Paper Citation Record · LEDGER

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework

As of 20 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2411.13962.

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

pith.paper-citation-record.v1
2411.13962 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

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measured 40 of 40 standing notices

One-hop event checks from named stored sources.

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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

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External citation measurements

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Outbound references

Observation 72ca3414-e495-4feb-a0cd-5eb2b6e7feb5 · outbound

This paper cites Ultra low power bioelectronics: Fundamentals, biomedical applications, and bio-inspired system,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Ultra low power bioelectronics: Fundamentals, biomedical applications, and bio-inspired system,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:39.027724Z

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Observation be1090d7-881a-47eb-8b68-0924030d0250 · outbound

This paper cites Monitoring marine environments with autonomous underwater vehicles: a bibliometric analysis,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Monitoring marine environments with autonomous underwater vehicles: a bibliometric analysis,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.999128Z

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Observation c4e074af-7ae4-4301-a0a2-ce5b3d674482 · outbound

This paper cites Ex- ploring the.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Ex- ploring the

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.972674Z

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Observation bb47a39b-d98d-4d06-afe6-7821db36d7ee · outbound

This paper cites Treatment of offshore oily produced water: Research and application of a novel fibrous coalescence technique,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Treatment of offshore oily produced water: Research and application of a novel fibrous coalescence technique,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.952574Z

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Observation 9c3c84e2-88e6-4818-a56c-e6aca40763cc · outbound

This paper cites Deep learning for un- derwater visual odometry estimation,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Deep learning for un- derwater visual odometry estimation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.920037Z

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Observation fbda4ee7-521b-4e40-92d5-0c1e3f5f299d · outbound

This paper cites Real-time underwater onboard vision sensing system for robotic gripping,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Real-time underwater onboard vision sensing system for robotic gripping,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.899371Z

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Observation 7ffa425c-a9e0-45f0-895e-0a944e23ca9b · outbound

This paper cites Underwater acoustic research trends with machine learning: general background,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Underwater acoustic research trends with machine learning: general background,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.867911Z

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Observation 520fe3d3-5e09-4531-ae59-027503cf04ba · outbound

This paper cites Underwater hyperspectral imaging technology and its applications for detecting and mapping the seafloor: A review,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Underwater hyperspectral imaging technology and its applications for detecting and mapping the seafloor: A review,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.844030Z

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Observation bcb8fe3d-eb22-4c27-8e3b-c5e0f440b953 · outbound

This paper cites A survey of model driven engineering in robotics,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework A survey of model driven engineering in robotics,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.801263Z

Source-reported events for the cited work

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Observation fbf244c4-0ebd-4ade-bbc3-56e436a17e61 · outbound

This paper cites Assessing feasibility of secure quantum communications involving underwater assets,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Assessing feasibility of secure quantum communications involving underwater assets,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.773369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 668edf3a-ee54-4d5b-997a-3df26821cee1 · outbound

This paper cites Design and applications of mems flow sensors: A review,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Design and applications of mems flow sensors: A review,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.750132Z

Source-reported events for the cited work

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Observation ecd7ae49-fdd5-49ae-b33d-dd2c7d0d7231 · outbound

This paper cites Visual servoing,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Visual servoing,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.717532Z

Source-reported events for the cited work

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Observation 63e11605-5511-4d04-8984-d8abd742f60c · outbound

This paper cites Image processing with spiking neuron networks,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Image processing with spiking neuron networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.691441Z

Source-reported events for the cited work

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Observation 1caaef4b-596e-434d-ae6b-b4a0dd3cb33f · outbound

This paper cites Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.669759Z

Source-reported events for the cited work

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Observation 325b402b-bd09-4343-9059-bbe324144e3e · outbound

This paper cites Koch and I.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Koch and I

Reference 15

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Source-reported events for the cited work

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Observation c71eb4ad-36b7-483e-ba4d-fb44543aa8a6 · outbound

This paper cites Gerstner, W.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Gerstner, W

Reference 16

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Source-reported events for the cited work

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Observation deba74cc-b208-4bcb-ad0b-f6bf4553b50a · outbound

This paper cites Simple model of spiking neurons,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Simple model of spiking neurons,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.605894Z

Source-reported events for the cited work

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Observation 7f726848-e645-4d3b-8d71-7e248b03d4ff · outbound

This paper cites Neural coding in spiking neural networks: A comparative study for robust neuromorphic systems,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Neural coding in spiking neural networks: A comparative study for robust neuromorphic systems,

Reference 18

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This paper cites On the relevance of time in neural computation and learning,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework On the relevance of time in neural computation and learning,

Reference 19

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Observation 447ef608-b613-47de-8a97-3758caf5946f · outbound

This paper cites First spikes in ensembles of human tactile afferents code complex spatial fingertip events,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework First spikes in ensembles of human tactile afferents code complex spatial fingertip events,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.536524Z

