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- research-articleJuly 2024
A joint estimation algorithm for single-input multiple-output underwater acoustic communications
Highlights- The performance of underwater acoustic communication systems can be further enhanced by employing a multi-channel receiver.
- Classical passive time-reversal techniques with decision feedback equalizers offer low complexity but exhibit ...
In single-input multiple-output (SIMO) underwater acoustic (UWA) communications, the receiver based on passive time reversal (PTR) combined with decision feedback equalizer (DFE) is widely used but has a limited performance. A multi-channel joint ...
- research-articleMay 2024
HeadSculpt: crafting 3D head avatars with text
NIPS '23: Proceedings of the 37th International Conference on Neural Information Processing SystemsDecember 2023, Article No.: 218, Pages 4915–4936Recently, text-guided 3D generative methods have made remarkable advancements in producing high-quality textures and geometry, capitalizing on the proliferation of large vision-language and image diffusion models. However, existing methods still struggle ...
- research-articleMay 2024
Fault diagnosis model for railway signalling equipment using deep learning techniques
International Journal of Sensor Networks (IJSNET), Volume 45, Issue 12024, Pages 40–53https://doi.org/10.1504/ijsnet.2024.138759A hybrid deep transfer learning-assisted fault diagnosis model (HDTL-FLM) was presented for railway signalling equipment, addressing the challenge of accurately diagnosing and predicting irregularities in this critical transportation component. The model ...
Graph Contrastive Learning with Cohesive Subgraph Awareness
WWW '24: Proceedings of the ACM on Web Conference 2024May 2024, Pages 629–640https://doi.org/10.1145/3589334.3645470Graph contrastive learning (GCL) has emerged as a state-of-the-art strategy for learning representations of diverse graphs including social and biomedical networks. GCL widely uses stochastic graph topology augmentation, such as uniform node dropping, to ...
- research-articleApril 2024
SCL-WC: cross-slide contrastive learning for weakly-supervised whole-slide image classification
- Xiyue Wang,
- Jinxi Xiang,
- Jun Zhang,
- Sen Yang,
- Zhongyi Yang,
- Minghui Wang,
- Jing Zhang,
- Wei Yang,
- Junzhou Huang,
- Xiao Han
NIPS '22: Proceedings of the 36th International Conference on Neural Information Processing SystemsNovember 2022, Article No.: 1309, Pages 18009–18021Weakly-supervised whole-slide image (WSI) classification (WSWC) is a challenging task where a large number of unlabeled patches (instances) exist within each WSI (bag) while only a slide label is given. Despite recent progress for the multiple instance ...
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- research-articleMarch 2024
LS-MVSNet: Lightweight self-supervised multi-view stereo
Computers and Graphics (CGRS), Volume 117, Issue CDec 2023, Pages 183–191https://doi.org/10.1016/j.cag.2023.11.001AbstractIn recent years, significant progress has been made in multi-view stereo through the adoption of learning-based methods. However, current state-of-the-art approaches exhibit high computational and memory costs, owing to their reliance on semantic ...
Highlights- We propose a novel self-supervised framework for high-precision scene depth estimation, optimizing computational efficiency and memory utilization.
- We propose a contour feature extraction module aimed at enhancing depth estimation ...
- erratumDecember 2023
- research-articleNovember 2023
A framework for generating anomaly analysis comments in DHI interpretation report
Computers and Electronics in Agriculture (COEA), Volume 214, Issue CNov 2023https://doi.org/10.1016/j.compag.2023.108331Highlights- Generate anomaly analysis comments from time-series data of DHI indicators.
- Improved Encoder-Decoder model is employed to generate comments.
- Three pre-processing methods are used to capture change trend of indicators.
- Attention ...
Efficient and high-quality writing of DHI interpretation reports is critical to realize the instructive value of time-series DHI data, in which anomaly analysis of DHI indicators is the basis of diagnosing problems and giving suggestions for ...
- research-articleOctober 2023
Dynamic Low-Rank Instance Adaptation for Universal Neural Image Compression
MM '23: Proceedings of the 31st ACM International Conference on MultimediaOctober 2023, Pages 632–642https://doi.org/10.1145/3581783.3612187The latest advancements in neural image compression show great potential in surpassing the rate-distortion performance of conventional standard codecs. Nevertheless, there exists an indelible domain gap between the datasets utilized for training (i.e., ...
- research-articleOctober 2023
Towards Real-Time Neural Video Codec for Cross-Platform Application Using Calibration Information
MM '23: Proceedings of the 31st ACM International Conference on MultimediaOctober 2023, Pages 7961–7970https://doi.org/10.1145/3581783.3611955The state-of-the-art neural video codecs have outperformed the most sophisticated traditional codecs in terms of rate-distortion (RD) performance in certain cases. However, utilizing them for practical applications is still challenging for two major ...
