1.9k citations · 2.4k across the 11 of their papers we have counts for
11 papers
LGA-RCNN: Loss-Guided Attention for Object Detection
Xin Yi, Jiahao Wu, Bo Ma +2
Object detection is widely studied in computer vision filed. In recent years, certain representative deep learning based detection methods along with solid benchmarks are proposed,…
Self-Paced Uncertainty Estimation for One-shot Person Re-Identification
Yulin Zhang, Bo Ma, Longyao Liu +1
The one-shot Person Re-ID scenario faces two kinds of uncertainties when constructing the prediction model from to . The first is model uncertainty, which captures the noise…
Two-Step Image Dehazing with Intra-domain and Inter-domain Adaptation
Xin Yi, Bo Ma, Yulin Zhang +2
Caused by the difference of data distributions, intra-domain gap and inter-domain gap are widely present in image processing tasks. In the field of image dehazing, certain previous…
Automatic classification of multiple catheters in neonatal radiographs with deep learning
Robert D. E. Henderson, Xin Yi, Scott J. Adams +1
We develop and evaluate a deep learning algorithm to classify multiple catheters on neonatal chest and abdominal radiographs. A convolutional neural network (CNN) was trained using…
AFD-Net: Adaptive Fully-Dual Network for Few-Shot Object Detection
Longyao Liu, Bo Ma, Yulin Zhang +2
Few-shot object detection (FSOD) aims at learning a detector that can fast adapt to previously unseen objects with scarce annotated examples, which is challenging and demanding. Ex…
Computer-Aided Assessment of Catheters and Tubes on Radiographs: How Good is Artificial Intelligence for Assessment?
Xin Yi, Scott J. Adams, Robert D. E. Henderson +1
Catheters are the second most common abnormal finding on radiographs. The position of catheters must be assessed on all radiographs, as serious complications can arise if catheters…
Focus-Enhanced Scene Text Recognition with Deformable Convolutions
Linjie Deng, Yanxiang Gong, Xinchen Lu +3
Recently, scene text recognition methods based on deep learning have sprung up in computer vision area. The existing methods achieved great performances, but the recognition of irr…
Generative Adversarial Network in Medical Imaging: A Review
Xin Yi, Ekta Walia, Paul Babyn
Generative adversarial networks have gained a lot of attention in the computer vision community due to their capability of data generation without explicitly modelling the probabil…
Automatic catheter detection in pediatric X-ray images using a scale-recurrent network and synthetic data
Xin Yi, Scott Adams, Paul Babyn +1
Catheters are commonly inserted life supporting devices. X-ray images are used to assess the position of a catheter immediately after placement as serious complications can arise f…
Unsupervised and semi-supervised learning with Categorical Generative Adversarial Networks assisted by Wasserstein distance for dermoscopy image Classification
Xin Yi, Ekta Walia, Paul Babyn
Melanoma is a curable aggressive skin cancer if detected early. Typically, the diagnosis involves initial screening with subsequent biopsy and histopathological examination if nece…
Sharpness-aware Low dose CT denoising using conditional generative adversarial network
Xin Yi, Paul Babyn
Low Dose Computed Tomography (LDCT) has offered tremendous benefits in radiation restricted applications, but the quantum noise as resulted by the insufficient number of photons co…