ID 原文 译文
24535 针对带内全双工（In-band Full Duplex, IBFD）电子系统的收发机自干扰问题，提出了一种基于相位调制器的光子射频自干扰消除系统。 To solve the problem of transceiver interference in the in-band full duplex (IBFD) system, a photonic radio frequency interference cancellation system based on phase modulators is proposed.
24536 利用两个相位调制器在萨格纳克（Sagnac）环中分别实现接收信号和本地参考干扰信号的调制，通过偏振控制最终可在光域中消除自干扰信号。 Two phase modulators are used in a Sagnac loop to realize the modulation of the received signal and the local reference interference signal. Proper polarization control in the optical domain can finally cancel the self-interference signal.
24537 实验结果表明，所提方案最终可以实现超过 45dB的单频干扰消除和超过25dB的宽带干扰消除，系统的动态范围可达99.4dB·Hz2/3。 Experimental results show that the proposed scheme can achieve a single frequency interference suppression of more than 45 dB and a broad band interference suppression of more than 25 dB. The dynamic range of the system can reach 99.4 dB·Hz2/3.
24538 当前基于深度学习的有监督前景分割方法得益于大量待分割场景的标注信息，其性能大幅超越传统的无监督方法。 Benefiting from large amounts of ground-truths of to-be-segmented scenarios, deep-learning based and supervised foreground segmentation algorithms generally outperform conventional unsupervised methods.
24539 然而，获取高精度的像素级标注需要耗费大量的人力和时间成本，这严重限制了有监督算法在无标注场景的部署应用。 However, pixel-wise annotation is a tedious task, especially when it comes to the annotation of foreground moving objects. This seriously limits the deployment of a supervised algorithm in a wide range of scenes without ground-truths.
24540 为解决对场景监督信息依赖的问题，设计了一种与传统的帧间差分法相融合的跨场景深度学习架构，即帧间高级特征差分算法。 To address the dependence on supervised information of to-be-segmented unseen scenes, we design an inter-frame high-level feature differencing algorithm with a deep learning architecture via integrating the traditional frame differencing method.
24541 该算法重点围绕时域变化等跨场景共性知识的迁移，在不依赖待分割场景监督信息的前提下实现高精度分割。 The proposed algorithm leverages the transfer of cross-scene common knowledge, such as temporal changes, so as to achieve high performance for the scene in the absence of supervised information of to-be-segmented scenes.
24542 面向五类不同模式的困难场景开展实验，本文算法的平均 F 值达到 0.8719，超越了当前最高性能的有监督算法FgSegNet_v2（相同的跨场景条件下）和最佳的无监督算法SemanticBS。 We evaluate our method on five challenging scenes with different patterns. The average F-Measure of our algorithm is 0.8719, which surpasses the current highest-performance (supervised) algorithm (FgSegNet_v2) under the cross-scene learning condition and the best unsupervised algorithm SemanticBS.
24543 本文算法对QVGA视频（320×240）的处理速度达到35帧/s，具有较好的实时性。 Our method which can process a QVGA (320 × 240) video at 35 frames per second shows favorable real-time performance.
24544 甲骨文是中国最早的系统文字，是目前能见到的最早的成熟汉字。 Oracle-Bone inscriptions are the earliest systematic and mature Chinese characters presently discovered.