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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Gilberto Kreisler Garibaldi da Silveira Júnior Bruno Zatt Daniel Palomino Guilherme Correa Video Technology Research Group - ViTech Graduate Program in Computing - UFPel Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

Lossy video compression introduces visual artifacts that degrade video quality, where deep neural networks (DNNs) are effective in enhancement. However, conventional DNN-based methods often focus on a single video compression standard, limiting their deployment in multiple cases. To overcome this issue, this study introduces a multi-domain video quality enhancement architecture based on the Spatio-Temporal Deformable Fusion (STDF) technique. This method enables the model to enhance videos compressed with multiple codecs, maintaining reliable performance across standards. After trained, the proposed architecture was tested with videos compressed by the High Efficiency Video Coding (HEVC) encoder, the Versatile Video Coding (VVC) encoder, the VP9 codec and the AOMedia Video 1 (AV1) codec. Results show an average Peak Signal-to-Noise Ratio (PSNR) improvement between 0.228 dB and 0.787 dB.

关键词： Training Visualization Codecs PSNR Artificial neural networks Video compression Quality assessment Video recording Standards High efficiency video coding

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A Coding Efficiency-Aware Hardware Design for VVC Affine Motion Estimation Reconstructor

IEEE Design and Test

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IEEE Design and Test 2025年

作者： Muñoz, Marcello M. Maass, Denis Perleberg, Murilo Agostini, Luciano Corrêa, Guilherme Porto, Marcelo Graduate Program in Computing - PPGC Video Technology Research Group ViTech Federal University of Pelotas - UFPel Pelotas Brazil

One of the most important new tools of the Versatile Video Coding (VVC) standard is the Affine Motion Estimation (AME). The AME contribution to the coding efficiency comes with a high computational cost, especially for real-time high-resolution video encoding, making dedicated hardware for battery-powered devices mandatory. Considering this scenario, this work presents a dedicated hardware design for the Affine Reconstructor of the VVC standard, focusing on high coding efficiency for real-time processing of UHD video. ASIC synthesis results show a circuit area of 179.9k Gates, with a power dissipation of 107.76 mW when targeting the processing of 4K UHD@60fps videos. The proposed design shows the lowest impact in BD-Rate (only 0.54%) in the current literature. © 2013 IEEE.

关键词： Motion estimation

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Vision-Based Landing Guidance Through Tracking and Orientation Estimation

Vision-Based Landing Guidance Through Tracking and Orientati...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： João P. K. Ferreira João P. Pinto Júlia Moura Yi Li Cristiano L. Castro Plamen Angelov Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais School of Computing and Communications Lancaster University

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Fixed-wing aerial vehicles are equipped with functional-ities such as ILS (instrument landing system), PAR (precision approach radar) and, DGPS (differential global positioning system), enabling fully automated landings. How-ever, these systems impose significant costs on airport op-erations due to high installation and maintenance requirements. Moreover, since these navigation parameters come from ground or satellite signals, they are vulnerable to in-terference. A more cost-effective and independent alternative for guiding landing is a vision-based system that de-tects the runway and aligns the aircraft, reducing the pi-lot's cognitive load. This paper proposes a novel frame-work that addresses three key challenges in developing au-tonomous vision-based landing systems. Firstly, to over-come the lack of aerial front-view video data, we created high-quality videos simulating landing approaches through the generator code available in the LARD (landing approach runway detection dataset) repository. Secondly, in contrast to former studies focusing on object detection for finding the runway, we chose the state-of-the-art model Lo-RAT to track runways within bounding boxes in each video frame. Thirdly, to align the aircraft with the designated landing runway, we extract runway keypoints from the re-sulting LoRAT frames and estimate the camera relative pose via the Perspective-n-Point algorithm. Our experimental re-sults over a dataset of generated videos and original images from the LARD dataset consistently demonstrate the proposed framework's highly accurate tracking and alignment capabilities. Our approach source code and the Lo-RAT model pre-trained with LARD videos are available at https://***/jpklock2/vision-based-landing-guidance

关键词： Visualization Codes Accuracy Atmospheric modeling Pose estimation Video sequences Radar tracking Generators Aircraft navigation Global Positioning System

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Quality-Reconfigurable Approximate Multiplier Utilizing Select Leading One-Bit Blocks

