Pooling in convolutional neural networks for medical image analysis: a survey and an empirical study
Convolutional neural networks (CNN) are widely used in computer vision and medical
image analysis as the state-of-the-art technique. In CNN, pooling layers are included mainly …
image analysis as the state-of-the-art technique. In CNN, pooling layers are included mainly …
A survey of evaluation metrics used for NLG systems
In the last few years, a large number of automatic evaluation metrics have been proposed for
evaluating Natural Language Generation (NLG) systems. The rapid development and …
evaluating Natural Language Generation (NLG) systems. The rapid development and …
Fine-grained image analysis with deep learning: A survey
Fine-grained image analysis (FGIA) is a longstanding and fundamental problem in computer
vision and pattern recognition, and underpins a diverse set of real-world applications. The …
vision and pattern recognition, and underpins a diverse set of real-world applications. The …
X-linear attention networks for image captioning
Recent progress on fine-grained visual recognition and visual question answering has
featured Bilinear Pooling, which effectively models the 2nd order interactions across multi …
featured Bilinear Pooling, which effectively models the 2nd order interactions across multi …
Learning attention-guided pyramidal features for few-shot fine-grained recognition
H Tang, C Yuan, Z Li, J Tang - Pattern Recognition, 2022 - Elsevier
Few-shot fine-grained recognition (FS-FGR) aims to distinguish several highly similar
objects from different sub-categories with limited supervision. However, traditional few-shot …
objects from different sub-categories with limited supervision. However, traditional few-shot …
Attention on attention for image captioning
Attention mechanisms are widely used in current encoder/decoder frameworks of image
captioning, where a weighted average on encoded vectors is generated at each time step to …
captioning, where a weighted average on encoded vectors is generated at each time step to …
Pooling methods in deep neural networks, a review
H Gholamalinezhad, H Khosravi - arXiv preprint arXiv:2009.07485, 2020 - arxiv.org
Nowadays, Deep Neural Networks are among the main tools used in various sciences.
Convolutional Neural Network is a special type of DNN consisting of several convolution …
Convolutional Neural Network is a special type of DNN consisting of several convolution …
Hierarchical deep click feature prediction for fine-grained image recognition
The click feature of an image, defined as the user click frequency vector of the image on a
predefined word vocabulary, is known to effectively reduce the semantic gap for fine-grained …
predefined word vocabulary, is known to effectively reduce the semantic gap for fine-grained …
Mixed high-order attention network for person re-identification
Attention has become more attractive in person re-identification (ReID) as it is capable of
biasing the allocation of available resources towards the most informative parts of an input …
biasing the allocation of available resources towards the most informative parts of an input …
Do better imagenet models transfer better?
Transfer learning is a cornerstone of computer vision, yet little work has been done to
evaluate the relationship between architecture and transfer. An implicit hypothesis in …
evaluate the relationship between architecture and transfer. An implicit hypothesis in …