Search Results for author: Xuesong Yin

Found 11 papers, 3 papers with code

Exploring the Correlation Between Ultrasound Speed and the State of Health of LiFePO$_4$ Prismatic Cells

no code implementations13 Sep 2023 Shengyuan Zhang, Peng Zuo, Xuesong Yin, Zheng Fan

We propose that the reduction of binder stiffness can be a primary cause of the change in ultrasonic speed during battery ageing.

POSTER++: A simpler and stronger facial expression recognition network

1 code implementation28 Jan 2023 Jiawei Mao, Rui Xu, Xuesong Yin, Yuanqi Chang, Binling Nie, Aibin Huang

POSTER achieves the state-of-the-art (SOTA) performance in FER by effectively combining facial landmark and image features through two-stream pyramid cross-fusion design.

Facial Expression Recognition Facial Expression Recognition (FER)

More comprehensive facial inversion for more effective expression recognition

1 code implementation24 Nov 2022 Jiawei Mao, Guangyi Zhao, Yuanqi Chang, Xuesong Yin, Xiaogang Peng, Rui Xu

We extensively evaluate ASIT on facial datasets such as FFHQ and CelebA-HQ, showing that our approach achieves state-of-the-art facial inversion performance.

Facial Expression Recognition Facial Expression Recognition (FER) +1

Token Transformer: Can class token help window-based transformer build better long-range interactions?

no code implementations11 Nov 2022 Jiawei Mao, Yuanqi Chang, Xuesong Yin

The core mechanism of TT is the addition of a Class (CLS) token for summarizing window information in each local window.

Image Classification Long-range modeling

Self-Supervised Deep Subspace Clustering with Entropy-norm

no code implementations10 Jun 2022 Guangyi Zhao, Simin Kou, Xuesong Yin

The local structure and dense connectivity of the original data benefit from the self-expressive layer and additional entropy-norm constraint.

Clustering Motion Segmentation

Improvements to Self-Supervised Representation Learning for Masked Image Modeling

no code implementations21 May 2022 Jiawei Mao, Xuesong Yin, Yuanqi Chang, Honggu Zhou

The MIM paradigm enables the model to learn the main object features of the image by masking the input image and predicting the masked part by the unmasked part.

Decoder Representation Learning

Weakly-supervised Generative Adversarial Networks for medical image classification

no code implementations29 Nov 2021 Jiawei Mao, Xuesong Yin, Yuanqi Chang, Qi Huang

First, we combine with MixMatch to generate pseudo labels for the fake images and unlabeled images to do the classification.

Contrastive Learning Image Classification +2

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