activity
20172022
most citedDSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation

88 citations · 330 across the 10 of their papers we have counts for

collaborators

9 papers

cs.CV202188 cited

DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation

Ziyuan Zhao, Zeng Zeng, Kaixin Xu +2

Image segmentation is one of the most essential biomedical image processing problems for different imaging modalities, including microscopy and X-ray in the Internet-of-Medical-Thi…

cs.CV202030 cited

Sea-Net: Squeeze-And-Excitation Attention Net For Diabetic Retinopathy Grading

Ziyuan Zhao, Kartik Chopra, Zeng Zeng +1

Diabetes is one of the most common disease in individuals. \textit{Diabetic retinopathy} (DR) is a complication of diabetes, which could lead to blindness. Automatic DR grading bas…

eess.SP20202 cited

A Hierarchical Deep Convolutional Neural Network and Gated Recurrent Unit Framework for Structural Damage Detection

Jianxi Yang, Likai Zhang, Cen Chen +5

Structural damage detection has become an interdisciplinary area of interest for various engineering fields, while the available damage detection methods are being in the process o…

cs.CV20196 cited

Ordered or Orderless: A Revisit for Video based Person Re-Identification

Le Zhang, Zenglin Shi, Joey Tianyi Zhou +5

Is recurrent network really necessary for learning a good visual representation for video based person re-identification (VPRe-id)? In this paper, we first show that the common pra…

cs.CV20192 cited

FaultNet: Faulty Rail-Valves Detection using Deep Learning and Computer Vision

Ramanpreet Singh Pahwa, Jin Chao, Jestine Paul +7

Regular inspection of rail valves and engines is an important task to ensure the safety and efficiency of railway networks around the globe. Over the past decade, computer vision a…

eess.IV20191 cited

Cribriform pattern detection in prostate histopathological images using deep learning models

Malay Singh, Emarene Mationg Kalaw, Wang Jie +7

Architecture, size, and shape of glands are most important patterns used by pathologists for assessment of cancer malignancy in prostate histopathological tissue slides. Varying st…