SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization | Paper Citation Record

Observation 9f677390-22f2-4c6e-b5ae-7f22ffb78eb1 · outbound

This paper cites Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural network,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural network,

Reference 1

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Observation 88472d96-c43a-4fb8-9cbe-e391cded408b · outbound

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

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Training spiking neural networks using lessons from deep learning,

Reference 2

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Observation ade97144-937f-4a19-ad92-6a44dc72261f · outbound

This paper cites Hire-snn: Harnessing the inherent robustness of energy-efficient deep spiking neural networks by training with crafted input noise,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Hire-snn: Harnessing the inherent robustness of energy-efficient deep spiking neural networks by training with crafted input noise,

Reference 3

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Observation 9870513c-1ce5-4bc5-b1b4-d782ed3223f2 · outbound

This paper cites Intellectual property protection of dnn models,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Intellectual property protection of dnn models,

Reference 4

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Observation 05e58841-2a5f-4f0a-8118-d31ae614d6d1 · outbound

This paper cites Steganographic passport: An owner and user verifiable credential for deep model ip protection without retraining,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Steganographic passport: An owner and user verifiable credential for deep model ip protection without retraining,

Reference 5

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Observation 29ad48f9-425e-44cc-b44e-4f7d688e985b · outbound

This paper cites Watermarking neuromorphic brains: Intellectual property protection in spiking neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Watermarking neuromorphic brains: Intellectual property protection in spiking neural networks,

Reference 6

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Observation 8f64c6dd-ca19-4b64-a218-cf7f9884710c · outbound

This paper cites Incorporating learnable membrane time constant to enhance learning of spiking neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Incorporating learnable membrane time constant to enhance learning of spiking neural networks,

Reference 7

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Observation cfce13f4-3b08-45d1-9a41-b60652b255f5 · outbound

This paper cites Direct learning-based deep spiking neural networks: a review,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Direct learning-based deep spiking neural networks: a review,

Reference 8

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Observation 6e2d39f2-7033-42b4-a6b5-6906d30540b9 · outbound

This paper cites Synaptic modifications in cultured hip- pocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Synaptic modifications in cultured hip- pocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type,

Reference 9

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Observation 910162cc-d386-46f5-ac56-ea0bc11143f0 · outbound

This paper cites Spikeconverter: An efficient conversion framework zipping the gap between artificial neural networks and spiking neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Spikeconverter: An efficient conversion framework zipping the gap between artificial neural networks and spiking neural networks,

Reference 10

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Observation 771a1e97-7787-4147-b257-0681a7f0ec11 · outbound

This paper cites Lisnn: Improving spiking neural networks with lateral interactions for robust object recognition.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Lisnn: Improving spiking neural networks with lateral interactions for robust object recognition

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 55e47002-ab83-4214-acf8-1ff1c7df6a4b · outbound

This paper cites A free lunch from ann: Towards efficient, accurate spiking neural networks calibration,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization A free lunch from ann: Towards efficient, accurate spiking neural networks calibration,

Reference 12

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Observation f41968f5-32dd-47e3-8586-456c0c44c36a · outbound

This paper cites Surrogate module learning: Reduce the gradient error accumulation in training spiking neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Surrogate module learning: Reduce the gradient error accumulation in training spiking neural networks,

Reference 13

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Observation 008388b2-fc07-4f5a-8c2a-163e90871daf · outbound

This paper cites Embedding water- marks into deep neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Embedding water- marks into deep neural networks,

Reference 14

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Observation 1aeb6ee4-6549-4a11-ab10-99a7f95bdd6f · outbound

This paper cites Riga: Covert and robust white-box watermarking of deep neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Riga: Covert and robust white-box watermarking of deep neural networks,

Reference 15

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Observation 63467cb3-bde6-46c0-b4f8-2f1f47e04e40 · outbound

This paper cites Deepsigns: An end- to-end watermarking framework for ownership protection of deep neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Deepsigns: An end- to-end watermarking framework for ownership protection of deep neural networks,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 6a036cdd-656c-485c-9705-d66082d3d0fa · outbound

This paper cites Turning your weakness into a strength: Watermarking deep neural networks by backdooring,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Turning your weakness into a strength: Watermarking deep neural networks by backdooring,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 7d017b07-9fbd-4fce-939b-606b68f0d485 · outbound

This paper cites Protecting intellectual property of deep neural networks with watermarking,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Protecting intellectual property of deep neural networks with watermarking,

Reference 18

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Observation 23d26fe7-39a1-4320-b6a6-b93745b1b162 · outbound

This paper cites Entangled watermarks as a defense against model extraction,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Entangled watermarks as a defense against model extraction,

Reference 19

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Observation 1238ed37-a828-4423-a091-b97a6d2d4918 · outbound

This paper cites Sslguard: A watermarking scheme for self-supervised learning pre-trained encoders,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Sslguard: A watermarking scheme for self-supervised learning pre-trained encoders,

Reference 20

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Observation bc1e1dd2-90da-4522-b741-e175f73c4c96 · outbound

This paper cites Chaotic weights: A novel approach to protect intellectual property of deep neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Chaotic weights: A novel approach to protect intellectual property of deep neural networks,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 7d12a7d0-d00c-41ed-b5cb-914f86062464 · outbound

