Fine-grained visual classification (FGVC) distinguishes sub-categories under a large
category, with significant differences within classes and minor differences between classes …

针对车辆因姿态, 视角等成像差异造成车型难以识别问题, 提出一种基于渐进式多粒度ResNet
车型识别网络. 首先, 以ResNet 网络作为主干网络, 提出渐进式多粒度局部卷积模块 …

The reasonable selection and optimized design of the deep foundation pit support scheme
is directly related to the safety, construction period, and cost of the entire project. Here …

Pair-wise similarity has been widely used for image classification by propagating the class
information from labeled images to unlabeled images and predicting the classes of …

Exploring and mining subtle yet distinctive features between sub-categories with similar
appearances is crucial for fine-grained visual categorization (FGVC). However, less effort …

With the vast development of deep learning, many deep learning-based approaches have
demonstrated their outstanding performance on the task of fine-grained visual categorization …

The process operation performance assessment (POPA) of the smelting process of electro‐
fused magnesium furnaces (EFMFs) plays a very important role for improving production …

Fine-grained recognition aims to classify images into hundreds of subcategorical labels
under a generic category. The main challenge lies in the similar appearance between sub …

Aiming at the problems of low prediction accuracy and efficiency and poor prediction effect
in the current psychological pressure prediction methods, a psychological pressure …

Fine-Grained Visual Classification (FGVC) is known as a challenging task due to subtle
differences among subordinate categories. Many current FGVC approaches focus on …