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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Hou, Junlin Xiao, Fan Xu, Jilan Feng, Rui Zhang, Yuejie Zou, Haidong Lu, Lina Xue, Wenwen Fudan University School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Shanghai China Fudan University Academy for Engineering and Technology Shanghai China Shanghai Eye Diseases Prevention & Treatment Center Shanghai China

ISBN: (纸本)9781728163277

Explicit information of lesions can provide visual instructions for diabetic retinopathy (DR) grading on fundus images. However, pixel-level lesion annotations are extremely difficult and time-consuming to acquire. In this work, we propose a novel weakly-supervised lesion-aware network for DR grading, which enhances the discriminative features with lesion priors by only image-level supervision. Specifically, we design a lesion attention module that generates lesion activation maps by introducing an auxiliary task of binary DR identification. Lesion activation maps are utilized to assist the network to focus on the most relevant regions for boosting DR grading performance. Besides, we particularly devise an adaptive joint loss to balance the DR identification and DR grading tasks dynamically. Extensive results on the public DR dataset demonstrate the superiority and generality of our proposed lesion-aware network. The interpretability of generated lesion activation maps is also verified by the comparison with ground truth segmentation masks. © 2023 IEEE.

关键词： Activation map Diabetic retinopathy grading Fundus image Lesion priors Weakly-supervised

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Improving Automatic Piano Transcription by Refined Feature Fusion and Weighted Loss 9th

Improving Automatic Piano Transcription by Refined Feature ...

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9th Conference on Sound and Music technology, CSMT 2021

作者： Zhao, Jiahao Wu, Yulun Wen, Liang Ma, Lianhang Ruan, Linping Wang, Wantao Li, Wei School of Computer Science and Technology Fudan University Shanghai200438 China CETHIK Group Co. Ltd Hangzhou311199 China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai200433 China

ISBN: (纸本)9789811947025

Automatic Piano Transcription is to transcribe raw audio files into annotated piano rolls. In recent studies, jointly estimating pitch, onset, offset, and velocity of each note is commonly used. The previous state-of-the-art "Onsets and Frames" model chooses to concatenate the output of both onset and offset sub-tasks with extracted features to improve the frame-wise pitch detection, which is, however, low-efficiency in our opinion. In this paper, we proposed an improved piano transcription model by doing feature fusion and loss weighting. Our proposed model outperforms the baselines by a large margin. It also shows comparable performance with the state-of-the-art "High-Res PT" model in note metrics and outperforms it in frame metrics with an F1 score of 90.27%. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Musical instruments

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Steel Surface Defect Detection Based on Improved YOLOv8 20

Steel Surface Defect Detection Based on Improved YOLOv8

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20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2024

作者： Zhang, Jichen Zhang, Zhi College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Hubei Wuhan430065 China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Hubei Wuhan430065 China

ISBN: (纸本)9798350356328

There are some defects on the surface of steel that are difficult to detect, so we propose an improved algorithm based on YOLOv8 for detecting defects that are difficult to be detected. This improvement includes the introduction of an SPD module to minimize the problem of information loss due to downsampling;the addition of a small object detection head combined with EMA attention to further enhance the detection capabilities for small targets;the use of BiFPN to replace the original PANet, applying different weights to different features to strengthen feature fusion. Experiments were conducted on the NEU-DET dataset, and the algorithm improved mAP to 80.2%, an improvement of 3.9% over the baseline model. © 2024 IEEE.

关键词： Change detection

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Efficient fully analytical polygon-based continuous shading rendering CGH algorithm with specular reflection 14

Efficient fully analytical polygon-based continuous shading ...

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Holography, Diffractive Optics, and Applications XIV 2024

作者： Wang, Pin Fu, Qingyang Zhang, Yaping Poon, Ting-Chung Yunnan Provincial Key Laboratory of Modern Information Optics Kunming University of Science and Technology Kunming Yunnan650500 China Nanjing University of Science and Technology Nanjing Jiangsu210094 China Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States

ISBN: (纸本)9781510682085

The fully analytical method has been widely studied for its higher accuracy and efficiency, and the addition of shading rendering can effectively improve the three-dimensional perception of reconstructed images. However, existing fully analytical polygon-based shading rendering methods suffer from high computational complexity and complexity due to the need for additional calculation of the highlight spectrum. Based on previous research, we employ a continuous light and shadow algorithm that uses linear interpolation to decouple the reflection term from the spectrum, meaning that we incorporate the specular component into the calculation of vertex modulus, and separately compute the vertex modulus and the corresponding spectrum values, simplifying the calculation process of existing Blinn Phong lighting models. The algorithm can effectively generate highly realistic holographically reconstructed images with high gloss effects under continuous illumination. It achieves computational efficiency than existing algorithms, without increasing the number of polygons. Simulations and experimental results have verified the effectiveness of our proposed method. © 2024 SPIE. All rights reserved.

