A brief survey on semantic segmentation with deep learning

S Hao, Y Zhou, Y Guo - Neurocomputing, 2020 - Elsevier
Semantic segmentation is a challenging task in computer vision. In recent years, the
performance of semantic segmentation has been greatly improved by using deep learning …

[HTML][HTML] Deep learning for detecting macroplastic litter in water bodies: A review

T Jia, Z Kapelan, R de Vries, P Vriend, EC Peereboom… - Water Research, 2023 - Elsevier
Plastic pollution in water bodies is an unresolved environmental issue that damages all
aquatic environments, and causes economic and health problems. Accurate detection of …

U2Fusion: A unified unsupervised image fusion network

H Xu, J Ma, J Jiang, X Guo… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This study proposes a novel unified and unsupervised end-to-end image fusion network,
termed as U2Fusion, which is capable of solving different fusion problems, including multi …

General multi-label image classification with transformers

J Lanchantin, T Wang, V Ordonez… - Proceedings of the …, 2021 - openaccess.thecvf.com
Multi-label image classification is the task of predicting a set of labels corresponding to
objects, attributes or other entities present in an image. In this work we propose the …

Multi-label image recognition with graph convolutional networks

ZM Chen, XS Wei, P Wang… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
The task of multi-label image recognition is to predict a set of object labels that present in an
image. As objects normally co-occur in an image, it is desirable to model the label …

Query2label: A simple transformer way to multi-label classification

S Liu, L Zhang, X Yang, H Su, J Zhu - arXiv preprint arXiv:2107.10834, 2021 - arxiv.org
This paper presents a simple and effective approach to solving the multi-label classification
problem. The proposed approach leverages Transformer decoders to query the existence of …

Residual attention: A simple but effective method for multi-label recognition

K Zhu, J Wu - Proceedings of the IEEE/CVF international …, 2021 - openaccess.thecvf.com
Multi-label image recognition is a challenging computer vision task of practical use.
Progresses in this area, however, are often characterized by complicated methods, heavy …

Approximating cnns with bag-of-local-features models works surprisingly well on imagenet

W Brendel, M Bethge - arXiv preprint arXiv:1904.00760, 2019 - arxiv.org
Deep Neural Networks (DNNs) excel on many complex perceptual tasks but it has proven
notoriously difficult to understand how they reach their decisions. We here introduce a high …

Automatic ECG classification using continuous wavelet transform and convolutional neural network

T Wang, C Lu, Y Sun, M Yang, C Liu, C Ou - Entropy, 2021 - mdpi.com
Early detection of arrhythmia and effective treatment can prevent deaths caused by
cardiovascular disease (CVD). In clinical practice, the diagnosis is made by checking the …

Exploring categorical regularization for domain adaptive object detection

CD Xu, XR Zhao, X Jin, XS Wei - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
In this paper, we tackle the domain adaptive object detection problem, where the main
challenge lies in significant domain gaps between source and target domains. Previous …