ABSTRACT Accurate lane line segmentation is critical for auto‐gantry steering of Rubber‐Tyred Gantry (RTG) cranes in automated container terminals. RTG lanes are typically straight but often exhibit degradation due to surface wear, contamination or interference from nearby ground markings, making pixel‐level detection particularly challenging. This letter proposes a lightweight and robust segmentation algorithm based on an enhanced BiSeNet V2. Improvements include depthwise separable convolutions to reduce model complexity, efficient channel attention to enhance feature discriminability under contamination and weak contrast, and an edge‐aware loss function to address the thin‐line nature of RTG lanes. Experiments on a curated set of labelled RTG images demonstrate that the proposed method outperforms existing lightweight segmentation models in accuracy and robustness. The model achieves a favourable balance between precision and computational efficiency, making it suitable for real‐time use in port automation systems. To facilitate future research and reproducibility, the annotated RTG lane dataset used in this work is publicly available at: https://github.com/DONN‐RD/Lane‐line‐detection .

ABSTRACT This letter presents a high‐ Q tunable waveguide (WG) filter with constant absolute bandwidth (CABW). By adjusting the penetration depth of a single dielectric tuning element into the filter, frequency tuning is readily obtained without a complicated mechanism. Modified cavity perturbation theory (CPT) is adopted for the first time to deduce the quantitative relationship between the penetration depth and resonant frequency. At the same time, the tuning element also plays a vital role in realising innovative inter‐resonator (IR) coupling and input‐output (IO) coupling structures, combined with the configuration of double septa to ensure the CABW and IO port impedance matching. Finally, to validate the proposed concept, a prototype of a fifth‐order inline tunable WG filter is implemented, which has a tuning range of 8% from 18.2 to 19.7 GHz and the 1‐dB bandwidth variation is maintained within 315 ± 15 MHz. Measured results match the simulated ones very well, which show that the insertion losses are less than 0.6 dB and the return losses are better than 20 dB for all tuned passbands. The high performance of the proposed tunable WG filter makes it very suitable for the applications of 5G/6G millimetre‐wave backhaul or satellite telecommunication.

ABSTRACT Data compression built into solid‐state drives (SSDs) has emerged as an effective technique to reduce write amplification and improve storage utilisation. Nevertheless, compression introduces variable‐length data, which invalidates the 1‐to‐1 mapping between logical and physical pages in the flash translation layer (FTL). The proposed virtual page‐based FTL (VPFTL) addresses challenges of asymmetric mappings caused by compression. By grouping multiple physically related pages into a single virtual page, VPFTL enables flexible management of logical‐to‐physical (L2P) and physical‐to‐logical (P2L) address mappings. Experimental results demonstrate that VPFTL significantly improves NAND flash storage utilisation, achieving up to 1.44× higher than N‐to‐1 mapping schemes. VPFTL maintains comparable read/write performance, indicating its effectiveness and scalability for compressed SSD controllers that integrate hardware compression and emerging error‐correction codes (ECCs).

ABSTRACT The proposed winner‐take‐all‐loser‐take‐all (WTA–LTA) circuit identifies both the winner and the loser simultaneously using a shared delay line and is suitable for applications where both the winner and the loser are important. Due to the shared delay line between the WTA and LTA cells, power consumption and occupied area are significantly reduced. The power consumption per cell at a frequency of 2 MHz is 5°nW and the occupied area per cell is 41.43°µm 2 . Moreover, the precision of the circuit for three cells is 99.4% for WTA and 99.2% for LTA. The proposed time‐domain WTA‐LTA circuit has been post‐layout simulated in 65‐nm technology with a supply voltage of 0.5 V.

ABSTRACT We successfully fabricated GaN‐based red resonant‐cavity light‐emitting diodes by using two dielectric distributed Bragg reflectors as the top and bottom reflector mirrors. The device exhibited resonant modes up to 673 nm, being the longest emission wavelength ever reported for a GaN‐based microcavity device. This achievement establishes spectral overlap between GaN‐based light‐emitting devices and GaAs‐based devices. This work contributes significantly to the development of GaN‐based microcavity devices in longer wavelengths.

