no code implementations • 9 Apr 2024 • YanJie Li, Weijun Li, Lina Yu, Min Wu, Jingyi Liu, Wenqiang Li, Meilan Hao, Shu Wei, Yusong Deng
However, its performance is very dependent on the training data and performs poorly on data outside the training set, which leads to poor noise robustness and Versatility of such methods.
no code implementations • 28 Feb 2024 • YanJie Li, Jingyi Liu, Weijun Li, Lina Yu, Min Wu, Wenqiang Li, Meilan Hao, Su Wei, Yusong Deng
The SR problem is solved as a pure multimodal problem, and contrastive learning is also introduced in the training process for modal alignment to facilitate later modal feature fusion.
no code implementations • 26 Jan 2024 • Songsong Tian, Lusi Li, Weijun Li, Hang Ran, Li Li, Xin Ning
In this paper, we propose a novel approach called Prompt Learning for FSCIL (PL-FSCIL), which harnesses the power of prompts in conjunction with a pre-trained Vision Transformer (ViT) model to address the challenges of FSCIL effectively.
1 code implementation • 25 Jan 2024 • Min Wu, Weijun Li, Lina Yu, Wenqiang Li, Jingyi Liu, YanJie Li, Meilan Hao
Therefore, a greedy pruning algorithm is proposed to prune the network into a subnetwork while ensuring the accuracy of data fitting.
no code implementations • 24 Jan 2024 • YanJie Li, Weijun Li, Lina Yu, Min Wu, Jingyi Liu, Wenqiang Li, Meilan Hao, Shu Wei, Yusong Deng
To optimize the trade-off between efficiency and versatility, we introduce SR-GPT, a novel algorithm for symbolic regression that integrates Monte Carlo Tree Search (MCTS) with a Generative Pre-Trained Transformer (GPT).
no code implementations • 3 Jan 2024 • YanJie Li, Weijun Li, Lina Yu, Min Wu, Jinyi Liu, Wenqiang Li, Meilan Hao
1, The type of activation function is single and relatively fixed, which leads to poor "unit representation ability" of the network, and it is often used to solve simple problems with very complex networks; 2, the network structure is not adaptive, it is easy to cause network structure redundant or insufficient.
no code implementations • 13 Nov 2023 • YanJie Li, Weijun Li, Lina Yu, Min Wu, Jinyi Liu, Wenqiang Li, Meilan Hao, Shu Wei, Yusong Deng
To address these issues, we propose MetaSymNet, a novel neural network that dynamically adjusts its structure in real-time, allowing for both expansion and contraction.
no code implementations • 24 Sep 2023 • Wenqiang Li, Weijun Li, Lina Yu, Min Wu, Jingyi Liu, YanJie Li
Instead of searching for expressions within a large search space, we explore DySymNet with various structures and optimize them to identify expressions that better-fitting the data.
no code implementations • 17 Apr 2023 • Songsong Tian, Lusi Li, Weijun Li, Hang Ran, Xin Ning, Prayag Tiwari
Overall, this paper offers a comprehensive analysis of the latest advances in FSCIL from a methodological, performance, and application perspective.
no code implementations • 25 Oct 2021 • Liping Zhang, Weijun Li, Linjun Sun, Lina Yu, Xin Ning, Xiaoli Dong, Jian Xu, Hong Qin
First, we propose an explicit model (EmFace) for human face representation in the form of a finite sum of mathematical terms, where each term is an analytic function element.
no code implementations • 8 Jan 2021 • Liang Xu, Liying Zheng, Weijun Li, Zhenbo Chen, Weishun Song, Yue Deng, Yongzhe Chang, Jing Xiao, Bo Yuan
In recent studies, Lots of work has been done to solve time series anomaly detection by applying Variational Auto-Encoders (VAEs).
no code implementations • 12 Sep 2020 • Yaohua Bu, Weijun Li, Tianyi Ma, Shengqi Chen, Jia Jia, Kun Li, Xiaobo Lu
To provide more discriminative feedback for the second language (L2) learners to better identify their mispronunciation, we propose a method for exaggerated visual-speech feedback in computer-assisted pronunciation training (CAPT).
no code implementations • 3 Aug 2020 • Liping Zhang, Weijun Li, Lina Yu, Xiaoli Dong, Linjun Sun, Xin Ning, Jian Xu, Hong Qin
The GmNet is then designed using Gaussian functions as neurons, with parameters that correspond to each of the parameters of GmFace in order to transform the problem of GmFace parameter solving into a network optimization problem of GmNet.
no code implementations • 16 Apr 2020 • Liping Zhang, Weijun Li, Xin Ning
In this work, we propose a finger vein-specific local feature descriptors based physiological characteristic of finger vein patterns, i. e., histogram of oriented physiological Gabor responses (HOPGR), for finger vein recognition.
no code implementations • 15 Apr 2020 • Xin Ning, Shaohui Xu, Xiaoli Dong, Weijun Li, Fangzhe Nan, Yuanzhou Yao
To overcome the limitations of a single network in new attribute synthesis, a continuous learning method for face attribute synthesis is proposed in this work.