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Fast intra coding based on mode decision in high efficiency video coding

Fast intra coding based on mode decision in high efficiency ...

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2014 International conference on Artificial Intelligence and Industrial Application (AIIA2014)

作者： Q.Li G.S.Tian C.Q.Gao Chongqing Key Laboratory of Signal and Information Processing(CQKLS&IP) Chongqing University of Posts and Telecommunications (CQUPT)

ISBN: (纸本)9781784660529

The latest high efficiency video coding(HEVC) standard has a significantly improved compression performance relative to H.264/AVC, only requiring a 50% bit-rate at the equal perceptual video quality, but with a significant encoder complexity increase. Hence it is necessary and inevitable to develop fast HEVC encoding algorithms for potential market adoption. In this paper, we propose a fast intra mode decision(FMD) for a HEVC encoder, which aims at reducing computation time and keeping the coding performance at the same time. Firstly, we use edge information of the current prediction unit(PU) instead of only the modes of the neighbor PUs to choose a reduced set of directions from the 35 prediction mode directions. Next, we use an early termination rate-distortion optimized(RDO) to further reduce complexity. Different picture resolutions, ranging from 416×240 to 2560×1600 are tested and experimental results show that the proposed algorithm can reduce 32.64% encoding time with only a 1.45% increase in BD rate.

关键词： fast encoding algorithm HEVC intra prediction edge information

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Rethinking the Up-Sampling Operations in CNN-Based Generative Network for Generalizable Deepfake Detection

Rethinking the Up-Sampling Operations in CNN-Based Generativ...

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Chuangchuang Tan Huan Liu Yao Zhao Shikui Wei Guanghua Gu Ping Liu Yunchao Wei Institute of Information Science Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology School of Information Science and Engineering Yanshan University Hebei Key Laboratory of Information Transmission and Signal Processing CSE department University of Nevada Reno USA

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Recently, the proliferation of highly realistic synthetic images, facilitated through a variety of GANs and Diffusions, has significantly heightened the susceptibility to misuse. While the primary focus of deepfake detection has traditionally centered on the design of detection algorithms, an investigative inquiry into the generator architectures has remained conspicuously absent in recent years. This paper contributes to this lacuna by rethinking the architectures of CNN-based generator, thereby establishing a generalized representation of synthetic artifacts. Our findings illuminate that the up-sampling operator can, beyond frequency-based artifacts, produce generalized forgery artifacts. In particular, the local interdependence among image pixels caused by upsampling operators is significantly demon-strated in synthetic images generated by GAN or diffusion. Building upon this observation, we introduce the concept of Neighboring Pixel Relationships(NPR) as a means to capture and characterize the generalized structural artifacts stemming from up-sampling operations. A comprehensive analysis is conducted on an open-world dataset, comprising samples generated by 28 distinct generative models. This analysis culminates in the establishment of a novel state-of-the-art performance, showcasing a remarkable 12.8% im-provement over existing methods. The code is available at https://***/chuangchuangtan/NPR-DeepfakeDetection.

关键词： Deepfakes Computer vision Frequency-domain analysis Computer architecture Detectors Generative adversarial networks Generators

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Comparative Performance Analysis of Edge-AI Devices in Deep Learning Applications

Comparative Performance Analysis of Edge-AI Devices in Deep ...

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IEEE conference on Industrial Electronics and Applications (ICIEA)

作者： Muhammad Hafiz Samsuri Shang Li Yuen Phooi Yee Lau Chin Wee Wong Nur Afiqah Kamarudin Zarina Hussin Muhammad Syukri Mohd Talib Hock Woon Hon Advanced Intelligence Lab MIMOS Berhad Kuala Lumpur Malaysia

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

The fusion of edge computing and artificial intelligence, known as Edge AI, represents a paradigm shift that facilitates the direct execution of AI algorithms on edge devices. As these devices become increasingly powerful, their role in developing and deploying AI systems becomes more significant. By eliminating the need to transmit and analyze data at remote machines, Edge AI applications can significantly reduce latency and enhance efficiency by processing data closer to the source. In this study, we thoroughly investigate the performance of our object classification model deployed in a vision inspection system on four types of edge devices (Jetson AGX Orin, Jetson Orin Nano, NUC, and Raspberry Pi). Our object classification models are trained using proprietary industrial datasets provided by industry partners. These models, in FP32, are converted into lower precision processing, being INT8, to evaluate the accuracy variation between FP32 and INT8 precision, and inference speed for different edge devices. In our experiments, we identified that the average accuracy deviation for INT8 models is −2.78%, with some models exhibiting variations exceeding −10.95%. Most devices have an average inference speed less than 100 ms per image (as requested by industrial partners), except the Raspberry Pi, which records more than 2 seconds of inferencing an image. Intel NUC consumes 107 W, which is averagely comparable with a server PC, while AGX Orin, Orin Nano, and Raspberry Pi consume less than 20 W of power. The outcomes of our evaluations offer valuable insights for selecting appropriate devices for specific scenarios. These detailed observations on the strengths and limitations of different edge devices can guide future research and advancements in Edge AI technology.

