Ts. Dr. Sicily Ting Fung Fung

About Ts. Dr. Sicily Ting Fung Fung

Ts. Dr. Sicily Ting Fung Fung, With an exceptional h-index of 6 and a recent h-index of 5 (since 2020), a distinguished researcher at Monash University, specializes in the field of Deep Learning, Expert system, Image Processing, Biomedical Engineering, Medical imaging.

His recent articles reflect a diverse array of research interests and contributions to the field:

ASF-YOLO: A novel YOLO model with attentional scale sequence fusion for cell instance segmentation

A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities

CAFCT: Contextual and Attentional Feature Fusions of Convolutional Neural Networks and Transformer for Liver Tumor Segmentation

RCS-YOLO: A fast and high-accuracy object detector for brain tumor detection

Bgf-yolo: Enhanced yolov8 with multiscale attentional feature fusion for brain tumor detection

Toward more accurate diagnosis of multiple sclerosis:Automated lesion segmentation in brain magneticresonance image using modified U-Net model

CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer

Implementing a Successful Collaborative Active Learning Approach in Information Technology Discipline

Ts. Dr. Sicily Ting Fung Fung Information

University

Position

Lecturer

Citations(all)

574

Citations(since 2020)

556

Cited By

170

hIndex(all)

6

hIndex(since 2020)

5

i10Index(all)

3

i10Index(since 2020)

3

Email

University Profile Page

Google Scholar

Ts. Dr. Sicily Ting Fung Fung Skills & Research Interests

Deep Learning

Expert system

Image Processing

Biomedical Engineering

Medical imaging

Top articles of Ts. Dr. Sicily Ting Fung Fung

ASF-YOLO: A novel YOLO model with attentional scale sequence fusion for cell instance segmentation

arXiv preprint arXiv:2312.06458

2023/12/11

A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities

arXiv preprint arXiv:2404.14019

2024/4/22

CAFCT: Contextual and Attentional Feature Fusions of Convolutional Neural Networks and Transformer for Liver Tumor Segmentation

arXiv preprint arXiv:2401.16886

2024/1/30

RCS-YOLO: A fast and high-accuracy object detector for brain tumor detection

2023/10/1

Bgf-yolo: Enhanced yolov8 with multiscale attentional feature fusion for brain tumor detection

arXiv preprint arXiv:2309.12585

2023/9/22

Toward more accurate diagnosis of multiple sclerosis:Automated lesion segmentation in brain magneticresonance image using modified U-Net model

International Journal of Imaging Systems and Technology

2024/1

CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer

arXiv preprint arXiv:2306.14590

2023/6/26

Implementing a Successful Collaborative Active Learning Approach in Information Technology Discipline

2022/12/10

Adaptive Tuning Noise Estimation for Medical Images using Maximum Element Convolution Laplacian

Int. Journal of Innovative Computing,Information and Control

2020

See List of Professors in Ts. Dr. Sicily Ting Fung Fung University(Monash University)

Co-Authors

academic-engine