping A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T10:26:02.797623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 076cb9ba-13f3-436a-8dfc-fcb56740a49f · outbound

This paper cites Uncertainty in deep learning,.

Active Learning for UAV-based Semantic Mapping Uncertainty in deep learning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.279478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 82dd1c2d-4da4-43ec-a1cc-392074465beb · outbound

This paper cites What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?.

Active Learning for UAV-based Semantic Mapping What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T10:26:02.804464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67bacf98-bb89-4ba9-8150-3fb28d59a19e · outbound

This paper cites Distance-based Confidence Score for Neural Network Classifiers.

Active Learning for UAV-based Semantic Mapping Distance-based Confidence Score for Neural Network Classifiers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T10:26:02.808955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c499fdf-dec3-4514-a8dd-373247687e16 · outbound

This paper cites Deep k-nearest neighbors: Towards conﬁdent, interpretable and robust deep learning,.

Active Learning for UAV-based Semantic Mapping Deep k-nearest neighbors: Towards conﬁdent, interpretable and robust deep learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.271742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f39a70bc-79b1-4072-9178-101d90c323cc · outbound

This paper cites Genera- tive probabilistic novelty detection with adversarial autoen- coders,.

Active Learning for UAV-based Semantic Mapping Genera- tive probabilistic novelty detection with adversarial autoen- coders,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.263607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0d376e3b-ed35-4d7a-a065-7cbbbaf82743 · outbound

This paper cites Detecting the unexpected via image resynthesis,.

Active Learning for UAV-based Semantic Mapping Detecting the unexpected via image resynthesis,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.255361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 946fd4ac-64f8-48b0-a6e8-2f8922d6e1ca · outbound

This paper cites Cost- Effective active learning for deep image classiﬁcation,.

Active Learning for UAV-based Semantic Mapping Cost- Effective active learning for deep image classiﬁcation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.246066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 46487fd4-6ddd-446a-8977-dd3896c28e28 · outbound

This paper cites Deep bayesian active learning with image data,.

Active Learning for UAV-based Semantic Mapping Deep bayesian active learning with image data,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.236795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ff5c530e-0872-401d-917c-d2f018234dc1 · outbound

This paper cites Adaptive continuous-space informative path planning for online environmental monitoring,.

Active Learning for UAV-based Semantic Mapping Adaptive continuous-space informative path planning for online environmental monitoring,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.227351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a0e9887a-1cd4-45bf-87e2-c4d771a5119e · outbound

This paper cites Sampling- based robotic information gathering algorithms,.

Active Learning for UAV-based Semantic Mapping Sampling- based robotic information gathering algorithms,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.216795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 06cd325a-2752-4751-993e-7c0b6b782138 · outbound

This paper cites Sampling- based incremental information gathering with applications to robotic exploration and environmental monitoring,.

Active Learning for UAV-based Semantic Mapping Sampling- based incremental information gathering with applications to robotic exploration and environmental monitoring,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.206143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 540eb701-1cf8-4311-9697-195a357ee306 · outbound

This paper cites Route planning for active classiﬁcation with uavs,.

Active Learning for UAV-based Semantic Mapping Route planning for active classiﬁcation with uavs,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T10:26:02.847937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03aed379-9ed9-46ec-b56e-6258a59f4d15 · outbound

This paper cites Receding horizon path planning for 3d explo- ration and surface inspection,.

Active Learning for UAV-based Semantic Mapping Receding horizon path planning for 3d explo- ration and surface inspection,

Reference 15

Resolution: verified exact; doi, observed 2026-08-14T10:26:02.920305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0f2daac0-c19a-4b30-adeb-3a005d4134bb · outbound

This paper cites Planning and acting in partially observable stochastic domains,.

Active Learning for UAV-based Semantic Mapping Planning and acting in partially observable stochastic domains,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.196534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation aa04d546-eb8f-4214-a38e-bb8b86906d18 · outbound

This paper cites an unresolved cited work.

Active Learning for UAV-based Semantic Mapping Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:26:03.186442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b6651506-beb7-4dc4-9a57-54a1ce71764f · outbound

This paper cites Safe visual navigation via deep learning and novelty detection,.

Active Learning for UAV-based Semantic Mapping Safe visual navigation via deep learning and novelty detection,

Reference 18

Resolution: verified exact; doi, observed 2026-08-14T10:26:02.909497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9419e753-c56f-44dd-867e-8b79876ca115 · outbound

This paper cites Algorithms for Semantic Segmentation of Multispectral Remote Sensing Imagery using Deep Learning.

Active Learning for UAV-based Semantic Mapping Algorithms for Semantic Segmentation of Multispectral Remote Sensing Imagery using Deep Learning

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:26:03.052949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f5d107ac-21e8-42d7-b111-46bc1519108b · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

Active Learning for UAV-based Semantic Mapping Fully convolutional networks for semantic segmentation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.177124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation baaa9706-d679-411d-bdfb-8ba0c1c6a590 · outbound

This paper cites Very deep convolutional networks for Large-Scale image recognition,.

Active Learning for UAV-based Semantic Mapping Very deep convolutional networks for Large-Scale image recognition,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:26:03.165401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fa3e9534-b58d-4e33-b6ee-c4bcb52968d2 · outbound

This paper cites Modular sensor fusion for semantic segmentation,.

Active Learning for UAV-based Semantic Mapping Modular sensor fusion for semantic segmentation,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T10:26:02.877320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f533da22-c1d7-494a-bd9f-409f8ffb8af0 · outbound

This paper cites an unresolved cited work.

Active Learning for UAV-based Semantic Mapping Unresolved cited work

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-14T10:26:02.870871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18f6bd72-699d-4830-b89f-c706db1e3b43 · outbound

This paper cites Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning.

Active Learning for UAV-based Semantic Mapping Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-14T10:26:02.815968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02b33d3b-de4d-4c7e-9d42-00df2546d3a1 · outbound

This paper cites an unresolved cited work.

Active Learning for UAV-based Semantic Mapping Unresolved cited work

Reference 2019

Resolution: verified exact; doi, observed 2026-08-14T10:26:02.930551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation 773879b1-3d54-4932-8d55-729459147786 · inbound

Semantically-driven Deep Reinforcement Learning for Inspection Path Planning cites this paper.

Semantically-driven Deep Reinforcement Learning for Inspection Path Planning Active Learning for UAV-based Semantic Mapping

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:38:46.983210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.