Search Results for author: Juan Ye

Found 13 papers, 5 papers with code

Quantifying the Impact of Motion on 2D Gaze Estimation in Real-World Mobile Interactions

no code implementations14 Feb 2025 Yaxiong Lei, Yuheng Wang, Fergus Buchanan, Mingyue Zhao, Yusuke Sugano, Shijing He, Mohamed Khamis, Juan Ye

Mobile gaze tracking involves inferring a user's gaze point or direction on a mobile device's screen from facial images captured by the device's front camera.

Gaze Estimation

Approximate Maximum Likelihood Inference for Acoustic Spatial Capture-Recapture with Unknown Identities, Using Monte Carlo Expectation Maximization

no code implementations6 Oct 2024 Yuheng Wang, Juan Ye, Weiye Li, David L. Borchers

Because calls from different distances take different times to arrive at detectors, the order in which calls are detected is not necessarily the same as the order in which they are made, and without knowing which detections are of the same call, we do not know how many different calls are detected.

LPUWF-LDM: Enhanced Latent Diffusion Model for Precise Late-phase UWF-FA Generation on Limited Dataset

1 code implementation1 Sep 2024 Zhaojie Fang, Xiao Yu, Guanyu Zhou, Ke Zhuang, Yifei Chen, Ruiquan Ge, Changmiao Wang, Gangyong Jia, Qing Wu, Juan Ye, Maimaiti Nuliqiman, Peifang Xu, Ahmed Elazab

Our Latent Diffusion Model for Ultra-Wide-Field Late-Phase Fluorescein Angiography (LPUWF-LDM) effectively reconstructs fine details in late-phase UWF-FA and achieves state-of-the-art results compared to other existing methods when working with limited datasets.

Class-balanced Open-set Semi-supervised Object Detection for Medical Images

no code implementations22 Aug 2024 Zhanyun Lu, Renshu Gu, Huimin Cheng, Siyu Pang, Mingyu Xu, Peifang Xu, Yaqi Wang, Yuichiro Kinoshita, Juan Ye, Gangyong Jia, Qing Wu

In this paper, we consider the open-set semi-supervised object detection problem which leverages unlabeled data that contain OOD classes to improve object detection for medical images.

Object object-detection +3

TTMFN: Two-stream Transformer-based Multimodal Fusion Network for Survival Prediction

no code implementations13 Nov 2023 Ruiquan Ge, Xiangyang Hu, Rungen Huang, Gangyong Jia, Yaqi Wang, Renshu Gu, Changmiao Wang, Elazab Ahmed, Linyan Wang, Juan Ye, Ye Li

In TTMFN, we present a two-stream multimodal co-attention transformer module to take full advantage of the complex relationships between different modalities and the potential connections within the modalities.

Prediction Survival Prediction

Hadamard Domain Training with Integers for Class Incremental Quantized Learning

no code implementations5 Oct 2023 Martin Schiemer, Clemens JS Schaefer, Jayden Parker Vap, Mark James Horeni, Yu Emma Wang, Juan Ye, Siddharth Joshi

In this paper, we propose a technique that leverages inexpensive Hadamard transforms to enable low-precision training with only integer matrix multiplications.

class-incremental learning Class Incremental Learning +3

Towards Automated Animal Density Estimation with Acoustic Spatial Capture-Recapture

no code implementations24 Aug 2023 Yuheng Wang, Juan Ye, David L. Borchers

They can process large volumes of data quickly, but they do not detect all vocalisations and they do generate some false positives (vocalisations that are not from the target species).

Density Estimation Survey

An End-to-End Review of Gaze Estimation and its Interactive Applications on Handheld Mobile Devices

no code implementations30 Jun 2023 Yaxiong Lei, Shijing He, Mohamed Khamis, Juan Ye

In recent years we have witnessed an increasing number of interactive systems on handheld mobile devices which utilise gaze as a single or complementary interaction modality.

Deep Learning Gaze Estimation

A simple normalization technique using window statistics to improve the out-of-distribution generalization on medical images

1 code implementation7 Jul 2022 Chengfeng Zhou, Songchang Chen, Chenming Xu, Jun Wang, Feng Liu, Chun Zhang, Juan Ye, Hefeng Huang, Dahong Qian

In this study, we present a novel normalization technique called window normalization (WIN) to improve the model generalization on heterogeneous medical images, which is a simple yet effective alternative to existing normalization methods.

Breast Cancer Detection Out-of-Distribution Generalization

Self-Adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images

no code implementations7 May 2021 Yiming Bao, Jun Wang, Tong Li, Linyan Wang, Jianwei Xu, Juan Ye, Dahong Qian

Specifically, the encoder of a DL model that is pre-trained on the source domain is used to initialize the encoder of a reconstruction model.

Domain Adaptation Transfer Learning

Continual Learning in Human Activity Recognition: an Empirical Analysis of Regularization

1 code implementation6 Jul 2020 Saurav Jha, Martin Schiemer, Juan Ye

Given the growing trend of continual learning techniques for deep neural networks focusing on the domain of computer vision, there is a need to identify which of these generalizes well to other tasks such as human activity recognition (HAR).

Continual Learning Human Activity Recognition +1

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