Paper Citation Record · LEDGER

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation

As of 7 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2606.01271.

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

pith.paper-citation-record.v1
2606.01271 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T17:00:07.051978Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

38 of 38 outbound references displayed

verified exact4
verified fuzzy0
unresolved34
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 08ff4e3b-ae7e-4cff-b870-d4611b0c37c4 · outbound

This paper cites Telecommunication Systems for Small Satellites Operating at High Frequencies: A Review.Information, 11(5):258, 2020.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Telecommunication Systems for Small Satellites Operating at High Frequencies: A Review.Information, 11(5):258, 2020

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dbdc9bf-4302-4725-875a-22f8c7dc3e3d · outbound

This paper cites PicoSAM2: Low-Latency Segmentation In-Sensor for Edge Vision Appli- cations.IEEE Sensors Conference, 2025.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation PicoSAM2: Low-Latency Segmentation In-Sensor for Edge Vision Appli- cations.IEEE Sensors Conference, 2025

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e313e83-5e31-40e4-9f9c-ed1cb0311a83 · outbound

This paper cites PicoSAM3: Real-Time In-Sensor Region-of-Interest Segmentation.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation PicoSAM3: Real-Time In-Sensor Region-of-Interest Segmentation

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-06-28T17:02:24.005846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ed54efa6-c3ae-4651-b8e1-7bb937f8ce1c · outbound

This paper cites Tiny- Tracker: Ultra-Fast and Ultra-Low-Power Edge Vision In-Sensor for Gaze Estima- tion.IEEE Sensors, 2023.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Tiny- Tracker: Ultra-Fast and Ultra-Low-Power Edge Vision In-Sensor for Gaze Estima- tion.IEEE Sensors, 2023

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 546afc36-c33f-4da2-ae92-12413cf1b032 · outbound

This paper cites TinyGLASS: Real-Time Self-Supervised In-Sensor Anomaly Detection.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation TinyGLASS: Real-Time Self-Supervised In-Sensor Anomaly Detection

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-21T02:20:36.390785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3b2847e1-7836-4c66-8f1f-5b010b7a1c99 · outbound

This paper cites The CubeSat mission FUTURE: A preliminary analysis to validate the on-board autonomous orbit determination.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation The CubeSat mission FUTURE: A preliminary analysis to validate the on-board autonomous orbit determination

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e77931d1-ccdf-4c4e-880d-9dd7d244cbfc · outbound

This paper cites Performance Analysis of Edge and In-Sensor AI Processors: A Comparative Review.arXiv preprint arXiv:2603.08725, 2026.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Performance Analysis of Edge and In-Sensor AI Processors: A Comparative Review.arXiv preprint arXiv:2603.08725, 2026

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-28T17:02:24.010711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7fee1f2-7247-4ca0-a765-ef713e3ec24c · outbound

This paper cites A Machine Learning-Oriented Survey on Tiny Machine Learning.IEEE Access, 12:23406–23426, 2024.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation A Machine Learning-Oriented Survey on Tiny Machine Learning.IEEE Access, 12:23406–23426, 2024

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86cb4a04-aa6a-4439-a123-5052b615d0d4 · outbound

This paper cites TinyML Enhances CubeSat Mission Capa- bilities.arXiv preprint arXiv:2603.20174, 2026.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation TinyML Enhances CubeSat Mission Capa- bilities.arXiv preprint arXiv:2603.20174, 2026

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-28T17:02:24.007357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f71ac204-cd26-4f38-90a0-d9766d4c1e5b · outbound

This paper cites Opportunities and challenges of on-board AI-based image recognition for small satellite Earth observation missions.Advances in Space Re- search, 75(9):6734–6751, 2025.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Opportunities and challenges of on-board AI-based image recognition for small satellite Earth observation missions.Advances in Space Re- search, 75(9):6734–6751, 2025

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a00443d-43bb-4828-aca7-d37e357720eb · outbound

This paper cites Crisp, P.C.E.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Crisp, P.C.E

