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学者姓名：陈建
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样点自适应补偿（Sample Adaptive Offset,SAO）是高效视频编码（High Efficiency Video Coding,HEVC）的重要组成部分,能有效去除编码图像中的振铃效应，改善编码图像的主观质量。针对当前SAO滤波器处理速度慢和吞吐量较低的问题，基于6×6大小的基本信息统计单元采用亮色度并行处理的四级流水线设计，提出一种基于FPGA的适用于超高清视频（Ultra HD Video,UHD）的SAO硬件滤波器。实验结果表明，在Xilinx Virtex7 FPGA开发平台上，该架构仅占用了10.5k的查找表和6.2k的寄存器资源，工作主频最高可达250 MHz，支持8K@110 fps的超高清视频流处理。在相同分辨率条件下，相较于现有其它方案在逻辑资源及帧率方面更具优势。
Keyword ：
FPGA FPGA SAO SAO 硬件设计 硬件设计 视频编码 视频编码
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| GB/T 7714 | 汪家华 , 朱宇耀 , 刘睿宸 et al. 适用于超高清视频的SAO硬件优化设计 [J]. | 中国集成电路 , 2024 , 33 (04) : 47-51 . |
| MLA | 汪家华 et al. "适用于超高清视频的SAO硬件优化设计" . | 中国集成电路 33 . 04 (2024) : 47-51 . |
| APA | 汪家华 , 朱宇耀 , 刘睿宸 , 陈建 . 适用于超高清视频的SAO硬件优化设计 . | 中国集成电路 , 2024 , 33 (04) , 47-51 . |
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采用Rhino软件设计了两种多孔结构TC4骨科植入物模型，结合有限元分析方法对TC4多孔结构模型进行静力学仿真，得到了两种多孔结构及其不同孔隙率下的应力分布和等效弹性模量。通过激光选区熔化（SLM）打印出两种多孔结构TC4骨科植入物，进行准静态压缩试验和纳米压痕试验，探究了两种多孔结构及其不同孔隙率下力学性能的差异性。仿真结果表明，两种多孔结构孔隙率越大，平均应力越小。相同孔隙率下，规则多孔结构的平均应力、等效弹性模量和渗透率均大于不规则多孔结构；规则多孔结构弹性模量为4.18～9.71 GPa，不规则多孔结构的弹性模量为2.69～5.84 GPa，均满足人骨弹性模量范围。相同孔隙率下，规则多孔结构的抗压强度、弹性模量和耐磨性能均优于不规则多孔结构，与仿真结果一致。
Keyword ：
SLM SLM TC4 TC4 多孔结构 多孔结构 有限元分析 有限元分析 骨科植入物 骨科植入物
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| GB/T 7714 | 朱陈成 , 陈鸿玲 , 傅高升 et al. SLM成形多孔结构TC4骨科植入物的仿真与力学试验 [J]. | 特种铸造及有色合金 , 2024 , 44 (07) : 975-981 . |
| MLA | 朱陈成 et al. "SLM成形多孔结构TC4骨科植入物的仿真与力学试验" . | 特种铸造及有色合金 44 . 07 (2024) : 975-981 . |
| APA | 朱陈成 , 陈鸿玲 , 傅高升 , 张晨 , 陈建 . SLM成形多孔结构TC4骨科植入物的仿真与力学试验 . | 特种铸造及有色合金 , 2024 , 44 (07) , 975-981 . |
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去方块滤波是高效视频编码(HEVC)的重要组成部分,能够有效地改善编码图像的主观质量,是提升视频整体编码性能的重要手段之一.针对HEVC硬件编码器中去方块滤波技术复杂度较高的问题,为了在节省资源消耗的同时减少处理周期,改善滤波效率,提出HEVC自适应去方块滤波的硬件算法和VLSI架构.首先基于HEVC编码结构的边界规则,提出一种无需递归循环计算的快速边界判断算法,降低硬件实现的复杂度;然后基于上述边界判断结果,提出一种可自主选择滤波边界进行去方块滤波的4级流水结构,减少滤波处理周期;最后将亮度和色度并行滤波,设计一种高度并行且兼容共享的存储架构,改善滤波效率且节约存储资源消耗.实验结果表明,在TSMC90 nm工艺下,所设计的去方块滤波结构的硬件面积比已有结构减少60%左右,并且最高能达到250 MHz的工作频率,可满足8K@60帧/s的超高清视频的实时编码.