Quality-Reconfigurable Approximate Multiplier Utilizing Sele...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： João M. Bedin Pedro T. L. Pereira Rodrigo N. Wuerdig Eduardo Da Costa Sergio Bampi Graduate Program in Microelectronics (PGMicro) - Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Graduate Program in Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

Multipliers are essential for emerging technologies, as they are vital arithmetic circuits in many energy-efficient applications, such as digital signal processing and machine learning applications. Approximate multipliers (AxM) became an optimal option for applications in ASIC systems with error tolerance. This paper proposes to develop a run-time reconfigurable AxM with four approximation levels in a single circuit, evaluating accuracy and circuit metrics (e.g., circuit area, timing, and power consumption) based on the leading one-bit-based approximate (LoBA) multiplier. The results achieve a circuit area reduction of 52% less area and up to 27% less power consumption when compared with equivalent architecture based on LoBA state-of-art. Applying the proposed RLoBA to a normalized least mean square (NLMS) adaptive filter case study, we obtain 22.95% less power consumption using dynamic approximate level selection than the precise multiplier while maintaining the same accuracy level.

关键词： Measurement Power demand Accuracy Circuits Adaptive filters Machine learning Lead Timing Reconfigurable architectures Standards

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Computational Cost Analysis and Reduction of VVC Multiple Transform Selection

Computational Cost Analysis and Reduction of VVC Multiple Tr...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Caroline Camargo Bianca Silveira Guilherme Correa Video Technology Research Group - ViTech Graduate Program in Computing - PPGC Federal University of Pelotas - UFPel Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

The growing demand for high-definition online videos emphasizes the need for efficient video codecs like H.266/VVC, which offer significant compression potential. However, its implementation presents challenges, particularly in terms of computational cost, as is the case of the Multiple Transform Selection (MTS) tool. This study analyzes the performance of MTS modes, showing that explicit MTS improves coding efficiency but increases encoding time, while implicit MTS offers modest efficiency gains with less computational cost. A machine learning-based approach is proposed, using decision trees, to accelerate encoder decisions for both intra and inter predicted blocks in explicit MTS, reducing encoding time by an average of 7.98%, with only a 0.89% increase in BD-rate. These results highlight the potential for optimization of explicit MTS in both intra and inter transformations.

关键词： Circuits and systems Transforms Machine learning Encoding Computational efficiency Decision trees Video codecs Optimization Videos

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Evaluation of Coarse-to-Fine Spatio-Temporal Information Fusion (CF-STIF) Network

Evaluation of Coarse-to-Fine Spatio-Temporal Information Fus...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Luis Carlos Linares Gilberto Kreisler Daniel Palomino Guilherme Corrêa Bruno Zatt Video Technology Research Group (ViTech) Graduate Program in Computing (PPGC) Federal University of Pelotas (UFPel) Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

This paper presents an evaluation of the Coarse-to-Fine Spatio-Temporal Information Fusion (CF-STIF) network for enhancing the quality of compressed videos across multiple codecs, including HEVC, VVC, VP9, and AV1. The CF-STIF network leverages spatiotemporal fusion and deep learning techniques to reduce compression artifacts and improve video quality. The evaluation extends existing methods by employing multiple quality metrics such as PSNR, SSIM, LPIPS. The CF-STIF network has been integrated with the Spatio-Temporal Deformable Fusion (STDF) training scheme in order to execute the model. Results demonstrate that CF-STIF achieves the highest quality improvements for HEVC-encoded videos, with an average PSNR increase of 0.813 dB and superior visual quality as measured by SSIM. However, the performance significantly drops for other codecs, particularly AV1, highlighting the need for future adaptations to optimize CF-STIF for diverse compression standards.

关键词： Training Deep learning Adaptation models Visualization Codecs Computational modeling Computer architecture Quality assessment Standards Videos

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Fast VVC Test Zone Search and Affine Motion Estimation Using Machine Learning

Fast VVC Test Zone Search and Affine Motion Estimation Using...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Ramiro Viana Marta Loose Ruhan Conceição Marcelo Porto Guilherme Corrêa Luciano Agostini Video Technology Research Group (ViTech) Graduate Program in Computing (PPGC) Federal University of Pelotas (UFPel) Pelotas/RS Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

