Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …
prevalence in natural language processing or computer vision. Since medical imaging bear …
A survey on instance segmentation: state of the art
Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …
digital image inference. It not only provides the classes of the image objects, but also …
Differentiable augmentation for data-efficient gan training
The performance of generative adversarial networks (GANs) heavily deteriorates given a
limited amount of training data. This is mainly because the discriminatorsis memorizing the …
limited amount of training data. This is mainly because the discriminatorsis memorizing the …
Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection
Object detection has been dominated by anchor-based detectors for several years.
Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal …
Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal …
A review on generative adversarial networks: Algorithms, theory, and applications
Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …
however, they have been studied since 2014, and a large number of algorithms have been …
Object detection in 20 years: A survey
Object detection, as of one the most fundamental and challenging problems in computer
vision, has received great attention in recent years. Over the past two decades, we have …
vision, has received great attention in recent years. Over the past two decades, we have …
Recent advances in deep learning for object detection
Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …
been widely studied in the past decades. Visual object detection aims to find objects of …
[HTML][HTML] A state-of-the-art survey on deep learning theory and architectures
In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …
domains. This new field of machine learning has been growing rapidly and has been …
A review of object detection based on deep learning
With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …
networks (DCNNs) have become more important for object detection. Compared with …
Imbalance problems in object detection: A review
In this paper, we present a comprehensive review of the imbalance problems in object
detection. To analyze the problems in a systematic manner, we introduce a problem-based …
detection. To analyze the problems in a systematic manner, we introduce a problem-based …