Selected work

Representative Papers

DRAFE: Domain-Robust Asymmetric Fusion of Heterogeneous Detection Transformers for Cross-City Fine-Grained Traffic Object Detection

Aug 17, 2026

This study addresses the challenge of balancing domain generalization and accuracy in fine-grained traffic object detection across cross-city scenarios by proposing the DRAFE framework. The method employs a heterogeneous asymmetric fusion mechanism integrating LW-DETR and RF-DETR, combined with two-stage training to construct high-quality corpora. During inference, complementary hypotheses are effectively recovered and transfer robustness is enhanced through anchor-conditioned matching, reliability-weighted fusion, and protocol-aware confidence recalibration. Validated on Track 6 of the AI City Challenge 2026, DRAFE achieved a mAP of 0.4022, ranking sixth and outperforming the baseline ensemble by 0.0553 mAP, thereby demonstrating its effectiveness in real-world cross-domain traffic detection tasks.

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An Efficient Transport-Based Dissimilarity Measure for Time Series Classification under Warping Distortions

May 08, 2025

To address the discriminability challenge in time-series classification caused by temporal warping—particularly under single-shot learning where robustness and efficiency are difficult to reconcile—this paper introduces, for the first time, continuous optimal transport theory into time-series deformation modeling. We propose a Wasserstein-based heterogeneity measure that theoretically guarantees optimal solution recovery under single-sample conditions, achieving both warping robustness and low computational complexity. Compared to dynamic time warping (DTW), our method reduces time complexity by over an order of magnitude while maintaining—or even surpassing—the 1-nearest-neighbor (1NN) classification accuracy on both synthetic and real-world benchmarks. Our core contributions are threefold: (i) establishing a rigorous theoretical linkage between continuous optimal transport and temporal deformation; (ii) overcoming DTW’s inherent high-complexity bottleneck; and (iii) providing an efficient, interpretable paradigm for few-shot time-series classification.

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Frequency Hopping Waveform Design for Secure Integrated Sensing and Communications

Apr 14, 2025

To address the vulnerability of radar parameters to passive eavesdropping and the inherent trade-off between security and sensing performance in Integrated Sensing and Communication (ISAC) systems, this paper proposes a Random Frequency and Pulse Repetition Interval Agile (RFPA) waveform design. The framework integrates Channel Reciprocity-based Key Generation (CRKG) with hybrid information embedding—combining ASK, PSK, Index Modulation, and Spatial Modulation—enabling decentralized secure communication-sensing coexistence. A novel sparse matched-filter receiver is devised to jointly achieve high-accuracy Doppler and PRI estimation while ensuring low-bit-error-rate (BER) data decoding. Experimental results demonstrate a significant reduction in passive eavesdroppers’ success rate for estimating critical radar parameters; ambiguity function analysis confirms improved range-Doppler resolution and enhanced clutter suppression; and communication throughput increases substantially with markedly reduced BER.

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Recent publications

Latest Papers

DRAFE: Domain-Robust Asymmetric Fusion of Heterogeneous Detection Transformers for Cross-City Fine-Grained Traffic Object Detection

Aug 17, 2026

This study addresses the challenge of balancing domain generalization and accuracy in fine-grained traffic object detection across cross-city scenarios by proposing the DRAFE framework. The method employs a heterogeneous asymmetric fusion mechanism integrating LW-DETR and RF-DETR, combined with two-stage training to construct high-quality corpora. During inference, complementary hypotheses are effectively recovered and transfer robustness is enhanced through anchor-conditioned matching, reliability-weighted fusion, and protocol-aware confidence recalibration. Validated on Track 6 of the AI City Challenge 2026, DRAFE achieved a mAP of 0.4022, ranking sixth and outperforming the baseline ensemble by 0.0553 mAP, thereby demonstrating its effectiveness in real-world cross-domain traffic detection tasks.

0 citationsRead paper

An Efficient Transport-Based Dissimilarity Measure for Time Series Classification under Warping Distortions

May 08, 2025

To address the discriminability challenge in time-series classification caused by temporal warping—particularly under single-shot learning where robustness and efficiency are difficult to reconcile—this paper introduces, for the first time, continuous optimal transport theory into time-series deformation modeling. We propose a Wasserstein-based heterogeneity measure that theoretically guarantees optimal solution recovery under single-sample conditions, achieving both warping robustness and low computational complexity. Compared to dynamic time warping (DTW), our method reduces time complexity by over an order of magnitude while maintaining—or even surpassing—the 1-nearest-neighbor (1NN) classification accuracy on both synthetic and real-world benchmarks. Our core contributions are threefold: (i) establishing a rigorous theoretical linkage between continuous optimal transport and temporal deformation; (ii) overcoming DTW’s inherent high-complexity bottleneck; and (iii) providing an efficient, interpretable paradigm for few-shot time-series classification.

0 citationsRead paper

Frequency Hopping Waveform Design for Secure Integrated Sensing and Communications

Apr 14, 2025

To address the vulnerability of radar parameters to passive eavesdropping and the inherent trade-off between security and sensing performance in Integrated Sensing and Communication (ISAC) systems, this paper proposes a Random Frequency and Pulse Repetition Interval Agile (RFPA) waveform design. The framework integrates Channel Reciprocity-based Key Generation (CRKG) with hybrid information embedding—combining ASK, PSK, Index Modulation, and Spatial Modulation—enabling decentralized secure communication-sensing coexistence. A novel sparse matched-filter receiver is devised to jointly achieve high-accuracy Doppler and PRI estimation while ensuring low-bit-error-rate (BER) data decoding. Experimental results demonstrate a significant reduction in passive eavesdroppers’ success rate for estimating critical radar parameters; ambiguity function analysis confirms improved range-Doppler resolution and enhanced clutter suppression; and communication throughput increases substantially with markedly reduced BER.

0 citationsRead paper