Keyword ：
去方块滤波 去方块滤波 硬件设计 硬件设计 边界判断 边界判断 高效视频编码 高效视频编码
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| GB/T 7714 | 陈焯淼 , 陈志峰 , 陈建 et al. HEVC自适应去方块滤波器的VLSI设计与实现 [J]. | 计算机辅助设计与图形学学报 , 2024 , 36 (04) : 636-644 . |
| MLA | 陈焯淼 et al. "HEVC自适应去方块滤波器的VLSI设计与实现" . | 计算机辅助设计与图形学学报 36 . 04 (2024) : 636-644 . |
| APA | 陈焯淼 , 陈志峰 , 陈建 , 汪家华 . HEVC自适应去方块滤波器的VLSI设计与实现 . | 计算机辅助设计与图形学学报 , 2024 , 36 (04) , 636-644 . |
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With the rapid development of image editing technology, tampering with images has become easier. Maliciously tampered images lead to serious security problems (e.g., when used as evidence). The current mainstream methods of image tampering are divided into three types which are copy-move, splicing and removal. Many image tampering detection methods can only detect one type of image tampering. Additionally, some methods learn features by suppressing image content, which can result in false positives when identifying tampered areas. In this paper, the authors propose a novel framework named the dual supervision neural network (DS-Net) to localize the tampered regions of images tampered by the three tampering methods mentioned above. First, to extract richer multiscale information, the authors add skip connections to the atrous spatial pyramid pooling (ASPP) module. Second, a channel attention mechanism is introduced to dynamically weigh the results generated by ASPP. Finally, the authors build additional supervised branches for high-level features to further enhance the extraction of these high-level features before fusing them with low-level features. The authors conduct experiments on various standard datasets. Through extensive experiments, the results show that the AUC scores reach 86.4%, 95.3% and 99.6% for CASIA, COVERAGE and NIST16 datasets, respectively, and the F1 scores are 56.0%, 73.4% and 82.7%, respectively. The results demonstrate that the authors' method can accurately locate tampered regions and achieve better performance on various datasets than other methods of the same type.
Keyword ：
image forensics image forensics image processing image processing
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| GB/T 7714 | Dai, Chenwei , Su, Lichao , Wu, Bin et al. DS-Net: Dual supervision neural network for image manipulation localization [J]. | IET IMAGE PROCESSING , 2023 , 17 (12) : 3551-3563 . |
| MLA | Dai, Chenwei et al. "DS-Net: Dual supervision neural network for image manipulation localization" . | IET IMAGE PROCESSING 17 . 12 (2023) : 3551-3563 . |
| APA | Dai, Chenwei , Su, Lichao , Wu, Bin , Chen, Jian . DS-Net: Dual supervision neural network for image manipulation localization . | IET IMAGE PROCESSING , 2023 , 17 (12) , 3551-3563 . |
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基于视频的点云压缩(Video based point cloud compression, V-PCC)为压缩动态点云提供了高效的解决方案,但V-PCC从三维到二维的投影使得三维帧间运动的相关性被破坏,降低了帧间编码性能.针对这一问题,提出一种基于V-PCC改进的自适应分割的视频点云多模式帧间编码方法,并依此设计了一种新型动态点云帧间编码框架.首先,为实现更精准的块预测,提出区域自适应分割的块匹配方法以寻找最佳匹配块;其次,为进一步提高帧间编码性能,提出基于联合属性率失真优化(Rate distortion optimization, RDO)的多模式帧间编码方法,以更好地提高预测精度和降低码率消耗.实验结果表明,提出的改进算法相较于V-PCC实现了-22.57%的BD-BR (Bjontegaard delta bit rate)增益.该算法特别适用于视频监控和视频会议等帧间变化不大的动态点云场景.