关键词： Performance evaluation Industries Accuracy Quantization (signal) Costs Power demand Edge AI

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Broadband Beamforming via Frequency Invariance Transformation and PARAFAC Decomposition for Jamming Mitigation in V2X Scenarios

Broadband Beamforming via Frequency Invariance Transformatio...

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IEEE conference on Vehicular Technology (VTC)

作者： Daniel V. de Lima João Paulo J. da Costa Antonio Arlis S. da Silva Giovanni A. Santos José Alfredo R. Vargas Auzuir R. de Alexandria Postgraduate Program in Telecommunications Engineering (PPGET) IFCE Fortaleza Brazil Hamm-Lippstadt University of Applied Sciences (HSHL) Lippstadt Germany Graduate School for Applied Research in North Rhine-Westphalia (PKNRW) Bochum Germany Karlsruhe Institute of Technology (KIT) Karlsruhe Gennany Graduate Program in Computing (PPGC) UFRGS Porto Alegre Brazil Department of Electrical Engineering UnB Brasilia Brazil

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Vehicle-to-Everything (V2X) communication can considerably improve the efficiency and safety of autonomous driving and advanced driver-assistance systems (ADASs). However, V2X communication can be considerably degraded in the presence of cyberattacks, such as radio jamming. Traditionally, beamforming techniques can be applied to increase the signal-to-interference plus noise ratio (SINR). This paper evaluates broadband beamforming in the mmWave spectrum against radio jamming in V2X communication. The exploitation of the mm Wave spectrum in 5G-V2X communication has a natural advantage against radio jamming. First, attenuation is stronger in the mmWave spectrum in the range of 40 GHz or higher than in the traditional 5.9 GHz. Second, to generate broadband radio jamming, the radio jammer requires much more complex hardware and energy consumption. Third, by using broadband beamforming, broadband radio jamming can be considerably attenuated, limiting the degradation of the spectrum by the radio jamming. According to our numerical results, gains of close to 30 dB SINR can be achieved. We propose a broad-band beamforming technique based on the canonical polyadic decomposition via generalized eigenvalue decomposition (CPD-GEVD). The CPD-GEVD broadband beamforming outperforms state-of-the-art beamforming algorithms in most V2X scenarios presented in this paper.

关键词： Vehicular and wireless technologies Array signal processing Interference Attenuation Broadband communication Jamming Millimeter wave communication

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Performance of Mobile Networks with UAVs: Can Flying Base Stations Substitute Ultra-Dense Small Cells?

Performance of Mobile Networks with UAVs: Can Flying Base St...

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European Wireless 2017;23th European Wireless conference

作者： Zdenek Becvar Michal Vondra Pavel Mach Jan Plachy David Gesbert Dpt. of Telecommunication Engineering FEE Czech Technical University in Prague Communication Systems Department EURECOM

ISBN: (纸本)9781509038442

A crucial challenge for future mobile networks is to enable wide range of scenarios and use cases for different devices spanning from simple sensors to advanced machines or users devices. Such requirements call for highly flexible and scalable radio access network (RAN). To provide high flexibility and scalability in dynamic scenarios, flying base stations (FlyBSs), i.e., base stations mounted on general unmanned aerial vehicles, can be integrated into RAN. In this paper, implementation and operational issues related to the FlyBSs are discussed. Additionally scenarios where the FlyBS can be profitable are outlined. Furthermore, we define the architecture of a flying RAN (FlyRAN) encompassing the FlyBSs and enabling real-time control of whole RAN so that it can dynamically adapt to users' movement and changes in their communication activity. Our results show the superior efficiency of FlyBSs comparing to an ultra-dense deployment of static base stations (BSs) for a realistic scenario with moving users. Our simulations suggest that one FlyBS can provide throughput comparable to static BSs deployed with density corresponding to inter-site distance of 45 meters. At the same time, energy efficiency of the communication for the user equipment can be improved more than 5-times. This indicates that integration of the FlyBSs into mobile networks can be an efficient alternative to ultra-dense small cell deployment, especially in scenarios with users moving in crowds.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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Analyzing the Relationship Between Head Pose and Gaze to Model Driver Visual Attention

Analyzing the Relationship Between Head Pose and Gaze to Mod...