- research-articleOctober 2023
On Root Cause Localization and Anomaly Mitigation through Causal Inference
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge ManagementOctober 2023, Pages 699–708https://doi.org/10.1145/3583780.3614995Due to a wide spectrum of applications in the real world, such as security, financial surveillance, and health risk, various deep anomaly detection models have been proposed and achieved state-of-the-art performance. However, besides being effective, in ...
- research-articleSeptember 2023
SQ-SLAM: Monocular Semantic SLAM Based on Superquadric Object Representation
Journal of Intelligent and Robotic Systems (JIRS), Volume 109, Issue 2Oct 2023https://doi.org/10.1007/s10846-023-01960-wAbstractObject SLAM uses additional semantic information to detect and map objects in the scene, in order to improve the system’s perception and map representation capabilities. Previous methods often use quadrics and cuboids to represent objects, ...
- research-articleAugust 2023
Mitigating Action Hysteresis in Traffic Signal Control with Traffic Predictive Reinforcement Learning
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 673–684https://doi.org/10.1145/3580305.3599528Traffic signal control plays a pivotal role in the management of urban traffic flow. With the rapid advancement of reinforcement learning, the development of signal control methods has seen a significant boost. However, a major challenge in implementing ...
- research-articleAugust 2023
Misbehavior Detection in Wi-Fi/LTE Coexistence Over Unlicensed Bands
IEEE Transactions on Mobile Computing (ITMV), Volume 22, Issue 8Aug. 2023, Pages 4773–4791https://doi.org/10.1109/TMC.2022.3164326We address the problem of detecting misbehavior in the coexistence etiquette between LTE and Wi-Fi systems operating in the 5GHz U-NII unlicensed bands. We define selfish misbehavior strategies for the LTE that can yield an unfair share of the spectrum ...
- research-articleAugust 2023
MMDAE-HGSOC: A novel method for high-grade serous ovarian cancer molecular subtypes classification based on multi-modal deep autoencoder
Computational Biology and Chemistry (COBC), Volume 105, Issue CAug 2023https://doi.org/10.1016/j.compbiolchem.2023.107906AbstractHigh-grade serous ovarian cancer (HGSOC) is a type of ovarian cancer developed from serous tubal intraepithelial carcinoma. The intrinsic differences among molecular subtypes are closely associated with prognosis and pathological ...
Graphical AbstractDisplay Omitted
Highlights- Multi-omics data are integrated for classification.
- Superimposed LASSO is ...
- short-paperJuly 2023
Multi-Grained Topological Pre-Training of Language Models in Sponsored Search
- Zhoujin Tian,
- Chaozhuo Li,
- Zhiqiang Zuo,
- Zengxuan Wen,
- Xinyue Hu,
- Xiao Han,
- Haizhen Huang,
- Senzhang Wang,
- Weiwei Deng,
- Xing Xie,
- Qi Zhang
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2023, Pages 2189–2193https://doi.org/10.1145/3539618.3592024Relevance models measure the semantic closeness between queries and the candidate ads, widely recognized as the nucleus of sponsored search systems. Conventional relevance models solely rely on the textual data within the queries and ads, whose ...
- ArticleMay 2023
Achieving Counterfactual Fairness for Anomaly Detection
Advances in Knowledge Discovery and Data MiningMay 2023, Pages 55–66https://doi.org/10.1007/978-3-031-33374-3_5AbstractEnsuring fairness in anomaly detection models has received much attention recently as many anomaly detection applications involve human beings. However, existing fair anomaly detection approaches mainly focus on association-based fairness notions. ...
- research-articleMay 2023
On a Flexible Car Use Restriction Policy: Theory and Experiment
Transportation Science (TRNPS), Volume 57, Issue 3May-June 2023, Pages 647–660https://doi.org/10.1287/trsc.2023.1200Car use restrictions have been adopted in some mega cities that experience rapid car ownership increase and worsening traffic congestion. Although easy to implement and considered fair, most implementations of this travel demand management policy do not ...
Cross-center Early Sepsis Recognition by Medical Knowledge Guided Collaborative Learning for Data-scarce Hospitals
WWW '23: Proceedings of the ACM Web Conference 2023April 2023, Pages 3987–3993https://doi.org/10.1145/3543507.3583989There are significant regional inequities in health resources around the world. It has become one of the most focused topics to improve health services for data-scarce hospitals and promote health equity through knowledge sharing among medical ...
Vertical Federated Knowledge Transfer via Representation Distillation for Healthcare Collaboration Networks
WWW '23: Proceedings of the ACM Web Conference 2023April 2023, Pages 4188–4199https://doi.org/10.1145/3543507.3583874Collaboration between healthcare institutions can significantly lessen the imbalance in medical resources across various geographic areas. However, directly sharing diagnostic information between institutions is typically not permitted due to the ...