Recent advances in convolutional neural networks
In the last few years, deep learning has led to very good performance on a variety of
problems, such as visual recognition, speech recognition and natural language processing …
problems, such as visual recognition, speech recognition and natural language processing …
Automated plant species identification—Trends and future directions
Current rates of species loss triggered numerous attempts to protect and conserve
biodiversity. Species conservation, however, requires species identification skills, a …
biodiversity. Species conservation, however, requires species identification skills, a …
Attentive region embedding network for zero-shot learning
Zero-shot learning (ZSL) aims to classify images from unseen categories, by merely utilizing
seen class images as the training data. Existing works on ZSL mainly leverage the global …
seen class images as the training data. Existing works on ZSL mainly leverage the global …
Mask-CNN: Localizing parts and selecting descriptors for fine-grained bird species categorization
Fine-grained image recognition is a challenging computer vision problem, due to the small
inter-class variations caused by highly similar subordinate categories, and the large intra …
inter-class variations caused by highly similar subordinate categories, and the large intra …
Region graph embedding network for zero-shot learning
Most of the existing Zero-Shot Learning (ZSL) approaches learn direct embeddings from
global features or image parts (regions) to the semantic space, which, however, fail to …
global features or image parts (regions) to the semantic space, which, however, fail to …
Semantic-aware scene recognition
Scene recognition is currently one of the top-challenging research fields in computer vision.
This may be due to the ambiguity between classes: images of several scene classes may …
This may be due to the ambiguity between classes: images of several scene classes may …
Automatic classification of pavement distress using 3D ground-penetrating radar and deep convolutional neural network
X Liang, X Yu, C Chen, Y **… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The realization of nondestructive detection and classification of pavement distress is of great
significance for putting forward a reasonable maintenance scheme and prolonging the …
significance for putting forward a reasonable maintenance scheme and prolonging the …
Flower classification using deep convolutional neural networks
Flower classification is a challenging task due to the wide range of flower species, which
have a similar shape, appearance or surrounding objects such as leaves and grass. In this …
have a similar shape, appearance or surrounding objects such as leaves and grass. In this …
Multifaceted fused-CNN based scoring of breast cancer whole-slide histopathology images
Automating the scoring of Whole-Slide Images (WSIs) is a challenging task because the
search space for selecting region of interest (ROI) is huge due to the very large sizes of …
search space for selecting region of interest (ROI) is huge due to the very large sizes of …
TA-CNN: Two-way attention models in deep convolutional neural network for plant recognition
Automatic plant recognition using AI is a challenging problem. In addition to the recognition
of the plant specimen, we also want to recognize the plant type in its actual living …
of the plant specimen, we also want to recognize the plant type in its actual living …