Keyword ：
三维帧间编码 三维帧间编码 基于视频的点云压缩 基于视频的点云压缩 点云分割 点云分割 点云压缩 点云压缩 率失真优化 率失真优化
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| GB/T 7714 | 陈建 , 廖燕俊 , 王适 et al. 自适应分割的视频点云多模式帧间编码方法 [J]. | 自动化学报 , 2023 , 49 (08) : 1707-1722 . |
| MLA | 陈建 et al. "自适应分割的视频点云多模式帧间编码方法" . | 自动化学报 49 . 08 (2023) : 1707-1722 . |
| APA | 陈建 , 廖燕俊 , 王适 , 郑明魁 , 苏立超 . 自适应分割的视频点云多模式帧间编码方法 . | 自动化学报 , 2023 , 49 (08) , 1707-1722 . |
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去方块滤波(Deblocking Filtering,DBF)是高效视频编码(High Efficiency Video Coding,HEVC)的重要组成部分,能够有效地改善编码图像的主观质量,是提升视频整体编码性能的重要手段之一.但是去方块滤波技术复杂度较高.为解决该问题,设计一种HEVC去方块滤波器的硬件架构,在节省资源消耗的同时,减少处理周期并改善滤波效率.以8×4块为基本滤波单元,从输入像素到输出像素,采用四级流水线的形式进行处理,每处理一个基本滤波单元共花费5个周期.实验结果表明,所设计的去方块滤波器仅需5212个查找表和1291个寄存器的逻辑资源消耗,最高可达到215 MHz的工作频率,满足1080p@60fps的高清视频实时编码.
Keyword ：
去方块滤波(DBF) 去方块滤波(DBF) 环路滤波 环路滤波 高效视频编码(HEVC) 高效视频编码(HEVC)
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| GB/T 7714 | 陈焯淼 , 陈志峰 , 陈建 et al. 基于FPGA的HEVC去方块滤波硬件设计 [J]. | 电视技术 , 2023 , 47 (1) : 48-51,69 . |
| MLA | 陈焯淼 et al. "基于FPGA的HEVC去方块滤波硬件设计" . | 电视技术 47 . 1 (2023) : 48-51,69 . |
| APA | 陈焯淼 , 陈志峰 , 陈建 , 汪家华 . 基于FPGA的HEVC去方块滤波硬件设计 . | 电视技术 , 2023 , 47 (1) , 48-51,69 . |
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The sample adaptive offset (SAO) filter introduced in the high efficiency video coding standard can remove the ringing artifacts caused by the loss of high-frequency information. But, it dominates the complexity of in-loop filtering. In this article, an algorithm optimization and implementation scheme with low complexity SAO is proposed. The information statistical range is optimized regionally, which avoids the complex logic control across coding tree unit boundary, and saves additional cache structure. To trade off the complexity of SAO mode decision and the accuracy of rate model in rate-distortion optimization, a three-dimensional linear rate estimation model for fast calculation of rate-distortion cost is proposed. Finally, based on the above improved algorithms, a SAO hardware filter suitable for ultra high definition (UHD) video processing is designed. The proposed architecture supports the UHD video processing up to 333 MHz with only 85. 6 k equivalent gates. Compared with the traditional scheme, the logical resource consumption can be saved up to 71. 47% . © 2023 Science Press. All rights reserved.
Keyword ：
hardware design hardware design high efficiency video coding high efficiency video coding in-loop filtering in-loop filtering rate-distortion optimization rate-distortion optimization sample adaptive offset sample adaptive offset
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| GB/T 7714 | Chen, J. , Qin, L. , Wang, W. et al. Optimized design of sample adaptive offset filter with low complexity; [低复杂度样点自适应补偿滤波器的优化设计] [J]. | Chinese Journal of Scientific Instrument , 2023 , 44 (6) : 293-302 . |
| MLA | Chen, J. et al. "Optimized design of sample adaptive offset filter with low complexity; [低复杂度样点自适应补偿滤波器的优化设计]" . | Chinese Journal of Scientific Instrument 44 . 6 (2023) : 293-302 . |
| APA | Chen, J. , Qin, L. , Wang, W. , Yang, X. , Chen, P. . Optimized design of sample adaptive offset filter with low complexity; [低复杂度样点自适应补偿滤波器的优化设计] . | Chinese Journal of Scientific Instrument , 2023 , 44 (6) , 293-302 . |
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高效视频编码标准引入了样点自适应补偿(SAO)滤波,可去除由高频信息丢失而产生的振铃效应,但是也极大增加了环路滤波的复杂度.本文提出一种低复杂度的样点自适应补偿滤波器的算法优化和实现方案.对信息统计范围进行区域优化,避免了跨编码树单元边界的复杂逻辑控制,并节省了额外缓存结构;提出一种快速计算率失真代价的三维线性码率估计模型,以此权衡率失真优化中SAO模式决策复杂度和码率模型精确度;最后,基于上述算法改进设计了适用于超高清视频处理的SAO硬件滤波器,该架构仅以 85.6 k等效门消耗,支持高达 333 MHz主频的超高清视频处理,其逻辑资源消耗相对于传统方案最高可节省 71.47%.