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61d85b1d-e0bc-47b9-baaf-d73ff9ef2e14 · outbound

This paper cites Mmitigating challenges of the space environment for onboard artificial intelligence: Design overview of the imaging payload on spirit.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Mmitigating challenges of the space environment for onboard artificial intelligence: Design overview of the imaging payload on spirit

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f6c1e5d-6f49-4b44-8f2b-60b1cb8382bb · outbound

This paper cites Review on Hardware Devices and Software Techniques Enabling Neural Network Inference Onboard Satellites.Remote Sens- ing, 16(21):3957, 2024.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Review on Hardware Devices and Software Techniques Enabling Neural Network Inference Onboard Satellites.Remote Sens- ing, 16(21):3957, 2024

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5520c6a2-a484-4559-879b-fabc042e9b23 · outbound

This paper cites Earth+: On-Board Satellite Imagery Compression Leveraging Historical Earth Ob- servations.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Earth+: On-Board Satellite Imagery Compression Leveraging Historical Earth Ob- servations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 542f9ea9-221d-4b90-b760-60e2c48c53fd · outbound

This paper cites Advancing Earth observation: a survey on AI-powered image processing in satellites.European Journal of Remote Sensing, 58(1), 2025.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Advancing Earth observation: a survey on AI-powered image processing in satellites.European Journal of Remote Sensing, 58(1), 2025

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3d0cb43-13c3-436f-b1f6-340ac1afaf71 · outbound

This paper cites 9.6 A 1/2.3inch 12.3Mpixel with On-Chip 4.97TOPS/W CNN Processor Back-Illuminated Stacked CMOS Image Sensor.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation 9.6 A 1/2.3inch 12.3Mpixel with On-Chip 4.97TOPS/W CNN Processor Back-Illuminated Stacked CMOS Image Sensor

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb0c8116-b036-46fb-9a1c-6a939bb9e890 · outbound

This paper cites Artificial intelligence for satellite com- munication: A review.Intelligent and Converged Networks, 2(3):213–243, 2021.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Artificial intelligence for satellite com- munication: A review.Intelligent and Converged Networks, 2(3):213–243, 2021

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fc4e7d8-cbb8-44e5-bf47-d5c5132e54a3 · outbound

This paper cites Convolutional Neural Networks for On-Board Cloud Screening.Remote Sensing, 11(12):1417, 2019.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Convolutional Neural Networks for On-Board Cloud Screening.Remote Sensing, 11(12):1417, 2019

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4463a8b6-a1f6-4ee9-8b43-05aa3204e01c · outbound

This paper cites CloudScout: A Deep Neural Net- work for On-Board Cloud Detection on Hyperspectral Images.Remote Sensing, 12(14):2205, 2020.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation CloudScout: A Deep Neural Net- work for On-Board Cloud Detection on Hyperspectral Images.Remote Sensing, 12(14):2205, 2020

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bad54398-c0d8-4463-bf4f-ca596d0fa2d7 · outbound

This paper cites The Phi-Sat-1 Mission: The First On-Board Deep Neural Network Demonstrator for Satellite Earth Observation.IEEE Transactions on Geoscience and Remote Sensing, 60:1– 14, 2022.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation The Phi-Sat-1 Mission: The First On-Board Deep Neural Network Demonstrator for Satellite Earth Observation.IEEE Transactions on Geoscience and Remote Sensing, 60:1– 14, 2022

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e657b6b-ffab-4be7-9bfc-287d74ffd506 · outbound

This paper cites On-Board Image Com- pression using Convolutional Autoencoder: Performance Analysis and Application Scenarios.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation On-Board Image Com- pression using Convolutional Autoencoder: Performance Analysis and Application Scenarios

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71c2587b-a8fe-4031-afdf-041e854320b5 · outbound

This paper cites an unresolved cited work.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Unresolved cited work

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8237c8c4-0bb3-447b-bd00-71795b2b66f0 · outbound

