no code implementations • 27 Apr 2024 • Yuntao Shou, Tao Meng, FuChen Zhang, Nan Yin, Keqin Li
Specifically, on the one hand, in the feature disentanglement stage, we propose a Broad Mamba, which does not rely on a self-attention mechanism for sequence modeling, but uses state space models to compress emotional representation, and utilizes broad learning systems to explore the potential data distribution in broad space.
no code implementations • 27 Apr 2024 • Tao Meng, FuChen Zhang, Yuntao Shou, Wei Ai, Nan Yin, Keqin Li
Since consistency and complementarity information correspond to low-frequency and high-frequency information, respectively, this paper revisits the problem of multimodal emotion recognition in conversation from the perspective of the graph spectrum.
no code implementations • 22 Apr 2024 • Armando Zhu, Keqin Li, Tong Wu, Peng Zhao, Bo Hong
With wearing masks becoming a new cultural norm, facial expression recognition (FER) while taking masks into account has become a significant challenge.
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • 21 Apr 2024 • Keqin Li, Armando Zhu, Peng Zhao, Jintong Song, Jiabei Liu
This study explores the application of deep learning technologies in software development processes, particularly in automating code reviews, error prediction, and test generation to enhance code quality and development efficiency.
no code implementations • 17 Apr 2024 • Jin Wang, Jinfei Wang, Shuying Dai, Jiqiang Yu, Keqin Li
The model can detect and understand a wide range of emotions and specific pain signals in real time, enabling the system to provide empathetic interaction.
no code implementations • 16 Apr 2024 • Keqin Li, Peng Xirui, Jintong Song, Bo Hong, Jin Wang
With the rapid advancement of technology, Augmented Reality (AR) technology, known for its ability to deeply integrate virtual information with the real world, is gradually transforming traditional work modes and teaching methods.
no code implementations • 9 Apr 2024 • Jianhua Jiang, Ziying Zhao, Weihua Li, Keqin Li
To tackle these problems, an enhanced Grey Wolf Optimizer with Elite Inheritance Mechanism and Balance Search Mechanism, named as EBGWO, is proposed to improve the effectiveness of the position updating and the quality of the convergence solutions.
1 code implementation • 1 Mar 2024 • Zeju Cai, Jianguo Chen, Yuting Fan, Zibin Zheng, Keqin Li
We explore why blockchain is applicable to FL, how it can be implemented, and the challenges and existing solutions for its integration.
no code implementations • 19 Jan 2024 • Wei Ai, CanHao Xie, Tao Meng, Yinghao Wu, Keqin Li
Community search is a derivative of community detection that enables online and personalized discovery of communities and has found extensive applications in massive real-world networks.
no code implementations • 19 Jan 2024 • JiaYi Du, Yinghao Wu, Wei Ai, Tao Meng, CanHao Xie, Keqin Li
Community Search (CS) aims to identify densely interconnected subgraphs corresponding to query vertices within a graph.
no code implementations • 3 Jan 2024 • Wei Ai, FuChen Zhang, Tao Meng, Yuntao Shou, HongEn Shao, Keqin Li
To address the above issues, we propose a two-stage emotion recognition model based on graph contrastive learning (TS-GCL).
no code implementations • 28 Dec 2023 • Yuntao Shou, Tao Meng, Wei Ai, Keqin Li
However, the existing feature fusion methods have usually mapped the features of different modalities into the same feature space for information fusion, which can not eliminate the heterogeneity between different modalities.
no code implementations • 17 Dec 2023 • Wei Ai, Yuntao Shou, Tao Meng, Keqin Li
Specifically, we construct a weighted multi-relationship graph to simultaneously capture the dependencies between speakers and event relations in a dialogue.
no code implementations • 11 Dec 2023 • Tao Meng, Yuntao Shou, Wei Ai, Nan Yin, Keqin Li
The main task of Multimodal Emotion Recognition in Conversations (MERC) is to identify the emotions in modalities, e. g., text, audio, image and video, which is a significant development direction for realizing machine intelligence.
no code implementations • 10 Dec 2023 • Yuntao Shou, Tao Meng, Wei Ai, Nan Yin, Keqin Li
Unlike the traditional single-utterance multi-modal emotion recognition or single-modal conversation emotion recognition, MCER is a more challenging problem that needs to deal with more complex emotional interaction relationships.
no code implementations • 4 Dec 2023 • Yuntao Shou, Wei Ai, Tao Meng, Keqin Li
Zero-shot age estimation aims to learn feature information about age from input images and make inferences about a given person's image or video frame without specific sample data.
