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检索条件"任意字段=15th Symposium on Computer Architecture and High Performance Computing"

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Offline Versus Online Triplet Mining Based on Extreme Distances of Histopathology Patches 15th

Offline Versus Online Triplet Mining Based on Extreme Distan...

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15th International symposium on Visual computing, ISVC 2020

作者： Sikaroudi, Milad Ghojogh, Benyamin Safarpoor, Amir Karray, Fakhri Crowley, Mark Tizhoosh, Hamid R. KIMIA Lab University of Waterloo WaterlooON Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooON Canada

ISBN: (纸本)9783030645557

We analyze the effect of offline and online triplet mining for colorectal cancer (CRC) histopathology dataset containing 100,000 patches. We consider the extreme, i.e., farthest and nearest patches to a given anchor, both in online and offline mining. While many works focus solely on selecting the triplets online (batch-wise), we also study the effect of extreme distances and neighbor patches before training in an offline fashion. We analyze extreme cases’ impacts in terms of embedding distance for offline versus online mining, including easy positive, batch semi-hard, batch hard triplet mining, neighborhood component analysis loss, its proxy version, and distance weighted sampling. We also investigate online approaches based on extreme distance and comprehensively compare offline, and online mining performance based on the data patterns and explain offline mining as a tractable generalization of the online mining with large mini-batch size. As well, we discuss the relations of different colorectal tissue types in terms of extreme distances. We found that offline and online mining approaches have comparable performances for a specific architecture, such as ResNet-18 in this study. Moreover, we found the assorted case, including different extreme distances, is promising, especially in the online approach. © 2020, Springer Nature Switzerland AG.

关键词： Diseases

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Parameter-Free Outlier Scoring Algorithm Using the Acute Angle Order Difference Distance 15th

Parameter-Free Outlier Scoring Algorithm Using the Acute Ang...

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15th International Conference on computing and Information Technology, IC2IT 2019

作者： Pumruckthum, Pollaton Boonsiri, Somjai Sinapiromsaran, Krung Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok10330 Thailand

ISBN: (纸本)9783030198602

An anomaly scoring algorithm assigns the anomalous rating to an instance in a dataset which provides a large value for an outlier. In 2013, one of the parameter-free techniques called the Ordered Difference Distance Outlier Factor algorithm is proposed. It calculates a score using an ordered difference distance among all instances which derives from the distance matrix sorted in each row before computing the difference. the score contribution from other instances must be compared with the global minimum distance to avoid misdetecting boundaries. However, this degrades the performance of the detection rate. To avoid the use of the global minimum distance term, the new technique is proposed using the ordered difference distance along the appropriate direction based on the acute angle. this technique is called the acute angle ordered difference distance outlier factor (AOF) algorithm. three collections of ten synthesized datasets are designed to show the performance of AOF. the AOF algorithm reports very high scores for anomalies in synthetic datasets and has better performance than OOF when the anomalies are close together. © 2020, Springer Nature Switzerland AG.

关键词： Anomaly detection

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X-architecture Steiner Minimal Tree Construction Based on Discrete Differential Evolution 15th

X-Architecture Steiner Minimal Tree Construction Based on Di...

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15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th International Conference on Harmony Search, Soft computing and Applications, ICHSA 2019

作者： Wu, Hailin Xu, Saijuan Zhuang, Zhen Liu, Genggeng College of Mathematics and Computer Sciences Fuzhou University Fuzhou350116 China Department of Information Engineering Fujian Business University Fuzhou350012 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350116 China

ISBN: (纸本)9783030324551

As the best connection model for the multi-pin net of the non-Manhattan architecture global routing problem, the X-architecture Steiner Minimum Tree (XSMT) construction is a Non-deterministic Polynomial hard (NP-hard) problem. the Differential Evolution (DE) algorithm has shown good application effect in solving various NP-hard problems. For this reason, based on the idea of DE algorithm, this paper proposes an XSMT construction algorithm for solving this problem. First of all, because the traditional DE algorithm is designed for continuous problems, the optimization ability is limited in solving discrete problems. this paper proposes a novel crossover operator and mutation operator. At the same time, in order to maintain the effectiveness of the evolutionary algorithm, an Edge-to-Point coding strategy suitable for evolutionary algorithms is proposed to better preserve the optimal substructure of the population. Finally, in order to speed up the convergence speed and quality of the algorithm, this paper proposes an initial solution based on the minimum tree generation algorithm. Experiments show that the effectiveness of the proposed algorithm and related strategies can construct a high-quality XSMT solution. © Springer Nature Switzerland AG, 2020.

关键词： Evolutionary algorithms

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HPM-FSI: A high-performance Algorithm for Mining Frequent Significance Itemsets 15th

HPM-FSI: A High-Performance Algorithm for Mining Frequent Si...