This paper cites SqueezeNet: AlexNet-level accuracy with 50x fewer pa- rameters and ¡ 0.5 MB model size.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation SqueezeNet: AlexNet-level accuracy with 50x fewer pa- rameters and ¡ 0.5 MB model size

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2b56a93-a98b-4526-9627-c2486b67d902 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Adam: A Method for Stochastic Optimization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09eb1c47-3f30-44f3-9ed7-ce9f90f9e966 · outbound

This paper cites Vu, and George Goussetis.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Vu, and George Goussetis

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c557daa-882b-49e3-a2f9-392eff66b6df · outbound

This paper cites Satellite Edge Com- puting for Real-Time and Very-High Resolution Earth Observation.IEEE Trans- actions on Communications, 71(10):6180–6194, 2023.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Satellite Edge Com- puting for Real-Time and Very-High Resolution Earth Observation.IEEE Trans- actions on Communications, 71(10):6180–6194, 2023

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b0a3928-6f46-4528-aedf-d3480fc11d08 · outbound

This paper cites Douglas Liddle, Antony P.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Douglas Liddle, Antony P

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df63140b-6a0e-4e8e-90c5-7855b8e893eb · outbound

This paper cites MCUNet: Tiny Deep Learning on IoT Devices.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation MCUNet: Tiny Deep Learning on IoT Devices

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 784fdb8e-c4fe-4405-868c-c00039ddc172 · outbound

This paper cites Machine Learning in Earth Observation Operations: A review.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Machine Learning in Earth Observation Operations: A review

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e588286-69ee-4c0b-b21b-eec4d1d18da8 · outbound

This paper cites Hardware platforms enabling edge ai for space applications: A critical review.IEEE Access, 13:143939–143956, 2025.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Hardware platforms enabling edge ai for space applications: A critical review.IEEE Access, 13:143939–143956, 2025

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3edee355-8d38-45f7-ad61-0e4d9e523ef6 · outbound

This paper cites Earth Observing System Data and Information System (EOSDIS) Handbook, 2018.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Earth Observing System Data and Information System (EOSDIS) Handbook, 2018

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 511fbdca-7f8d-412b-baa1-48f272797cf2 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learn- ing Library.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation PyTorch: An Imperative Style, High-Performance Deep Learn- ing Library

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 179f4f8f-8d26-4375-ae29-138890f6a29f · outbound

This paper cites The Raspberry Pi AI Camera.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation The Raspberry Pi AI Camera

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1926d00a-2a78-4ff6-a466-45ed00c9d28a · outbound

This paper cites an unresolved cited work.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Unresolved cited work

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d388d0f7-8a34-4471-a284-7598e0b8f2aa · outbound

This paper cites Model Compression Toolkit (MCT).

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Model Compression Toolkit (MCT)

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ece633a1-5911-44e4-8a3b-aa8c472cf3cc · outbound

This paper cites High-Performance On-Orbit Intelligent Computing and Real-Time Services for Remote Sensing Satellites Based on Large-Scale Computing Power in Space.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation High-Performance On-Orbit Intelligent Computing and Real-Time Services for Remote Sensing Satellites Based on Large-Scale Computing Power in Space

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 007d5b95-84f5-4173-8eb1-bfcf505c0666 · outbound

This paper cites ShuffleNet: An Ex- tremely Efficient Convolutional Neural Network for Mobile Devices.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation ShuffleNet: An Ex- tremely Efficient Convolutional Neural Network for Mobile Devices

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1530b53d-4249-4495-b86b-423dac773f19 · outbound

This paper cites Expandable On-Board Real-Time Edge Computing Architecture for Luojia3 Intel- ligent Remote Sensing Satellite.Remote Sensing, 14(15):3596, 2022.

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation Expandable On-Board Real-Time Edge Computing Architecture for Luojia3 Intel- ligent Remote Sensing Satellite.Remote Sensing, 14(15):3596, 2022

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-28T17:00:07.051978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.