1 code implementation • 5 Jul 2022 • Liang Li, Siwei Wang, Xinwang Liu, En Zhu, Li Shen, Kenli Li, Keqin Li
Multiple kernel clustering (MKC) is committed to achieving optimal information fusion from a set of base kernels.
no code implementations • 26 Feb 2021 • Cheng Xie, Ting Zeng, Hongxin Xiang, Keqin Li, Yun Yang, Qing Liu
The approach also applies a semi-supervised learning process to re-train knowledge-to-visual model.
no code implementations • 19 Jan 2021 • Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng
The BSDP system contains four modules: bicycle drop-off location clustering, bicycle-station graph modeling, bicycle-station location prediction, and bicycle-station layout recommendation.
no code implementations • 19 Jan 2021 • Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng
We model the DL-PBS system from the perspective of CPS and use deep learning to predict the layout of bicycle parking spots and the dynamic demand of bicycle dispatching.
no code implementations • 17 Nov 2020 • Tiansheng Huang, Weiwei Lin, Li Shen, Keqin Li, Albert Y. Zomaya
Federated Learning (FL), arising as a privacy-preserving machine learning paradigm, has received notable attention from the public.
no code implementations • 3 Nov 2020 • Tiansheng Huang, Weiwei Lin, Wentai Wu, Ligang He, Keqin Li, Albert Y. Zomaya
The client selection policy is critical to an FL process in terms of training efficiency, the final model's quality as well as fairness.
no code implementations • 4 Jul 2020 • Jianguo Chen, Kenli Li, Zhaolei Zhang, Keqin Li, Philip S. Yu
The COVID-19 pandemic caused by the SARS-CoV-2 virus has spread rapidly worldwide, leading to a global outbreak.
no code implementations • 12 Apr 2019 • Jianguo Chen, Kenli Li, Qingying Deng, Keqin Li, Philip S. Yu
We implement the proposed DIVS system and address the problems of parallel training, model synchronization, and workload balancing.
no code implementations • 21 Feb 2019 • Chengjie Li, Ruixuan Li, Haozhao Wang, Yuhua Li, Pan Zhou, Song Guo, Keqin Li
Distributed asynchronous offline training has received widespread attention in recent years because of its high performance on large-scale data and complex models.
1 code implementation • 30 Dec 2018 • Pavlo Melnyk, Zhiqiang You, Keqin Li
Recent researches introduced fast, compact and efficient convolutional neural networks (CNNs) for offline handwritten Chinese character recognition (HCCR).
no code implementations • 17 Oct 2018 • Jianguo Chen, Kenli Li, Huigui Rong, Kashif Bilal, Keqin Li, Philip S. Yu
In this paper, a Periodicity-based Parallel Time Series Prediction (PPTSP) algorithm for large-scale time-series data is proposed and implemented in the Apache Spark cloud computing environment.
no code implementations • 17 Oct 2018 • Jianguo Chen, Kenli Li, Huigui Rong, Kashif Bilal, Nan Yang, Keqin Li
It is crucial to provide compatible treatment schemes for a disease according to various symptoms at different stages.
no code implementations • 17 Oct 2018 • Jianguo Chen, Kenli Li, Kashif Bilal, Xu Zhou, Keqin Li, Philip S. Yu
In this paper, we focus on the time-consuming training process of large-scale CNNs and propose a Bi-layered Parallel Training (BPT-CNN) architecture in distributed computing environments.
no code implementations • 30 Nov 2017 • Chenxing Xia, Hanling Zhang, Keqin Li
Different from prior methods, we calculate the saliency value of each node based on the relationship between the corresponding node and the virtual node.