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作者： Phan, Huan Le, Bac Faculty of Mathematics and Computer Science University of Science VNU-HCMC Ho Chi Minh City Viet Nam Division of IT University of Social Sciences and Humanities VNU-HCMC Ho Chi Minh City Viet Nam Faculty of IT University of Science VNU-HCMC Ho Chi Minh City Viet Nam

ISBN: (纸本)9783030325909

In the traditional frequent itemsets mining on transactional databases, which items have no weight (equal weight, as equal to 1). However, in real world applications are often each item has a different weight (the importance/significance of each item). therefore, we need to mining weighted/significance itemsets on transactional databases. In this paper, we propose a high-performance algorithm called HPM-FSI for mining frequent significance itemsets based on approach NOT satisfy the downward closure property (a great challenge). the experimental results show that the proposed algorithms perform better than other existing algorithms on both real-life and synthetic datasets. © 2020, Springer Nature Switzerland AG.

关键词： Database systems

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Robotic Autism Rehabilitation by Wearable Brain-computer Interface and Augmented Reality 15

Robotic Autism Rehabilitation by Wearable Brain-Computer Int...

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15th IEEE International symposium on Medical Measurements and Applications (MeMeA)

作者： Arpaia, Pasquale Bravaccio, Carmela Corrado, Giuseppina Duraccio, Luigi Moccaldi, Nicola Rossi, Silvia Univ Naples Federico II Dep Elect Engn & Informat Technol DIETI Naples Italy Univ Naples Federico II Dept Translat Med Sci Naples Italy

ISBN: (纸本)9781728153865

An instrument based on the integration of Brain computer Interface (BCI) and Augmented Reality (AR) is proposed for robotic autism rehabilitation. Flickering stimuli at fixed frequencies appear on the display of Augmented Reality (AR) glasses. When the user focuses on one of the stimuli a Steady State Visual Evoked Potentials (SSVEP) occurs on his occipital region. A single-channel electroencephalographic Brain computer Interface detects the elicited SSVEP and sends the corresponding commands to a mobile robot. the device's high wearability (single channel and dry electrodes), and the trainingless usability are fundamental for the acceptance by Autism Spectrum Disorder (ASD) children. Effectively controlling the movements of a robot through a new channel enhances rehabilitation engagement and effectiveness. A case study at an accredited rehabilitation center on 10 healthy adult subjects highlighted an average accuracy higher than 83%. Preliminary further tests at the Department of Translational Medical Sciences of University of Naples Federico II on 3 ASD patients between 8 and 10 years old provided positive feedback on device acceptance and attentional performance.

关键词： Augmented reality

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15th International symposium on Visual computing, ISVC 2020

15th International Symposium on Visual Computing, ISVC 2020

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15th International symposium on Visual computing, ISVC 2020

ISBN: (纸本)9783030645557

the proceedings contain 118 papers. the special focus in this conference is on Visual computing. the topics include: Understanding Flooding Detection Using Overhead Imagery - Lessons Learned;natural Disaster Building Damage Assessment Using a Two-Encoder U-Net;investigating the Effects of Display Fidelity of Popular Head-Mounted Displays on Spatial Updating and Learning in Virtual Reality;passenger Anxiety About Virtual Driver Awareness During a Trip with a Virtual Autonomous Vehicle;improving User Experience in Augmented Reality Mirrors with 3D Displays;biologically Inspired Sleep Algorithm for Variational Auto-Encoders;walking in a Crowd Full of Virtual Characters: Effects of Virtual Character Appearance on Human Movement Behavior;concurrenthull: A Fast Parallel computing Approach to the Convex Hull Problem;simulation of high-Definition Pixel-Headlights;body Motion Analysis for Golf Swing Evaluation;3D Articulated Body Model Using Anthropometric Control Points and an Articulation Video;TAGCN: Topology-Aware Graph Convolutional Network for Trajectory Prediction;Asynchronous Corner Tracking Algorithm Based on Lifetime of Events for DAVIS Cameras;coarse-to-Fine Object Tracking Using Deep Features and Correlation Filters;face Reenactment Based Facial Expression Recognition;gender and Age Estimation Without Facial Information from Still Images;controlled AutoEncoders to Generate Faces from Voices;Towards an Effective Approach for Face Recognition with DCGANs Data Augmentation;Deep Partial Occlusion Facial Expression Recognition via Improved CNN;evaluating Single Image Dehazing Methods Under Realistic Sunlight Haze;BVNet: A 3D End-to-End Model Based on Point Cloud;generalized Inverted Dirichlet Optimal Predictor for Image Inpainting;FA3D: Fast and Accurate 3D Object Detection;lightless Fields: Enhancement and Denoising of Light-Deficient Light Fields.

