检索结果-内蒙古大学图书馆

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023

作者： Zhu, Zijian Zhang, Yichi Chen, Hai Dong, Yinpeng Zhao, Shu Ding, Wenbo Zhong, Jiachen Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Institute for Ai Tsinghua University BNRist Center Thbi Lab Dept. of Comp. Sci. and Tech. China School of Computer Science and Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province China Saic Motor Ai Lab Zhongguancun Laboratory China

ISBN: (纸本)9798350301298

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations;2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features;3) Camera-LiDARfusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models. © 2023 IEEE.

关键词： Autonomous driving

来源：评论

学校读者我要写书评

暂无评论

A Survey: Target Tracking Algorithm Based on Sparse Representation

A Survey: Target Tracking Algorithm Based on Sparse Represen...

引用

International Symposium on Computational Intelligence and Design, ISCID

作者： Dan Lu Linsheng Li Qingsen Yan Institute of Digital Media & Communication Taiyuan University of Science and Technology Taiyuan China Shaanxi Key Laboratory of Speech & Image Information Processing School of Computer Science Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9781479970063

In this paper, we introduce the development of object tracking. In particular, we introduce several kinds of target tracking algorithm based on sparse coding, including a robust visual tracking method by casting tracking as a sparse approximation problem in a particle filter framework, kernel sparse tracking with compressive sensing, and real-time compressive tracking. Show the concept of sparse representation and compressed sensing, analyze the meaning of the sparse representation in the target tracking, and compare the algorithm.

关键词： Target tracking Kernel Robustness Visualization image coding Pattern recognition Compressed sensing

来源：评论

学校读者我要写书评

暂无评论

Visual comfort assessment of stereoscopic images with multiple salient objects

Visual comfort assessment of stereoscopic images with multip...

引用

IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Xiaonan Zhang Jun Zhou Jianyu Chen Xiaoqiang Guo Ya Zhang Xiao Gu Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Academy of Broadcasting Science Beijing China

This paper focuses on discomfort assessment issue for S3D images with multiple salient objects, and proposes four kinds of visual features of S3D images that have potential correlations with visual discomfort, including disparity distribution features, disparity jump features, object distribution features as well as object width features. A stereoscopic image database is designed focusing on multiple salient object scenarios and prediction model is built using support vector regression based on the proposed features. Prediction performance evaluation result shows that the proper combinations of the proposed features can achieve effective visual discomfort prediction for these types of pictures, and also shows that the convergence adjustments induced by the disparity discrepancies among the salient objects do cause visual discomfort in these scenarios.

关键词： Visualization Stereo image processing Feature extraction Three-dimensional displays image databases Convergence

来源：评论

学校读者我要写书评

暂无评论

Multi-view fuzzy logic system with the cooperation between visible and hidden views

arXiv

引用

arXiv 2018年

作者： Zhang, Te Deng, Zhaohong Wu, Dongrui Wang, Shitong School of Digital Media Jiangnan University Jiangsu Key Laboratory of Digital Design and Software Technology Wuxi214122 China Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan China

Multi-view datasets are frequently encountered in learning tasks, such as web data mining and multimedia information analysis. Given a multi-view dataset, traditional learning algorithms usually decompose it into several single-view datasets, from each of which a single-view model is learned. In contrast, a multi-view learning algorithm can achieve better performance by cooperative learning on the multi-view data. However, existing multi-view approaches mainly focus on the views that are visible and ignore the hidden information behind the visible views, which usually contains some intrinsic information of the multi-view data, or vice versa. To address this problem, this paper proposes a multi-view fuzzy logic system, which utilizes both the hidden information shared by the multiple visible views and the information of each visible view. Extensive experiments were conducted to validate its effectiveness. Copyright © 2018, The Authors. All rights reserved.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Improved frame-layer bit allocation scheme for H.264/AVC rate control

引用

Journal of Shanghai Jiaotong University (Science) 2009年第2期14 E卷 143-148页

作者： Lin, Gui-Xu Zheng, Shi-Bao Zhu, Liang-Jia Institute of Image Communication and Information Processing Department of Electronic Engineering Shanghai Jiaotong University Shanghai 200240 China Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Shanghai 200240 China Department of Automatic Control National University of Defense Technology Changsha 410073 China

In this paper, we aim at improving the video quality degradation due to high motions or scene changes. An improved frame-layer bit allocation scheme for H.264/AVC rate control is proposed. First, current frame is pre-encoded in 16 × 16 modes with a fixed quantization parameter (QP). The frame coding complexity is then measured based on the resulting bits and peak signal-to-ratio (PSNR) in the pre-coding stage. Finally, a bit budget is calculated for current frame according to its coding complexity and inter-frame PSNR fluctuation, combined with the buffer status. Simulation results show that, in comparison with the H.264 adopted rate control scheme, our method is more efficient to suppress the sharp PSNR drops caused by high motions and scene changes. The visual quality variations in a sequence are also relieved. Copyright.