关键词： Rendering (computer graphics)

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EPI-Mamba: State Space Model for Semantic Segmentation from Light Fields

EPI-Mamba: State Space Model for Semantic Segmentation from ...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Yan Li Jianan Chen Qiong Wang Jinshan Xu College of Computer Science & Technology Zhejiang University of Technology Hangzhou China Guangdong Provincial Key Laboratory of Intelligent Information Processing & Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Global contextual dependency is of significance for semantic segmentation from light fields. However, previous works mostly exploit attention mechanisms to model spatial context dependency and angular context dependency separately, since a light field capture is very data-intensive. Considering that self-attention is resource-consuming, existing methods only use it to capture spatial contextual dependency for the central view of light fields, and employ resource-efficient attention mechanisms to model angular view dependencies instead. Inspired by the recent success of State Space Sequence model (SSM), we present a novel SSM-based encoder for light field semantic segmentation, which models spatio-angular contextual dependency together. The proposed method is evaluated on the existing light field semantic segmentation datasets, and experimental results show that the proposed method significantly outperforms previous state-of-the-art methods. The code and models used in this work are available in https://***/YanWQ/EPI-Mamba

关键词： Geometry Attention mechanisms Codes Semantic segmentation Semantics Signal processing Light fields Acoustics Speech processing Context modeling

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Enhanced figure of merit for famatinite Cu_(3)SbSe_(4)via band structure tuning and hierarchical architecture

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Journal of Materiomics 2023年第6期9卷 1263-1272页

作者： Lijun Zhao Haolin Ye Xinmeng Wu Jian Yang Lihua Yu Zhongqi Shi Shahid Hussain Guanjun Qiao Junhua Xu Bangzhi Ge Li Wang Chongjian Zhou School of Materials Science and Engineering Jiangsu University of Science and TechnologyZhenjiang212100JiangsuChina State Key Laboratory of Solidification Processing Key Laboratory of Radiation Detection Materials and DevicesMinistry of Industry and Information TechnologyNorthwestern Polytechnical UniversityXi'an710072ShaanxiChina School of Materials Science and Engineering Jiangsu UniversityZhenjiang212013JiangsuChina State Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong UniversityXi'an710049ShaanxiChina

The p-type Te-free Cu_(3)SbSe_(4)with famatinite structure is a potential candidate for thermoelectric materials due to the low cost and eco-friendly constituent ***,its strong bipolar effect and high lattice thermal conductivity(klat)are the main challenges for its performance ***,we report a new strategy to enhance its figure of merit zT~0.86 at 673 K for Cu_(3)Sb_(0.95)Fe_(0.05)Se_(2.8)S_(1.2)via band structure tuning and hierarchical ***,S substituted Se atoms in lattice can widen the band gap to alleviate the bipolar ***,Fe doping in Sb site significantly increases the density of states,thus increasing the carrier effective mass,and obtaining a remarkably high Seebeck coefficient of~560 mV/K at 300 ***,the induced hierarchical architecture defects resulting in a minimum klat of~0.48 W·m^(-1)·K^(-1)at 673 ***,the improved Seebeck coefficient combined with low thermal conductivity leads to an enhanced zT.

关键词： Cu3SbSe4-Based materials Defects Band gap Thermoelectric properties Solid solution

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Deep learning-based activity recognition and fine motor identification using 2D skeletons of cynomolgus monkeys

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Zoological Research 2023年第5期44卷 967-980页

作者： Chuxi Li Zifan Xiao Yerong Li Zhinan Chen Xun Ji Yiqun Liu Shufei Feng Zhen Zhang Kaiming Zhang Jianfeng Feng Trevor W.Robbins Shisheng Xiong Yongchang Chen Xiao Xiao School of Information Science and Technology Micro Nano System Center Fudan UniversityShanghai 200433China Department of Anesthesiology Huashan HospitalKey Laboratory of Computational Neuroscience and Brain-Inspired IntelligenceMinistry of EducationBehavioral and Cognitive Neuroscience CenterInstitute of Science and Technology for Brain-Inspired IntelligenceMOE Frontiers Center for Brain ScienceFudan UniversityShanghai 200433China Kuang Yaming Honors School Nanjing UniversityNanjingJiangsu 210023China Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China State Key Laboratory of Primate Biomedical Research Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingYunnan 650500China New Vision World LLC. Aliso ViejoCalifornia 92656USA Behavioural and Clinical Neuroscience Institute University of CambridgeCambridgeCB21TNUK

Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and ***,action recognition currently used in non-human primate(NHP)research relies heavily on intense manual labor and lacks standardized *** this work,we established two standard benchmark datasets of NHPs in the laboratory:Monkeyin Lab(Mi L),which includes 13 categories of actions and postures,and MiL2D,which includes sequences of two-dimensional(2D)skeleton ***,based on recent methodological advances in deep learning and skeleton visualization,we introduced the Monkey Monitor Kit(Mon Kit)toolbox for automatic action recognition,posture estimation,and identification of fine motor activity in *** the datasets and Mon Kit,we evaluated the daily behaviors of wild-type cynomolgus monkeys within their home cages and experimental environments and compared these observations with the behaviors exhibited by cynomolgus monkeys possessing mutations in the MECP2 gene as a disease model of Rett syndrome(RTT).Mon Kit was used to assess motor function,stereotyped behaviors,and depressive phenotypes,with the outcomes compared with human manual *** Kit established consistent criteria for identifying behavior in NHPs with high accuracy and efficiency,thus providing a novel and comprehensive tool for assessing phenotypic behavior in monkeys.

