output
20212026
most citedMLN-net: A multi-source medical image segmentation method for clustered microcalcifications using multiple layer normalization

20 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

5 papers

eess.AS2026

AILive Mixer: A Deep Learning based Zero Latency Automatic Music Mixer for Live Music Performances

Devansh Zurale, Iris Lorente, Michael Lester +1

In this work, we present a deep learning-based automatic multitrack music mixing system catered towards live performances. In a live performance, channels are often corrupted with…

cs.CV2025★ 2 cited

SAM-TTT: Segment Anything Model via Reverse Parameter Configuration and Test-Time Training for Camouflaged Object Detection

Zhenni Yu, Li Zhao, Guobao Xiao +1

This paper introduces a new Segment Anything Model (SAM) that leverages reverse parameter configuration and test-time training to enhance its performance on Camouflaged Object Dete…

cs.CV2023★ 20 cited

MLN-net: A multi-source medical image segmentation method for clustered microcalcifications using multiple layer normalization

Ke Wang, Zanting Ye, Xiang Xie +3

Accurate segmentation of clustered microcalcifications in mammography is crucial for the diagnosis and treatment of breast cancer. Despite exhibiting expert-level accuracy, recent…

cs.CV2022★ 8 cited

MMFL-Net: Multi-scale and Multi-granularity Feature Learning for Cross-domain Fashion Retrieval

Chen Bao, Xudong Zhang, Jiazhou Chen +1

Instance-level image retrieval in fashion is a challenging issue owing to its increasing importance in real-scenario visual fashion search. Cross-domain fashion retrieval aims to m…

quant-ph2021★ 12 cited

Experimental demonstration of adversarial examples in learning topological phases

Huili Zhang, Si Jiang, Xin Wang +7

Classification and identification of different phases and the transitions between them is a central task in condensed matter physics. Machine learning, which has achieved dramatic…