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IEEE International conference on Intelligent Transportation Systems

作者： Sumit Jha Carlos Busso Multimodal Signal Processing Lab at the University of Texas at Dallas

ISBN: (纸本)9781509018901

Monitoring driver behavior is crucial in the design of advanced driver assistance systems (ADAS) that can detect driver actions, providing necessary warnings when not attentive to driving tasks. The visual attention of a driver is an important aspect to consider, as most driving tasks require visual resources. Previous work has investigated algorithms to detect driver visual attention by tracking the head or eye movement. While tracking pupil can give an accurate direction of visual attention, estimating gaze on vehicle environment is a challenging problem due to changes in illumination, head rotations, and occlusions (e.g. hand, glasses). Instead, this paper investigates the use of the head pose as a coarse estimate of the driver visual attention. The key challenge is the non-trivial relation between head and eye movements while glancing to a target object, which depends on the driver, the underlying cognitive and visual demand, and the environment. First, we evaluate the performance of a state-of-the-art head pose detection algorithm over natural driving recordings, which are compared with ground truth estimations derived from AprilTags attached to a headband. Then, the study proposes regression models to estimate the drivers' gaze based on the head position and orientation, which are built with data from natural driving recordings. The proposed system achieves high accuracy over the horizontal direction, but moderate/low performance over the vertical direction. We compare results while our participants were driving, and when the vehicle was parked.

关键词： Visualization Cameras Magnetic heads Head Roads Automobiles

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Approaching the maximum energy saving on embedded systems with multiple voltages 03

Approaching the maximum energy saving on embedded systems wi...

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IEEE International conference on Computer-Aided Design

作者： Shaoxiong Hua Gang Qu Electrical and Computer Engineering Department and Institute for Advanced Computer Studies University of Maryland College Park MD USA

ISBN: (纸本)1581137621

Dynamic voltage scaling (DVS) is arguably the most effective energy reduction technique. The multiple-voltage DVS systems, which can operate only at pre-determined discrete voltages, are practical and have been well studied. However, one important unsolved problem is how many levels and at which values should voltages be implemented on a multiple-voltage DVS system to achieve the maximum energy saving. We refer this as the voltage set-up problem. In this paper, (1) we derive analytical solutions for dual-voltage system. (2) For the general case that does not have analytic solutions, we develop efficient numerical methods. (3) We demonstrate how to apply the proposed algorithms on system design. (4) Interestingly, the experimental results suggest that the multiple-voltage DVS system, when the voltages are set up properly, can reach DVS technique's full potential in energy saving. Specifically, on the design of an ad hoc application-specific system and the design of the MPEG video encoder, we find that the best single-voltage systems consume 150% and 20% more energy than the tight theoretical lower bounds, respectively. However, our approach gives dual-, 3-, and 4-voltage DVS system settings that are only 17.6%, 4.9%, and 2.6% for the ad hoc system, and 4.0%, 1.1%, and 0.2% for the MPEG video encoder, over the same lower bounds.

关键词： Embedded system Voltage control Dynamic voltage scaling Energy consumption Algorithm design and analysis Data flow computing Power engineering and energy Educational institutions Potential energy Digital signal processing

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A High-dynamic Null-widen GPS Anti-jamming Algorithm Based on Statistical Model of The Changing Interference DOA

A High-dynamic Null-widen GPS Anti-jamming Algorithm Based o...

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第五届中国卫星导航学术年会

作者： Yanxin Ma Dan Lu Wenyi Wang Lu Wang Renbiao Wu Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Tianjin China

ISBN: (纸本)9783642547362

The directions of arrival(DOA) of interference changes rapidly with time in high-dynamic satellite navigation system, which leads to the mismatch between weights training data and weights applying data during the adaptive processing. In this case, the conventional adaptive anti-jamming algorithms are invalid since jammers may easily move out of the array pattern nulls and could not be suppressed. In this letter, a novel method of null-widen is deduced based on the Laplace distribution model of the changing interference DOA in high-dynamic environment. By taking the moving interferences as discrete interference sources obey the Laplace distribution, the extension matrix can be obtained and the average covariance matrix can be calculated from matrix product to broaden the width of nulls. The new method does not alter the noise contribution to the covariance matrix and does not require information about interference DOA. The width of nulls is easy to control. In addition, by combining with the power minimization approach, the new null-widen method does not need the DOA of desired satellite signal. The proposed method can provide correctly acquisition.

