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An Object Detection Framework for Span Extraction in Question Answering

An Object Detection Framework for Span Extraction in Questio...

引用

IEEE International conference on Network Infrastructure and Digital Content (IC-NIDC)

作者： Tianyu Zhou Ping Gong School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665405836

Machine Reading Comprehension(MRC), including a series of tasks that test the ability of models to understand natural language, has received quite a few attention in Natural Language Processing(NLP). Most existing works deal with MRC tasks by exploiting the expression capability of neural networks. Some of them have achieved impressive performance. Despite the rapid iteration of the models used, few work have focused on output layer and prediction method of answer span - also known as span extraction. In this paper, we focus on span extraction in the Question Answering(QA) task. A cross-sectional comparison of widely used span extraction methods is presented, with their strengths and weaknesses noted in detail. Furthermore, inspired by Faster R-CNN, we propose a brand new span extraction method. Experiment results show that our proposed method outperforms existing span extraction methods on both English and chinese MRC tasks.

关键词： computer vision Neural networks Object detection Predictive models Knowledge discovery Transformers Natural language processing

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Multi-feature Deep Learning for Face Gender recognition

Multi-feature Deep Learning for Face Gender Recognition

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2014 IEEE 7th Joint International Information Technology and Artificial Intelligence conference

作者： Yuxin Jiang Songbin Li Peng Liu Qiongxing Dai Haikou Laboratory Institute of Acoustics Chinese Academy of Sciences

Face gender recognition is a challenging problem in the traditional field of pattern recognition. In this paper, we propose a deep learning model that can learn the joint high-level and low-level features of human face to address this problem. Our deep neural networks apply convolution and subsampling in extracting the local and abstract features of human face, and reconstruct the raw input images to learn global and effective features as supplementary information at the same time. We also add a trainable weight in the networks when combining the two kinds of features to realize the final gender classification. Experiment results show that our method achieves the highest accuracy compared with existing methods, when test on the mixed face dataset. Further, in the generalization test, the average classification rate on 3 public datasets of our method is 5% higher than the joint Local Binary pattern(LBP) and Support Vector Machine(SVM) method, and is nearly 1% higher than the SVM with face pixels method. this proves our method outperforms the traditional methods in both learning ability and generalization ability.

关键词： face gender recognition deep learning multi-feature learning generalization ability

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Descriptive local feature groups for image classification

Descriptive local feature groups for image classification

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IEEE International conference on Image Processing

作者： Lei Yu Jing Liu Changsheng Xu Institute of Automation Chinese Academy of Sciences Beijing China

In the conventional bag of visual words (BoW) based image representation, single visual word is not discriminative enough and the spatial contextual information among local image features is ignored. In this paper, descriptive local feature groups are proposed to address these two problems. First, local image features are refined by slightly transforming the original image. then they are clustered and represented by visual words. Second, the candidate local feature groups are generated by searching the neighbors of every local image features. this kind of grouping shows more discriminative power than a single feature and the local spatial contexts can be catched. third, we obtain the groups more descriptive to the object category by defining a significance score and the groups with high score are selected. Finally, the high order descriptive local feature groups are integrated to the vector based object categorization framework by a feature reweighting strategy. Experimental results on Scene-15 and Caltech 101 demonstrate the superior performance of our method.

关键词： Visualization conferences Feature extraction Vocabulary computer vision pattern recognition Entropy

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the man-machine fitness design research of modern class sorting system

The man-machine fitness design research of modern class sort...

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the 7th International conference on computer-Aided Industrial Design and Conceptual Design (CAID&CD’2006)

作者： Qin Yang Weixing Wang 550003 GuiZhou University

Fitness design fundamental research in the thing class sorting system, is one kind of person’s factor consideration standardized method for the purpose of proposing. this article as an example of Pu Tian Sorting System from the man-machine work criterion fitness, the man-machine work rhythm fitness, the man-machine working pattern fitness, the man-machine work mood fitness four aspects carried on the analysis. By it, we took the basis reasonable man-machine function assignment and the thing flowed equipment development design, to obtain the highest comprehensive potency of system.

关键词： Man-machine Product design Sorting machine Fitness

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Fast Convolution Operations on Many-Core Architectures

Fast Convolution Operations on Many-Core Architectures

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Shigang Li Yunquan Zhang Chunyang Xiang Lei Shi State Key Laboratory of Computer Architecture Chinese Academy of Sciences Beijing China School of Information Engineering Zhengzhou University Zhengzhou China

ISBN: (纸本)9781479989386

Convolution operations have been widely used in many important application domains, such as deep learning and computer vision, in which convolution is always the most time-consuming part. High computational throughput and memory bandwidth make many-core architectures the promising targets to accelerate these applications. In this paper, we implement and optimize different convolution operations, including 1D convolution, 2D convolution and multi-channel 2D convolution executed in mini-batch mode, on both GPU and Intel MIC many-core architectures. We find out that the performance bottleneck of 1D and 2D convolutions is on registers rather than local memory or L1/L2 cache, and therefore, register tiling is used to improve the performance. In addition, we present a novel solution for multi-channel 2D convolution, in which convolution is conducted on images directly instead of being translated to matrix multiplication, and the data reuse of the algorithm is fully exploited. We further summarize the parameters of autotuning for multichannel 2D convolution and prune the search space based on heuristics. the experimental results show that, for the large filter size, our solution gets up to 33% performance improvement over cuDNN-v2 and up to 28% over clBLASbased implementation, on GTX TITAN and AMD W8000 respectively. On Intel MIC, our solution gets up to 25% of the theoretical peak performance.