关键词： Budget control

来源：评论

学校读者我要写书评

暂无评论

Predicting the pathological status of mammographic microcalcifications through a radiomics approach

引用

Intelligent Medicine 2021年第3期1卷 95-103页

作者： Min Li Liyu Zhu Guangquan Zhou Jianan He Yanni Jiang Yang Chen School of Biological Science and Medical Engineering Southeast UniversityNanjingJiangsu 210096China Department of Radiology the First Affiliated Hospital of Nanjing Medical UniversityNanjingJiangsu 210029China Department of Radiology the Second Affiliated Hospital of Nantong UniversityNantongJiangsu 226001China The State Key Laboratory of Bioelectronics Southeast UniversityNanjingJiangsu 210096China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing School of Computer Science and EngineeringSoutheast UniversityNanjingJiangsu 210096China The Laboratory of Image Science and Technology Key Laboratory of Ministry of EducationSchool of Computer Science and EngineeringSoutheast UniversityNanjingJiangsu 210096China

Objective The study aimed to develop a machine learning(ML)-coupled interpretable radiomics signature to predict the pathological status of non-palpable suspicious breast microcalcifications(MCs).Methods We enrolled 463 digital mammographical view images from 260 consecutive patients detected with non-palpable MCs and BI-RADS scored at 4(training cohort,n=428;independent testing cohort,n=35)in the First Affiliated Hospital of Nanjing Medical University between September 2010 and January ***,837 textures and 9 shape features were subsequently extracted from each view and finally selected by an XGBoostembedded recursive feature elimination technique(RFE),followed by four machine learning-based classifiers to build the radiomics *** Ten radiomic features constituted a malignancy-related signature for breast MCs as logistic regression(LR)and support vector machine(SVM)yielded better positive predictive value(PPV)/sensitivity(SE),0.904(95%CI,0.865–0.949)/0.946(95%CI,0.929–0.977)and 0.891(95%CI,0.822–0.939)/0.939(95%CI,0.907–0.973)respectively,outperforming their negative predictive value(NPV)/specificity(SP)from 10-fold crossvalidation(10FCV)of the training *** optimal prognostic model was obtained by SVM with an area under the curve(AUC)of 0.906(95%CI,0.834–0.969)and accuracy(ACC)0.787(95%CI,0.680–0.855)from 10FCV against AUC 0.810(95%CI,0.760–0.960)and ACC 0.800 from the testing *** The proposed radiomics signature dependens on a set of ML-based advanced computational algorithms and is expected to identify pathologically cancerous cases from mammographically undecipherable MCs and thus offer prospective clinical diagnostic guidance.

关键词： Nonpalpable microcalcifications Radiomics Machine learning

来源：评论

学校读者我要写书评

暂无评论

Highly efficient near-infrared thermally activated delayed fluorescence organic light-emitting diodes with emission beyond 800 nm

引用

Journal of Materials Chemistry C 2023年第21期11卷 6981-6988页

作者： Liang, Jing-Xing Tang, Yukun Wang, Xiaofei Zhang, Kai Shih, Yu-Wei Chen, Chia-Hsun Chiu, Tien-Lung Li, Pei Jin Lee, Jiun-Haw Wang, Chuan-Kui Wu, Chung-Chih Fan, Jian Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices Soochow University Jiangsu Suzhou215123 China Department of Electrical Engineering Graduate Institute of Electronics Engineering and Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei10617 Taiwan Shandong Province Key Laboratory of Medical Physics and Image Processing Technology School of Physics and Electronics Shandong Normal University Jinan250014 China Department of Chemistry National Taiwan University Taipei10617 Taiwan Department of Electrical Engineering Yuan Ze University Taoyuan32003 Taiwan Graduate Institute of Photonics and Optoelectronics and Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan State Key Laboratory of Structural Chemistry Fujian Institute of Research on Structure of Matter Chinese Academy of Sciences Fujian Fuzhou35002 China

Near-infrared (NIR) emitters are employed in a wide range of applications such as bio-sensors, optical communication devices, and organic light-emitting diodes (OLEDs). The development of NIR thermally activated delayed-fluorescence (TADF) materials lags significantly behind that of platinum complexes and quantum dots. To achieve cost reduction and environmental sustainability, TADF OLEDs have attracted extensive attention in both the academic community and industry in recent years. Herein, a conjugated planar acceptor was applied in a TADF emitter (TCN-TPA) to enhance the intermolecular through-space electronic coupling and redshift the emission spectra at high doping levels. In addition, multiple sub-acceptor units were integrated into a rigid acceptor to narrow the band gap. Importantly, the overall robust configuration of the TCN-TPA molecule led to high photoluminescence quantum yield (PLQY). Consequently, TCN-TPA demonstrated a record-high external quantum efficiency (EQE) of 2.4% at 802 nm and 1.1% at 841 nm among TADF OLEDs in this spectral range. © 2023 The Royal Society of Chemistry