关键词： GPS·High‐dynamic·interference suppression·null widening·adaptive array·Laplace distribution

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Fuzzy inference and fusion for health state diagnosis of hydraulic pumps and motors

Fuzzy inference and fusion for health state diagnosis of hyd...

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conference of the North American Fuzzy Information processing Society - NAFIPS

作者： S. Amin C. Byington M. Watson State College Impact Technologies LLC PA USA

An in-line health monitoring system has been developed for hydraulic pumps that utilize feature extraction, fuzzy inference systems, and knowledge fusion. These techniques were applied to hydraulic pump diagnostics in order to create a robust system for the determination and classification of pump degradation. A thorough examination of available measurements identified three critical parameters: pump pressure, case drain flow, and case drain temperature as strong indicators of impending pump failure. Using machinery vibration analysis techniques, dynamic analysis of the high frequency "noise" content of pump pressure and case drain signals was performed to provide reliable diagnostic features. A physics-based approach was also implemented to model performance characteristics of the pump. An Automated Health Assessment and Fusion stage was then implemented to correlate changes in these diagnostic features to pump health using one of five linguistic degradation categories, determined using a Mamdani-type fuzzy logic inference architecture. Fuzzy logic-based classification was performed for each analysis approach and fused using Bayesian knowledge fusion techniques. This fusion also incorporated a priori information, in the form of historical failure rate data and operational hours, to provide a real-time health output supplemented with a confidence interval. This paper reviews the technical approach implemented for a hydraulic pump in-line health monitoring system, specifically addressing the application and utility of fuzzy logic inference in hydraulic pump health assessment. Also briefly reviewed here are details regarding the advanced feature extraction process, Bayesian knowledge fusion, and the transition of the algorithms to a prototype embedded system. Finally, results are presented using pump degradation data from accelerated endurance tests provided by The Air Force Research Laboratory (AFRL) to validate the approach. These results demonstrate a robust infere

关键词： Pumps Degradation Performance analysis Fuzzy logic Feature extraction signal analysis Bayesian methods Monitoring Fuzzy systems Noise robustness

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Algorithm-Hardware Co-Design for Energy-Efficient A/D Conversion in ReRAM-Based Accelerators

Algorithm-Hardware Co-Design for Energy-Efficient A/D Conver...

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Design, Automation and Test in Europe conference and Exhibition

作者： Chenguang Zhang Zhihang Yuan Xingchen Li Guangyu Sun School of Integrated Circuits Peking University Beijing China School of Computer Science Peking University Beijing China Beijing Advanced Innovation Center for Integrated Circuits Beijing China

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

Deep neural networks are widely deployed in many fields. Due to the in-situ computation (known as processing in memory) capacity of the Resistive Random Access Memory (ReRAM) crossbar, ReRAM-based accelerator shows potential in accelerating DNN with low power and high performance. However, despite power advantage, such kind of accelerators suffer from the high power consumption of peripheral circuits, especially Analog-to-Digital Converter (ADC), which account for over 60 percent of total power consumption. This problem hinders the ReRAM-based accelerator to achieve higher efficiency. Some redundant Analog-to-Digital conversion operations have no contribution to maintaining inference accuracy, and such operations can be eliminated by modifying the ADC searching logic. Based on such observations, we propose an algorithm-hardware co-design method and explore the co-design approach in both hardware design and quantization algorithms. Firstly, we focus on the distribution output along the crossbar's bit-lines and identify the fine-grained redundant ADC sampling bits. To further compress ADC bits, we propose a hardware-friendly quantization method and coding scheme, in which different quantization strategy was applied to the partial results in different intervals. To support the two features above, we propose a lightweight architectural design based on SAR-ADC. It's worth mentioning that our method is not only more energy efficient but also retains the flexibility of the algorithm. Experiments demonstrate that our method can reduce about $1.6\sim 2.3\times$ ADC power reduction.

关键词： Adaptation models Quantization (signal) Power demand Resistive RAM Artificial neural networks Search problems Hardware

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