Keyword ：
样点自适应补偿 样点自适应补偿 率失真优化 率失真优化 环路滤波 环路滤波 硬件设计 硬件设计 高效视频编码 高效视频编码
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| GB/T 7714 | 陈建 , 覃露 , 王卫坤 et al. 低复杂度样点自适应补偿滤波器的优化设计 [J]. | 仪器仪表学报 , 2023 , 44 (6) : 293-302 . |
| MLA | 陈建 et al. "低复杂度样点自适应补偿滤波器的优化设计" . | 仪器仪表学报 44 . 6 (2023) : 293-302 . |
| APA | 陈建 , 覃露 , 王卫坤 , 杨秀芝 , 陈平平 . 低复杂度样点自适应补偿滤波器的优化设计 . | 仪器仪表学报 , 2023 , 44 (6) , 293-302 . |
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Since facial forgery techniques have made remarkable progress, the area of forgery detection attracts a significant amount of attention due to security concerns. Existing methods attempt to utilize convolutional neural networks (CNNs) to mine discriminative clues for forgery detection. However, most of these coarse-grained and vanilla methods struggle to extract subtle and multiscale clues in forgery detection. To address such problems, we propose a well-designed deep learning framework, named SCA-Net, to exploit subtle, multiscale and multiview clues. Specifically, our framework consists of a skipped channel attention module (SCM), a constrained difference module (CDM) and an adaptive attention module (AAM). First, the skipped channel attention module is used as the backbone to extract sufficient different information, including low-level and high-level features. Then, the constrained difference module captures manipulation clues from the input image based on constrained characteristics. Finally, the adaptive attention module captures multiscale features represented by facial forgery. Moreover, we introduce a combined loss to address the learning difficulty of our framework. The experimental results demonstrate that the proposed model has great detection performance compared with other face forgery detection methods in most cases. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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| GB/T 7714 | Su, L. , Wu, B. , Dai, C. et al. Learning to Detect Deepfakes via Adaptive Attention and Constrained Difference [未知]. |
| MLA | Su, L. et al. "Learning to Detect Deepfakes via Adaptive Attention and Constrained Difference" [未知]. |
| APA | Su, L. , Wu, B. , Dai, C. , Luo, H. , Chen, J. . Learning to Detect Deepfakes via Adaptive Attention and Constrained Difference [未知]. |
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针对现有交通系统中的车流量检测技术无法同时兼顾应用成本、计数精度、性能稳定的问题，提出一种基于模糊车流量信息的拥堵状况判断方法，并将其应用在基于ZYNQ-7020的智能交通系统中。这种估计方法兼顾实时交通数据的排队长度和等待时间，得出一个拥堵程度的模糊预测值。将该方法集成进拥堵程度估计的软件处理模块，与基于现场可编程逻辑门阵列（Field Programmable Gate Array,FPGA）硬件逻辑的视频采集模块和交通灯控制模块等一同组成智能交通SOPC系统，根据实时车流量动态调整路口红绿灯时长，从而提高路口交通效率。实验结果表明，拥堵程度估计模块给出的拥堵程度估计值可以近似表示道路的拥堵程度，系统实时性高、集成度高，具有一定的实用价值和推广应用前景。
Keyword ：
拥堵程度估计 拥堵程度估计 智能交通系统 智能交通系统 车流量检测技术 车流量检测技术
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| GB/T 7714 | 苏德福 , 陈彬晖 , 林诗雨 et al. 基于模糊车流量估计的智能交通系统SOPC设计 [J]. | 电视技术 , 2023 , 47 (05) : 41-44,50 . |
| MLA | 苏德福 et al. "基于模糊车流量估计的智能交通系统SOPC设计" . | 电视技术 47 . 05 (2023) : 41-44,50 . |
| APA | 苏德福 , 陈彬晖 , 林诗雨 , 陈冬杰 , 张昂 , 陈建 . 基于模糊车流量估计的智能交通系统SOPC设计 . | 电视技术 , 2023 , 47 (05) , 41-44,50 . |
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