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15th International symposium on Visual computing, ISVC 2020

15th International Symposium on Visual Computing, ISVC 2020

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15th International symposium on Visual computing, ISVC 2020

ISBN: (纸本)9783030645588

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Low-bit Quantized CNN Acceleration based on Bit-serial Dot Product Unit with Zero-bit Skip 8

Low-bit Quantized CNN Acceleration based on Bit-serial Dot P...

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8th International symposium on computing and Networking, CANDAR 2020

作者： Isobe, Sora Tomioka, Yoichi School of Computer Science and Engineering University of Aizu Fukushima Japan

ISBN: (纸本)9781728182216

A convolutional neural network (CNN) is widely used for various regression and classification problems and enables it to predict with high accuracy compared to conventional methods. On the other hand, today’s CNN inference requires a massive multiplication and accumulation (MAC) operations. To realize high-speed and low-power CNN inference, a bit-serial dot product unit (DPU)-based accelerator for CNN quantized to low-bit has been proposed. However, the performance and energy efficiency of bit-serial DPU decreases rapidly as the bit width of quantitation increases. In this paper, we propose an extended bit-serial DPU that supports a zero-bit skip function, called DPUZ. this DPUZ can reduce the number of clock cycles for inference by skipping multiplication and addition for zero-bit of weight. In the experiments, we demonstrated that the proposed DPUZ with 32 inputs achieved about 15 times higher performance compared with the original DPU for CNN of 2-bit weight and 4-bit activation. © 2020 IEEE

关键词： Field programmable gate arrays (FPGA)

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the Importance of Being X-Drop: high performance Genome Alignment on Reconfigurable Hardware

The Importance of Being X-Drop: High Performance Genome Alig...

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Annual IEEE symposium on Field-Programmable Custom computing Machines (FCCM)

作者： Alberto Zeni Guido Walter Di Donato Lorenzo Di Tucci Marco Rabozzi Marco D. Santambrogio Informazione e Bioingegneria Politecnico di Milano Milan Italy Huxelerate S.r.l.

Pairwise sequence alignment accounts for the majority of key genome analysis applications' runtime. Because of the quadratic time complexity of exact alignment algorithms, the community is moving away from exact algorithms in favor of heuristics that only compute high-quality results. However, the state of the art lacks hardware-accelerated versions of these heuristic algorithms as the vast majority of the available solutions still rely on implementing exact alignment algorithms. Moreover, hardware-based implementations lack high-level APIs that can simplify their integration in commonly used genomic pipelines, hindering their applicability in real-world scenarios. In this context, we present the first high-performance FPGA implementation of the popular X-drop heuristic alignment algorithm and provide an easy-to-use API for its integration. On a Xilinx Alveo U280, our FPGA design achieves up to 5× speed-up over SeqAn, the state-of-the-art software version of the algorithm, running on two Intel Xeon processors using 80 CPU threads. Moreover, our design is also 3.45× faster than ksw2, a state-of-the-art vectorized alignment algorithm that performs a similar heuristic to the one employed in the X-drop algorithm. Finally, our implementation also outperforms LOGAN, a recently published GPU implementation of X-drop running on an Nvidia Tesla V100, by a factor of 1.5×.

关键词： Proteins Runtime Heuristic algorithms Software algorithms Genomics Graphics processing units computer architecture

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Improving Resource Utilization by Timely Fine-Grained Scheduling 20

Improving Resource Utilization by Timely Fine-Grained Schedu...

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15th European Conference on computer Systems (EuroSys)

作者： Jin, Tatiana Cai, Zhenkun Li, Boyang Zheng, Chengguang Jiang, Guanxian Cheng, James Chinese Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781450368827

Monotask is a unit of work that uses only a single type of resource (e.g., CPU, network, disk I/O). While monotask was primarily introduced as a means to reason about job performance, in this paper we show that this fine-grained, resource-oriented abstraction can be leveraged by job schedulers to maximize cluster resource utilization. Although recent cluster schedulers have significantly improved resource allocation, the utilization of the allocated resources is often not high due to inaccurate resource requests. In particular, we show that existing scheduling mechanisms are ineffective for handling jobs with dynamic resource usage, which exists in common workloads, and propose a resource negotiation mechanism between job schedulers and executors that makes use of monotasks. We design a new framework, called Ursa, which enables the scheduler to capture accurate resource demands dynamically from the execution runtime and to provide timely, fine-grained resource allocation based on monotasks. Ursa also enables high utilization of the allocated resources by the execution runtime. We show by experiments that Ursa is able to improve cluster resource utilization, which effectively translates to improved makespan and average JCT.

关键词： Distributed computing resource utilization

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