Enabling resource-efficient aiot system with cross-level optimization: A survey
The emerging field of artificial intelligence of things (AIoT, AI+ IoT) is driven by the
widespread use of intelligent infrastructures and the impressive success of deep learning …
widespread use of intelligent infrastructures and the impressive success of deep learning …
Dual cross-attention learning for fine-grained visual categorization and object re-identification
Recently, self-attention mechanisms have shown impressive performance in various NLP
and CV tasks, which can help capture sequential characteristics and derive global …
and CV tasks, which can help capture sequential characteristics and derive global …
Sim-trans: Structure information modeling transformer for fine-grained visual categorization
Fine-grained visual categorization (FGVC) aims at recognizing objects from similar
subordinate categories, which is challenging and practical for human's accurate automatic …
subordinate categories, which is challenging and practical for human's accurate automatic …
Multi-stream hybrid architecture based on cross-level fusion strategy for fine-grained crop species recognition in precision agriculture
Precision farming aims to optimizing the crop production process and managing sustainable
supply chain practices as more efficient and reasonable as possible. Recently, various …
supply chain practices as more efficient and reasonable as possible. Recently, various …
A review of robotic grasp detection technology
M Dong, J Zhang - Robotica, 2023 - cambridge.org
In order to complete many complex operations and attain more general-purpose utility,
robotic grasp is a necessary skill to master. As the most common essential action of robots in …
robotic grasp is a necessary skill to master. As the most common essential action of robots in …
Accurate fine-grained object recognition with structure-driven relation graph networks
Fine-grained object recognition (FGOR) aims to learn discriminative features that can
identify the subtle distinctions between visually similar objects. However, less effort has …
identify the subtle distinctions between visually similar objects. However, less effort has …
[HTML][HTML] NCGLF2: Network combining global and local features for fusion of multisource remote sensing data
The fusion of multisource remote sensing (RS) data has demonstrated significant potential in
target recognition and classification tasks. However, there is limited emphasis on capturing …
target recognition and classification tasks. However, there is limited emphasis on capturing …
Fine-grained object classification via self-supervised pose alignment
Semantic patterns of fine-grained objects are determined by subtle appearance difference of
local parts, which thus inspires a number of part-based methods. However, due to …
local parts, which thus inspires a number of part-based methods. However, due to …
SR-GNN: Spatial Relation-Aware Graph Neural Network for Fine-Grained Image Categorization
Over the past few years, a significant progress has been made in deep convolutional neural
networks (CNNs)-based image recognition. This is mainly due to the strong ability of such …
networks (CNNs)-based image recognition. This is mainly due to the strong ability of such …
Granularity-aware distillation and structure modeling region proposal network for fine-grained image classification
X Ke, Y Cai, B Chen, H Liu, W Guo - Pattern Recognition, 2023 - Elsevier
Fine-grained visual classification (FGVC) aims to identify objects belonging to multiple sub-
categories of the same super-category. The key to solving fine-grained classification …
categories of the same super-category. The key to solving fine-grained classification …