关键词： Energy gap

来源：评论

学校读者我要写书评

暂无评论

A Research of Heart Rate Prediction Model Based on Evolutionary Neural Network

A Research of Heart Rate Prediction Model Based on Evolution...

引用

International Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Feng Xiao Ming Yuchi Mingyue Ding Jun Jo Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Life College of Science and Technology Huazhong University of Science and Technology Wuhan China School of Information and Communication Technology Griffith University QLD Australia

Heart rate (HR) signal analysis is widely used in the medicine and medical research area. Physical activities (PA) are commonly recognized to greatly affect the changes of heart rate. A method of Evolutionary Neural Network - Neuro-evolution of Augmenting Topologies (NEAT) is used to build a PA-based HR predictor model. Through special coding, crossover and mutation operator, NEAT can implement network topology and connectivity weights evolution simultaneously. The common problem in evolutionary neural network, like competing conventions, how to protect the new innovation are effectively solved. The experimental results demonstrated the application potential of the approach.

关键词： Heart rate Biological neural networks Training Monitoring Neurons Encoding Biomedical monitoring

来源：评论

学校读者我要写书评

暂无评论

Transclaw U-Net: Claw U-Net With Transformers for Medical image Segmentation

Transclaw U-Net: Claw U-Net With Transformers for Medical Im...

引用

IEEE International Conference on Information communication and Signal processing (ICICSP)

作者： Chang Yao Menghan Hu Qingli Li Guangtao Zhai Xiao-Ping Zhang Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai China Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai China Department of Electrical Computer and Biomedical Engineering Ryerson University Toronto Canada

In medical image analysis, the long-range spatial features are often not accurately obtained by the traditional convolutional neural networks. Hence, we propose a TransClaw U-Net network structure. The transformer part is added after three convolution operations to fuse shallow features extracted by convolution operations for maximally encoding the long-range spatial features between patches. The “Claw” in TransClaw U-net means that we add the bottom upsampling part to retain the deepest feature information for detail segmentation. In addition, the modified three-channel global attention mechanism to blend the outputs of three channels (the encoding part, the bottom upsampling part and the decoding part) to effectively extract image contours. The experimental results on Synapse Multi-organ Segmentation Dataset show that TransClaw U-Net performs better than other networks. The results of ablation experiments prove the effectiveness of the three improved components of the network and influence of input image size and skip-connection numbers on network performance. The source code will be publicly available once the paper is accepted.

关键词： Measurement image segmentation image coding Convolution Fuses Source coding Transformers

来源：评论

学校读者我要写书评

暂无评论

Hybrid Data-Free Knowledge Distillation

arXiv

引用

arXiv 2024年

作者： Tang, Jialiang Chen, Shuo Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China Jiangsu Key Laboratory of Image and Video Understanding for Social Security China Center for Advanced Intelligence Project RIKEN Japan Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

Data-free knowledge distillation aims to learn a compact student network from a pre-trained large teacher network without using the original training data of the teacher network. Existing collection-based and generation-based methods train student networks by collecting massive real examples and generating synthetic examples, respectively. However, they inevitably become weak in practical scenarios due to the difficulties in gathering or emulating sufficient real-world data. To solve this problem, we propose a novel method called Hybrid Data-Free Distillation (HiDFD), which leverages only a small amount of collected data as well as generates sufficient examples for training student networks. Our HiDFD comprises two primary modules, i.e., the teacher-guided generation and student distillation. The teacher-guided generation module guides a Generative Adversarial Network (GAN) by the teacher network to produce high-quality synthetic examples from very few real-world collected examples. Specifically, we design a feature integration mechanism to prevent the GAN from overfitting and facilitate the reliable representation learning from the teacher network. Meanwhile, we drive a category frequency smoothing technique via the teacher network to balance the generative training of each category. In the student distillation module, we explore a data inflation strategy to properly utilize a blend of real and synthetic data to train the student network via a classifier-sharing-based feature alignment technique. Intensive experiments across multiple benchmarks demonstrate that our HiDFD can achieve state-of-the-art performance using 120 times less collected data than existing methods. Code is available at https://***/tangjialiang97/HiDFD. Copyright © 2024, The Authors. All rights reserved.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：