关键词： Convolution Instruction sets Registers computer architecture Microwave integrated circuits Filtering algorithms Neural networks

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Estimation of Pig Weight by Machine vision:A Review

Estimation of Pig Weight by Machine Vision:A Review

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7th IFIP WG 5.14 International conference,CCTA2013

作者： Zhuo Li Cheng Luo Guanghui Teng Tonghai Liu College of Water Conservancy and Civil Engineering China Agricultural University Department of Computer Science and Information Engineering Tianjin Agricultural University

In pig production,food conversion ratio and profit can be evaluated by real time detection of pig live *** pig weight detections usually require direct contact with pigs,which are limited by its low efficiency and result in a lot of stresses even to *** non-contact detection of pig body weight has become a challenge in pig production for *** image analysis and machine vision method enable the real time estimation of pig live weight by detecting pig critical body dimensions without any *** article elucidated the advantages and limitations of each detection method of pig body weight by comparing the system framework and estimation *** research trends of contactless pig weight estimation were analyzed as well.

关键词： Pig weight machine vision estimation reviews

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A Novel LCD based Photometric Stereo Method

A Novel LCD based Photometric Stereo Method

引用

2014 4th IEEE International conference on Information Science and Technology

作者： Lina Bi Zhan Song Linmin Xie Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences The Chinese University of Hong Kong School of Automation Huazhong University of Science&Technology

this paper presents a novel LCD screen based photometric stereo method. the method is implemented with only a normal laptop. the screen of the computer is used as the light source and portioned into some different regions to simulate various lighting conditions. And the embedded camera is used for the image capture. With a deduction and proof, we show that a circular partition scheme can obtain optimal lighting effects. By the proposed lighting direction calibration means, a traditional photometric stereo algorithm is utilized for the 3D reconstruction. the experiments are conducted with a real object and compared with conventional means to demonstrate its feasibility and reconstruction accuracy.

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A Unified Probabilistic Graphical Model based Approach for the Robust Decoding of Color Structured Light pattern

A Unified Probabilistic Graphical Model based Approach for t...

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2014 4th IEEE International conference on Information Science and Technology

作者： Chao Yang Fang Liu Zhan Song Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences The Chinese University of Hong Kong Department of Aviation Ammunition China Air Force Logistics College

Color coding is an important research topic in spatial encoded structured light sensing(SLS). In this study, we propose a novel graphical model based approach for the color pattern decoding task. For efficient color labeling, the color pattern is firstly decomposed into separate binary pattern images. With the labeled pattern elements, a unified probabilistic graphical framework is constructed to represent the pseudorandom pattern as a clique tree structure. the model contains two parts: the Conditional Random Field(CRF) is used to represent the dependences between these local decisions, and the Bayesian network(BN) is applied for the representation of background colors effect. A colorful target is experimented to demonstrate its feasibility. And the 3D reconstructed models based on the decoding results are also provided to show its robustness.

关键词： image SLS CRF A Unified Probabilistic Graphical Model based Approach for the Robust Decoding of Color Structured Light pattern Model

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On Extended Graph-Based Rewiring Technique

On Extended Graph-Based Rewiring Technique

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International conference on ASIC

作者： F. S. Chim Y L. Wu Department of Computer Science and Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

the digital logic rewiring technique has been shown to be one of the most powerful logic transformation methods being able to further improve some already excellent results on many EDA problems, starting from logic minimization, partitioning, FPGA technology mappings and final routings. Previous studies show that GBAW, a graph-based rewiring engine, is able to outperform ATPG-based rewiring tools with 50-time faster runtime while being able to cover nearly half target wires in the circuit. this paper presents several new improving extensions on GBAW, including coverage of arbitrary gate sizes, to improve its rewiring power. Experimental results based on MCNC benchmark circuits show that, compared to previous GBAW, this new version is able to cover 12% more target wires and provide 1.5 times more alternative wires while runs over 100 times faster than its ATPG-based counterpart. For some problems only requiring a good-enough and very quick solution, this new rewiring technique may serve as a useful alternative.

关键词： Wires Electronic design automation and methodology Engines Field programmable gate arrays Humans Transistors Logic circuits Circuit faults Automatic test pattern generation Circuit testing

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FreeStyler: A Free-Form Stylization Method via Multimodal Vector Quantization 12th

FreeStyler: A Free-Form Stylization Method via Multimodal V...

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12th International conference on Computational Visual Media, CVM 2024

作者： Liu, WuQin Lin, MinXuan Huang, HaiBin Ma, ChongYang Dong, WeiMing School of Artificial Intelligence University of Chinese Academy of Sciences Beijing101408 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China Kuaishou Technology Beijing100085 China

ISBN: (纸本)9789819720910

Image stylization refers to the process of transforming an input image into a new one, while retaining its original content but in different styles. However, most existing works only support single-modal guidance, which is not ideal for real-world applications. To tackle this limitation, we propose FreeStyler, a flexible framework for image stylization that is capable of handling various input scenarios. Our approach goes beyond the traditional approach of relying on content and style images to generate a stylized image and supports situations where these references are absent. Specifically, in such cases, FreeStyler allows performing the stylization through text or audio information. the core of FreeStyler is a vector quantized style transfer framework that encodes content and style information into a shared discrete latent feature space, followed by a stylization transformer for style fusion and an image decoder for stylized image reconstruction. To enable free-form stylization, we introduce a novel pseudo-paired token predictor that can estimate tokens from varying input forms without the need for additional text or audio data. Specifically, we leverage Contrastive Language-Image Pre-training (CLIP) as prior knowledge to align discrete representations across different modalities and train the framework using an image and pseudo caption pair provided by Bootstrapping Language-Image Pre-training (BLIP). through qualitative and quantitative experiments, our method has demonstrated superior performance compared to state-of-the-art stylization methods. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Vector quantization

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