Search Results for author: Yan Gong

Found 10 papers, 5 papers with code

SkipcrossNets: Adaptive Skip-cross Fusion for Road Detection

no code implementations24 Aug 2023 Xinyu Zhang, Yan Gong, Zhiwei Li, Xin Gao, Dafeng Jin, Jun Li, Huaping Liu

Multi-modal fusion is increasingly being used for autonomous driving tasks, as images from different modalities provide unique information for feature extraction.

Autonomous Driving

Towards Better Instruction Following Language Models for Chinese: Investigating the Impact of Training Data and Evaluation

1 code implementation16 Apr 2023 Yunjie Ji, Yan Gong, Yong Deng, Yiping Peng, Qiang Niu, Baochang Ma, Xiangang Li

Recently, significant public efforts have been directed towards developing low-cost models with capabilities akin to ChatGPT, thereby fostering the growth of open-source conversational models.

Instruction Following

Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases

1 code implementation26 Mar 2023 Yunjie Ji, Yong Deng, Yan Gong, Yiping Peng, Qiang Niu, Lei Zhang, Baochang Ma, Xiangang Li

However current research rarely studies the impact of different amounts of instruction data on model performance, especially in the real-world use cases.

Exploring ChatGPT's Ability to Rank Content: A Preliminary Study on Consistency with Human Preferences

1 code implementation14 Mar 2023 Yunjie Ji, Yan Gong, Yiping Peng, Chao Ni, Peiyan Sun, Dongyu Pan, Baochang Ma, Xiangang Li

The results on the test set show that ChatGPT's ranking preferences are consistent with human to a certain extent.

Code Completion

VITR: Augmenting Vision Transformers with Relation-Focused Learning for Cross-Modal Information Retrieval

no code implementations13 Feb 2023 Yan Gong, Georgina Cosma, Axel Finke

This paper introduces VITR, a novel network that enhances ViT by extracting and reasoning about image region relations based on a local encoder.

Cross-Modal Retrieval Image Retrieval +2

Multi-modal Fusion Technology based on Vehicle Information: A Survey

no code implementations11 Nov 2022 Yan Gong, Jianli Lu, Jiayi Wu, Wenzhuo LIU

Multi-modal fusion is a basic task of autonomous driving system perception, which has attracted many scholars' interest in recent years.

Autonomous Driving

Improving Visual-Semantic Embeddings by Learning Semantically-Enhanced Hard Negatives for Cross-modal Information Retrieval

1 code implementation10 Oct 2022 Yan Gong, Georgina Cosma

Visual Semantic Embedding (VSE) aims to extract the semantics of images and their descriptions, and embed them into the same latent space for cross-modal information retrieval.

Cross-Modal Information Retrieval Information Retrieval +1

A CNN Segmentation-Based Approach to Object Detection and Tracking in Ultrasound Scans with Application to the Vagus Nerve Detection

1 code implementation25 Jun 2021 Abdullah F. Al-Battal, Yan Gong, Lu Xu, Timothy Morton, Chen Du, Yifeng Bu 1, Imanuel R Lerman, Radhika Madhavan, Truong Q. Nguyen

Real-time accurate and robust automatic detection and tracking of anatomical structures while scanning would significantly impact diagnostic and therapeutic procedures to be consistent and efficient.

object-detection Real-Time Object Detection

Spectroscopic and Photometric Redshift Estimation by Neural Networks For the China Space Station Optical Survey (CSS-OS)

no code implementations7 Jan 2021 Xingchen Zhou, Yan Gong, Xian-Min Meng, Xin Zhang, Ye Cao, Xuelei Chen, Valeria Amaro, Zuhui Fan, Liping Fu

This indicates that the neural network method is feasible and powerful for spec-z and photo-z estimations in future cosmological surveys.

Photometric Redshift Estimation Cosmology and Nongalactic Astrophysics

Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods

no code implementations1 Oct 2019 Xi Yang, Yan Gong, Nida Waheed, Keith March, Jiang Bian, William R. Hogan, Yonghui Wu

Early detection of cancer patients at risk for cardiotoxicity before cardiotoxic treatments and providing preventive measures are potential solutions to improve cancer patients's quality of life.

BIG-bench Machine Learning Specificity

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