关键词： Action recognition Fine motor identification Two-stream deep model 2D skeleton Non-human primates Rett syndrome

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On the Impact of Spatial Mode Dispersion for Strongly-Coupled Multicore Fiber Submarine Transmission

On the Impact of Spatial Mode Dispersion for Strongly-Couple...

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2023 Optical Fiber Communications Conference and Exhibition, OFC 2023

作者： Sun, Lin Chen, Bin Liu, Gordon Ning Cai, Yi Li, Zhaohui Lu, Chao Shen, Gangxiang Soochow University Suzhou Key Laboratory of Advanced Optical Communication Network Technology School of Electronic and Information Engineering Suzhou215006 China Hefei University of Technology School of Computer Science and Information Engineering Hefei China Sun Yat-Sen University Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips School of Electronics and Information Technology Guangzhou511400 China The Hong Kong Polytechnic University Photonics Research Center Department of Electrical and Information Engineering Kowloon Hung Hom Hong Kong

Strongly-coupled multicore fibers exhibit the improved tolerance to fiber non-linearity. Their potentials in optical submarine communications are investigated with considering the coupling length and spatial mode disp... 详细信息

ISBN: (纸本)9781957171180

关键词： Submarines

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Generative Negative Sample Enhancement Based Few-Shot Named Entity Recognition 11th

Generative Negative Sample Enhancement Based Few-Shot Named ...

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11th International Joint Conference on Rough Sets, IJCRS 2025

作者： Duan, Zhen Xiao, Shenghua Chen, Jie Zhao, Shu Zhang, Yanping Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui Hefei 230601 China School of Computer Science and Technology Anhui University Hefei 230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Hefei 230601 China

ISBN: (纸本)9783031927409

Few-shot Named Entity Recognition (Few-shot NER) aims to identify and classify unseen named entity types with a limited labeled samples. In recent years, large language models have achieved remarkable results in various NLP tasks due to their excellent zero/few-shot generalization capabilities. Recent research has extensively focused on using large language models to study the named entity recognition task. Negative sample entities have been demonstrated to be effective when performing this task using in-context learning paradigm. However, the problem of low efficiency and poor quality in manually constructing negative sample entities has been exposed. To address this issue, in this paper, we propose a Few-shot NER method based on generative negative sample enhancement (GNSE). Specifically, GNSE first utilizes a large language model to pre-identify potential entity spans in the support set text paragraphs in a zero-shot manner and generate the semantics of the spans based on the paragraph context. Then, the pre-identified candidate spans are compared with the ground-truth labels to determine positive or negative sample entity spans. Finally, based on Chain-of-Thought, the span semantics, positive and negative sample entities, and ground-truth labels are inserted into the example template for the in-context learning paradigm, and the test text from the query set is concatenated to construct a complete prompt. GNSE was evaluated on three widely used datasets: CoNLL’03, WNUT’17 and GUM. Experiments show that GNSE has achieved better performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Few-shot Named Entity Recognition In-context Learning Large Language Model Prompt Engineering

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DriveEditor: A Unified 3D information-Guided Framework for Controllable Object Editing in Driving Scenes 39

DriveEditor: A Unified 3D Information-Guided Framework for C...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Liang, Yiyuan Yan, Zhiying Chen, Liqun Zhou, Jiahuan Yan, Luxin Zhong, Sheng Zou, Xu Huazhong University of Science and Technology China National Key Laboratory of Multispectral Information Intelligent Processing Technology China Wangxuan Institute of Computer Technology Peking University China

ISBN: (纸本)157735897X

Vision-centric autonomous driving systems require diverse data for robust training and evaluation, which can be augmented by manipulating object positions and appearances within existing scene captures. While recent advancements in diffusion models have shown promise in video editing, their application to object manipulation in driving scenarios remains challenging due to imprecise positional control and difficulties in preserving high-fidelity object appearances. To address these challenges in position and appearance control, we introduce DriveEditor, a diffusion-based framework for object editing in driving videos. DriveEditor offers a unified framework for comprehensive object editing operations, including repositioning, replacement, deletion, and insertion. These diverse manipulations are all achieved through a shared set of varying inputs, processed by identical position control and appearance maintenance modules. The position control module projects the given 3D bounding box while preserving depth information and hierarchically injects it into the diffusion process, enabling precise control over object position and orientation. The appearance maintenance module preserves consistent attributes with a single reference image by employing a three-tiered approach: low-level detail preservation, high-level semantic maintenance, and the integration of 3D priors from a novel view synthesis model. Extensive qualitative and quantitative evaluations on the nuScenes dataset demonstrate DriveEditor’s exceptional fidelity and controllability in generating diverse driving scene edits, as well as its remarkable ability to facilitate downstream tasks. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Altitude control

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