ABSTRACT Intra template matching prediction (Intra TMP) mode, a promising new intra prediction technique, generates predictions using block vectors (BVs), which are obtained via the decoder side search. To improve the accuracy of prediction of Intra TMP mode while maintaining computational complexity, we propose a BV linkage‐based candidate construction algorithm, which leverages spatially adjacent BV‐coded blocks to generate a larger number of effective candidates, utilising highly correlated regions to enable efficient prediction. Experimental results demonstrate that the proposed method achieves improvements in coding efficiency over the enhanced compression model (ECM) of the technique exploration on enhanced compression beyond H.266/Versatile Video Coding (VVC) capability. Specifically, BD‐rate savings of 0.33% and 0.07% are achieved for screen content videos and camera‐captured natural videos, respectively. Due to its coding gains and low computational complexity, the proposed algorithm has been adopted in beyond VVC capability exploration and is integrated into the latest versions of ECM.

ABSTRACT Blosc2 is a high‐performance compression library and data format designed for binary data such as numerical arrays, tensors, and other structured types. In this proposal, we aim to develop two new codecs for Blosc2 by leveraging its extensible plugin‐based codec framework. Specifically, we propose integrating archetypal analysis (AA) and fuzzy clustering as novel codecs within Blosc2. Our proposal has been assessed by using the Olivetti faces dataset and results have demonstrated that AA outperforms fuzzy clustering in preserving fine‐grained data details, achieving substantially higher Structural Similarity Index. These results underscore AA's capability to capture the complete data distribution, including its extreme values, which is an essential property for achieving high‐fidelity compression.

ABSTRACT We address the problem of reconstructing 3D surfaces from depth and surface normal maps acquired by a sensor system based on a single perspective camera. Depth and normal maps can be obtained through techniques such as structured‐light scanning and photometric stereo, respectively. We propose a perspective‐aware log‐depth fusion approach that extends existing orthographic gradient‐based depth‐normals fusion methods by explicitly accounting for perspective projection, leading to metrically accurate 3D reconstructions. Additionally, the method handles missing depth measurements by leveraging available surface normal information to inpaint gaps. Experiments on the DiLiGenT‐MV data set demonstrate the effectiveness of our approach and highlight the importance of perspective‐aware depth‐normals fusion.

Abstract A significant challenge in the domain of anti‐drone warfare is the identification of enemies or own aircraft through the analysis of data broadcast by drones (e.g. ADS‐B). This issue can be conceptualized as an open set recognition (OSR) problem. This paper proposes a DV‐OSR‐QSED framework for the purpose of data visualization‐based OSR (DV‐OSR). Phase‐based 2D high‐importance features are extracted, the DV‐OSR framework is designed and mapped to 2D, and the 5th and 95th quantile selection‐Euclidean distance (QSED) strategy is proposed. Experiments show that by using the proposed framework, the correct classification rate for known and unknown samples is 96.04% and 95.79%, the recall rate and F1 value are 89.00% and 92.27%, and the AUC is 0.9630.

ABSTRACT This letter introduces a refreshable delay coincidence detection circuit for direct time‐of‐flight (DToF) depth sensors. Although the conventional coincidence detection structure can suppress noise pulses from background light, it results in significant attenuation of signal pulses, compromising the accuracy (ACC) of depth acquisition. In this work, the authors propose a refreshable delay coincidence detection structure, which integrates a refreshable delay unit to achieve automatic adjustment of the time window width. Additionally, the initial time window width of the refreshable delay unit can be externally configured, facilitating its application in various background light environments. The proposed structure was implemented and verified in an Artix‐7 FPGA. The measurements show that the refreshable structure effectively suppresses noise and performs better in retaining signal pulses and improving peak position accuracy. At an 18 m distance and 150 klx illumination, it captures 161 signal pulses over 300 frames, 60 more than the conventional structure. After 100 repeated measurements, the refreshable structure achieves 91% peak accuracy, outperforming the conventional structure's 72%. The refreshable delay structure enhances depth sensing robustness, flexibility and adaptability, making it ideal for high‐precision applications such as robotics and autonomous driving.