As the demand for video transmission surges on remote work, education, and streaming services, the need for continuous advancements in video encoding technologies becomes increasingly evident. Adapting to the evolving requirements of efficient video delivery and consumption necessitates ongoing development and enhancement in video encoding standards, with Versatile Video Coding (VVC) emerging as a notable example. This paper provides an overview of key algorithms within InterFrame prediction of VVC, mainly focusing on the Test Zone Search (TZS) and the Affine Motion Estimation (AME), two of the most computationally intensive tools inside the VVC. Furthermore, this paper introduces a fast TZS and AME approach using Machine Learning, specifically employing Decision Trees. The proposed approach achieved an average reduction of over $\mathbf{2 0 \%}$ in total VVC encoding time while maintaining less than a 1 % impact on BD-BR coding efficiency.

关键词： Video coding Motion estimation Machine learning Streaming media Encoding Software Remote working Decision trees Surges Standards

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FIFS: A Machine Learning-Based Fast AV1 Interpolation Filter Search

FIFS: A Machine Learning-Based Fast AV1 Interpolation Filter...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： William Kolodziejski Marcelo Porto Luciano Agostini Video Technology Research Group (ViTech) Graduate Program in Computing (PPGC) Federal University of Pelotas (UFPel) Pelotas RS Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

AV1 is a codec developed by huge technology companies to be used in current and future commercial video applications. It introduces and improves several tools from its predecessor VP9, designed for various video scenarios. One of the improved tools is the Fractional Motion Estimation (FME), which generates sub-pixel predictors. AV1 employs four sets of interpolation filters, requiring significant computational effort during the Interpolation Filter Search (IFS) to identify the best filter to be used. This work proposes the FIFS, a machinelearning method developed to reduce the processing time of IFS while maintaining minimal impact on coding efficiency. This method achieves over 52% reductions in IFS time, with only a slight increase in BD-BR of $\mathbf{0.14 \%}$ . To the best of the authors' knowledge, this is the first work in the literature to propose a machine learning-based approach for the AV1 IFS.

关键词： Video coding Interpolation Filters Codecs Motion estimation Computational modeling Focusing Machine learning Companies Encoding

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Load Balancing to Optimize MPEG-DASH Video Streaming

Load Balancing to Optimize MPEG-DASH Video Streaming

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International Conference on Information Networking

作者： Edenilson Jônatas Dos Passos Adriano Fiorese Department of Computer Science (DCC) Graduate Program in Apllied Computing (PPGCAP) Santa Catarina State University (UDESC) Joinville Brazil

ISBN: (数字)9798331506940

ISBN: (纸本)9798331506957

Recent advancements in on-demand multimedia streaming have revealed the potential of this business model, driven by the convenience of accessing content anytime and anywhere. However, delivering a seamless user experience remains challenging due to the demanding nature of audiovisual streams, despite significant resource allocation. A promising solution involves using load balancers to distribute workloads evenly among processing units. This study proposes optimizing the processing and transmission resources by means of Software-Defined Networks (SDN). By continuously monitoring performance metrics like CPU usage and throughput, the SDN network controller determines the best server for handling new connections, even allowing seamless server migration during playback. The results show up to 80% faster response times and more consistent video quality, with reduced latency and uninterrupted playback. The approach also confirms the feasibility of SDN in streaming services, providing a foundation for future network improvements.

关键词： Transform coding Streaming media Load management User experience Quality assessment Servers Time factors Software defined networking Video recording Monitoring

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Damage-Free Neutral Beam Etching for Gate Recess in E-Mode AlGaN/GaN HEMTs

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年第5期46卷 705-708页

作者： Chen, Yi-Ho Chu, Fu-Chuan Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering Hsinchu300093 Taiwan National Chung-Shan Institute of Science and Technology Solid State Devices Section Electronic System Research Division Taoyuan325 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

Recess gate etching is a critical technique for achieving enhancement-mode (E-mode) AlGaN/GaN high-electron mobility transistors (HEMTs) because the interface is susceptible to the etching damage. This study fabricates recess gates using the neutral beam etching (NBE) technique. By adjusting the aperture thickness in the NBE apparatus, we simulate both NB-mode and plasma-mode etching. The electrical characteristics of E-mode HEMTs fabricated using these two modes are analyzed and compared through DC, noise, and pulsed IV measurements. The results demonstrate that NB-recessed HEMTs exhibit superior performance. © 1980-2012 IEEE.

关键词： Aluminum gallium nitride

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