Learning selective mutual attention and contrast for RGB-D saliency detection
How to effectively fuse cross-modal information is a key problem for RGB-D salient object
detection. Early fusion and result fusion schemes fuse RGB and depth information at the …
detection. Early fusion and result fusion schemes fuse RGB and depth information at the …
Deep learning inspired object consolidation approaches using lidar data for autonomous driving: a review
Abstract Autonomous Driving Vehicle (ADV) services have become a prominent motif in
intelligent vehicle technology by adapting deep learning features. Automated driverless …
intelligent vehicle technology by adapting deep learning features. Automated driverless …
Deep learning-based computer vision methods for complex traffic environments perception: A review
Computer vision applications in intelligent transportation systems (ITS) and autonomous
driving (AD) have gravitated towards deep neural network architectures in recent years …
driving (AD) have gravitated towards deep neural network architectures in recent years …
Adversarial mixup ratio confusion for unsupervised domain adaptation
Multimedia applications often involve knowledge transfer across domains, eg, from images
to texts, where Unsupervised Domain Adaptation (UDA) can be used to reduce the domain …
to texts, where Unsupervised Domain Adaptation (UDA) can be used to reduce the domain …
Aligning correlation information for domain adaptation in action recognition
Domain adaptation (DA) approaches address domain shift and enable networks to be
applied to different scenarios. Although various image DA approaches have been proposed …
applied to different scenarios. Although various image DA approaches have been proposed …
Multi-spectral template matching based object detection in a few-shot learning manner
Multi-spectral template matching (MSTM) based object detection approaches can be widely
used in robotics and aerospace systems for fine-grained object discovery. However, the …
used in robotics and aerospace systems for fine-grained object discovery. However, the …
Towards Adaptive Multi-Scale Intermediate Domain via Progressive Training for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) involves the transfer of knowledge from a labelled
source domain to an unlabelled target domain. Recent studies have introduced the concept …
source domain to an unlabelled target domain. Recent studies have introduced the concept …
Shadowsense: Unsupervised domain adaptation and feature fusion for shadow-agnostic tree crown detection from rgb-thermal drone imagery
R Kapil, SM Marvasti-Zadeh… - Proceedings of the …, 2024 - openaccess.thecvf.com
Accurate detection of individual tree crowns from remote sensing data poses a significant
challenge due to the dense nature of forest canopy and the presence of diverse …
challenge due to the dense nature of forest canopy and the presence of diverse …
Domain adaptation for in-line allergen classification of agri-food powders using near-infrared spectroscopy
The addition of incorrect agri-food powders to a production line due to human error is a large
safety concern in food and drink manufacturing, owing to incorporation of allergens in the …
safety concern in food and drink manufacturing, owing to incorporation of allergens in the …
Physiological characteristics inspired hidden human object detection model
The current target detection algorithms provide the unsatisfactory performance on the task of
detecting hidden human targets. In this study, we put forward the physiological …
detecting hidden human targets. In this study, we put forward the physiological …