Fine|grained Image Classification Method for Recurrent ...

Recurrent Attention Convolutional Neural Network for Fine-Grained ...

Learning discriminative features is crucial for fine- grained image recognition. Due to the success of deep learning, most of the methods depend on the powerful ...

Fine-grained image classification method based on hybrid attention ...

Fine-grained image classification methods are broadly categorized into two types: those relying on deep learning and traditional methods based ...

Recurrent Attention Convolutional Neural Network for Fine-grained ...

Learning discriminative features is crucial for fine- grained image recognition. Due to the success of deep learning, most of the methods depend on the powerful ...

Fine-grained image recognition method for digital media based on ...

This extracts as much information as possible from fine-grained images under weak supervision to improve the recognition accuracy. When the ...

Fine-grained image classification method based on hybrid attention ...

To efficiently capture feature information in tasks of fine-grained image classification, this study introduces a new network model for ...

RAMS-Trans: Recurrent Attention Multi-scale Transformer forFine ...

Abstract:In fine-grained image recognition (FGIR), the localization and amplification of region attention is an important factor, ...

Fine-Grained Image Classification - Papers With Code

Fine-Grained Image Classification is a task in computer vision where the goal is to classify images into subcategories within a larger category.

A fine-grained image classification algorithm based on self ... - Nature

The model is then trained on a large dataset to comprehend the semantic information of the image and reconstruct the masked-off image blocks.

Image Classification by Image Subsets for Fine-Grained Image ...

The output of this process will be used as the input to a recurrent neural network, ultimately classify the initial image. In processing the ...

Weakly supervised fine-grained image classification via two-level ...

To address the above issues, we propose the Object Attention Activation Module (OAAM) to locate the target object, which is a novel method to obtain the object ...

haoweiz23/Awesome-Fine-grained-Visual-Classification - GitHub

By Attention-based methods · [RA-CNN] Look Closer to See Better: Recurrent Attention Convolutional Neural Networkfor Fine-grained Image Recognition (CVPR, 2017) ...

Multi-branch Recurrent Attention Convolutional Neural Network with ...

Fine-grained image classification (FGIC) aims to classify subordinate classes belonging to the same meta category. One of the existing FGIC methods is to ...

Image classification with recurrent attention models | Semantic Scholar

... images, and a fine-grained recognition dataset of 200 bird species. In this work we apply a fully differentiable Recurrent Model of Visual Attention to ...

Fine-Grained Image Classification via Combining Vision and ...

A mid-level temporal CNN hidden layer is at the bottom of CNN-RNN model, and a recurrent network is stacked on it. ... fine-grained image classification methods.

Learning Cascade Attention for fine-grained image classification

Our method first leverages the Spatial Confusion Attention to identify ambiguous areas of the input image. Two constraint loss functions are proposed: the ...

arkel23/AFGIC: Awesome Fine-Grained Image Classification - GitHub

2017 · Look Closer to See Better: Recurrent Attention Convolutional Neural Network for Fine-grained Image Recognition. · Learning Multi-Attention Convolutional ...

Hybrid Feature Collaborative Reconstruction Network for Few-Shot ...

This reconstruction-based approach has shown remarkable performance in few-shot fine-grained image classification and has brought new insights ...

MSFF: Multi-Scale feature fusion for fine-grained image classification

To evaluate the effectiveness of our method, fine-grained classification experiments were conducted on three datasets. The experimental results show that the ...

Few-Shot Fine-Grained Image Classification via GNN - MDPI

The experiments on three datasets (CIFAR-100, CUB, and DOGS) have shown that the proposed method yields better performances. This indicates that the proposed ...

Awesome Fine-Grained Image Analysis – Papers, Codes and ...

A Survey on Deep Learning-based Fine-Grained Object Classification and Semantic Segmentation. Bo Zhao, Jiashi Feng, Xiao Wu, and Shuicheng Yan. International ...