Yonghong Tian

Cooperative Bi-path Metric for Few-shot Learning

2020 · arXiv (Cornell University)

Given base classes with sufficient labeled samples, the target of few-shot classification is to recognize unlabeled samples of novel classes with only a few labeled samples. Most existing methods only pay attention to the relationship …

A Mongolian-Chinese neural machine translation model based on Transformer’s two-branch gating structure

2022

To design a new two-branch gating structure for the existence of Transformer structure, by dividing the attention mechanism into two pieces, one part adopts the attention mechanism for global information capture and the other part …

Event Stream based Human Action Recognition: A High-Definition Benchmark Dataset and Algorithms

2024 · arXiv (Cornell University)

Human Action Recognition (HAR) stands as a pivotal research domain in both computer vision and artificial intelligence, with RGB cameras dominating as the preferred tool for investigation and innovation in this field. However, in real-world …

Multi-Timescale Motion-Decoupled Spiking Transformer for Audio-Visual Zero-Shot Learning

2025 · IEEE Transactions on Circuits and Systems for Video Technology

Audio-visual zero-shot learning (ZSL) has been extensively researched for its capability to classify video data from unseen classes during training. Nevertheless, current methodologies often struggle with background scene biases and inadequate motion detail. This paper …

College Library Personalized Recommendation System Based on Hybrid Recommendation Algorithm

2019 · Procedia CIRP

When the number of books provided by library is relatively large, it becomes difficult for user to select appropriate book from a lot of candidate books. In this case, this paper designs a personalized recommendation …

PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation

2021 · arXiv (Cornell University)

Large-scale Pretrained Language Models (PLMs) have become the new paradigm for Natural Language Processing (NLP). PLMs with hundreds of billions parameters such as GPT-3 have demonstrated strong performances on natural language understanding and generation with …