This paper cites Advparams: An active dnn intellectual property protection technique via adversarial perturbation based parameter encryption,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Advparams: An active dnn intellectual property protection technique via adversarial perturbation based parameter encryption,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 32fb6767-d74f-4aaf-911f-15e493d15008 · outbound

This paper cites Protecting intellectual property with reliable availability of learning models in ai-based cyber- security services,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Protecting intellectual property with reliable availability of learning models in ai-based cyber- security services,

Reference 23

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Observation 7629925e-066e-4530-98f8-4e9f2016785f · outbound

This paper cites ActiveDaemon: Unconscious DNN dormancy and waking up via user-specific invisible token,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization ActiveDaemon: Unconscious DNN dormancy and waking up via user-specific invisible token,

Reference 24

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Observation 241055bb-d1ca-4212-9885-207dfdf34c8d · outbound

This paper cites Signed neuron with memory: Towards simple, accurate and high-efficient ann-snn conversion.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Signed neuron with memory: Towards simple, accurate and high-efficient ann-snn conversion

Reference 25

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Observation bf1c3686-7fc6-469a-aa38-8c803343b8d2 · outbound

This paper cites Gerstner and W.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Gerstner and W

Reference 26

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Observation 7354e11e-6fc5-4f7c-a987-d314bc24f71c · outbound

This paper cites Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks,

Reference 27

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Observation b355f286-829a-409d-8ba9-bcf9a5170fc2 · outbound

This paper cites Events-to-video: Bringing modern computer vision to event cameras,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Events-to-video: Bringing modern computer vision to event cameras,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation e5155c41-af49-4fff-8298-988792f29a16 · outbound

This paper cites Neuroclip: Neuromorphic data under- standing by clip and snn,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Neuroclip: Neuromorphic data under- standing by clip and snn,

Reference 29

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Observation 26c6cb75-5ef8-46fd-bdf5-db32676dbece · outbound

This paper cites Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-04T14:09:53.336809Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dcf3bea0-402a-41b3-a564-2367d9dff10e · outbound

This paper cites Spottune: transfer learning through adaptive fine-tuning,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Spottune: transfer learning through adaptive fine-tuning,

Reference 31

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Observation 7457f729-9124-4ad8-9d5c-36d196ae2567 · outbound

This paper cites Discrimination-aware network pruning for deep model compression,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Discrimination-aware network pruning for deep model compression,

Reference 32

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Observation a4c1ac38-a127-4b01-b4d6-a25504121513 · outbound

This paper cites Converting static image datasets to spiking neuromorphic datasets using saccades,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Converting static image datasets to spiking neuromorphic datasets using saccades,

Reference 33

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Observation abb5bced-0404-4304-bc93-56bc0b264805 · outbound

This paper cites Cifar10-dvs: an event-stream dataset for object classification,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Cifar10-dvs: an event-stream dataset for object classification,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 080feb4f-70d0-4d7d-871b-20c946646b63 · outbound

This paper cites Converting static image datasets to spiking neuromorphic datasets using saccades,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Converting static image datasets to spiking neuromorphic datasets using saccades,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 4f1b6878-dc1a-4e91-9e74-3866a3b58c6e · outbound

This paper cites A low power, fully event-based gesture recognition system,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization A low power, fully event-based gesture recognition system,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 1ca8418c-9f62-4a47-b1dd-b9b43a1a1270 · outbound

This paper cites Dailydvs-200: A comprehensive benchmark dataset for event-based action recognition,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Dailydvs-200: A comprehensive benchmark dataset for event-based action recognition,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 95f08a92-eb0b-4656-b600-b5c0b5c7944c · outbound

This paper cites Advancing spiking neural networks towards multiscale spatiotemporal interaction learning,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Advancing spiking neural networks towards multiscale spatiotemporal interaction learning,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 2312716e-92d5-4663-bf64-eb44f68c5c33 · outbound

This paper cites Ffcba: Feature-based full-target clean-label backdoor attacks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Ffcba: Feature-based full-target clean-label backdoor attacks,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation b8547a8e-bc94-4584-b6b3-3ac840dc5e19 · outbound

This paper cites Waveattack: Asymmetric frequency obfuscation-based backdoor attacks against deep neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Waveattack: Asymmetric frequency obfuscation-based backdoor attacks against deep neural networks,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 0350622d-d321-4120-ba37-a3ad50e97204 · outbound

This paper cites Spikingjelly: An open-source machine learning infrastructure platform for spike-based intelligence,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Spikingjelly: An open-source machine learning infrastructure platform for spike-based intelligence,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation cf5354bf-14f4-4811-8dfb-32c225e30f59 · outbound

This paper cites Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation f92decd5-5d4c-457b-856e-95ecef33946c · outbound

This paper cites Spikingformer: A key foundation model for spiking neural networks,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Spikingformer: A key foundation model for spiking neural networks,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 8324189d-c15d-4dd8-bf97-b494db6334b7 · outbound

This paper cites Spike- driven transformer,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Spike- driven transformer,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-26T04:28:46.585347Z

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Observation 5ec8798a-26de-42c5-ae98-f800f08bb0bc · outbound

This paper cites Te-spikformer:temporal-enhanced spiking neural network with trans- former,.

SpikeTimer: Exploring Active Copyright Protection in Spiking Neural Networks via Temporal Backdoor Regularization Te-spikformer:temporal-enhanced spiking neural network with trans- former,

Reference 45

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