Source-reported events for the cited work

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Observation 47142aef-06d8-4866-95bb-90a316f94edd · outbound

This paper cites Training spiking neural networks using lessons from deep learning,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Training spiking neural networks using lessons from deep learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.510044Z

Source-reported events for the cited work

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Observation 715976dc-8f25-480d-8d8e-aab09ac6497e · outbound

This paper cites Advancements in algorithms and neuromorphic hardware for spiking neural networks,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Advancements in algorithms and neuromorphic hardware for spiking neural networks,

Reference 22

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Observation 597d52a6-8dbc-4956-89ac-d0add816f3c2 · outbound

This paper cites Spike timing–dependent plasticity: a hebbian learning rule,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Spike timing–dependent plasticity: a hebbian learning rule,

Reference 23

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Observation bf7b328b-c0f1-4b09-a716-179644b53f9a · outbound

This paper cites Backpropagation-based learning techniques for deep spiking neural networks: A survey,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Backpropagation-based learning techniques for deep spiking neural networks: A survey,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.447772Z

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Observation d0995195-9dfa-4665-90ce-e9282f13465a · outbound

This paper cites Error-backpropagation in temporally encoded networks of spiking neurons,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Error-backpropagation in temporally encoded networks of spiking neurons,

Reference 25

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Observation 66084f81-c412-413b-8a98-9d46a5d18a48 · outbound

This paper cites The tempotron: a neuron that learns spike timing–based decisions,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework The tempotron: a neuron that learns spike timing–based decisions,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.403261Z

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Observation cd34a5b3-e3e1-4506-a5a5-88d1bab39418 · outbound

This paper cites Mapping from frame-driven to frame-free event-driven vision systems by low-rate rate coding and coincidence processing–application to feedforward convnets,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Mapping from frame-driven to frame-free event-driven vision systems by low-rate rate coding and coincidence processing–application to feedforward convnets,

Reference 27

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Observation 3cb315cb-d6de-4734-99f4-d9204887c62b · outbound

This paper cites Spiking deep convolutional neural networks for energy-efficient object recognition,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Spiking deep convolutional neural networks for energy-efficient object recognition,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.353860Z

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Observation 23bd7a17-7eec-4299-8a72-230efb25242d · outbound

This paper cites Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.326617Z

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Observation 8bb952c2-2c41-4674-a449-c1da0ece6ffa · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Batch normalization: Accelerating deep network training by reducing internal covariate shift,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.297042Z

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Observation 835cbabf-2226-474c-b06e-7b6dd8307e0f · outbound

This paper cites Spiden: deep spiking neural networks for efficient image denoising,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Spiden: deep spiking neural networks for efficient image denoising,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.275258Z

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Observation 2325b1b8-812b-4406-bb13-9ab535dc1936 · outbound

This paper cites Deep Multi-Threshold Spiking-UNet for Image Processing.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Deep Multi-Threshold Spiking-UNet for Image Processing

Reference 32

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Observation 1c69c68c-dd7a-45e7-a92f-6d4d77097c8e · outbound

This paper cites Neural architecture search for image dehazing,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Neural architecture search for image dehazing,

Reference 33

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Observation 9c0027b0-5cc8-48a3-8454-a466f65d2a5b · outbound

This paper cites Neural archi- tecture search for spiking neural networks,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Neural archi- tecture search for spiking neural networks,

Reference 34

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Observation f7e8a966-61b8-4f68-ad22-59a26a88236d · outbound

This paper cites Autosnn: Towards energy-efficient spiking neural networks,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Autosnn: Towards energy-efficient spiking neural networks,

Reference 35

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This paper cites Deep directly-trained spiking neural networks for object detection,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Deep directly-trained spiking neural networks for object detection,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.186217Z

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Observation 6a412c7c-89e5-482a-9f2c-778d59995d6d · outbound

This paper cites Spiking-yolo: spiking neural network for energy-efficient object detection,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Spiking-yolo: spiking neural network for energy-efficient object detection,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.150045Z

Source-reported events for the cited work

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Observation 54d5595d-2fea-42f6-b479-be6461bf5d4a · outbound

This paper cites G2l-net: Global to local network for real-time 6d pose estimation with embed- ding vector features,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework G2l-net: Global to local network for real-time 6d pose estimation with embed- ding vector features,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.125560Z

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Observation 14ba300d-da3c-4b2a-a3ed-1c4420b7b567 · outbound

This paper cites Hardware aware modeling of mixed- signal spiking neural network,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Hardware aware modeling of mixed- signal spiking neural network,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.094792Z

Source-reported events for the cited work

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Observation 8791d47a-0023-493a-a5e8-993b8d9b3687 · outbound

This paper cites Long short-term memory spiking networks and their applications,.

Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework Long short-term memory spiking networks and their applications,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:45:38.064749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.