Search Results for author:
Found 9 papers, 0 papers with code
MARformer: An Efficient Metal Artifact Reduction Transformer for Dental CBCT Images
Cone Beam Computed Tomography (CBCT) plays a key role in dental diagnosis and surgery.
Improving Visual Quality and Transferability of Adversarial Attacks on Face Recognition Simultaneously with Adversarial Restoration
To address this issue, we propose a novel adversarial attack technique known as Adversarial Restoration (AdvRestore), which enhances both visual quality and transferability of adversarial face examples by leveraging a face restoration prior.
Communication-Efficient Framework for Distributed Image Semantic Wireless Transmission
Multi-node communication, which refers to the interaction among multiple devices, has attracted lots of attention in many Internet-of-Things (IoT) scenarios.
Parameter-Free Channel Attention for Image Classification and Super-Resolution
The channel attention mechanism is a useful technique widely employed in deep convolutional neural networks to boost the performance for image processing tasks, eg, image classification and image super-resolution.
Improving the Transferability of Adversarial Attacks on Face Recognition with Beneficial Perturbation Feature Augmentation
Though generating hard samples has shown its effectiveness in improving the generalization of models in training tasks, the effectiveness of utilizing this idea to improve the transferability of adversarial face examples remains unexplored.
Semi-Supervised Contrastive Learning for Remote Sensing: Identifying Ancient Urbanization in the South Central Andes
Recently, systematic manual survey of satellite and aerial imagery has enabled continuous distributional views of archaeological phenomena at interregional scales.
NLHD: A Pixel-Level Non-Local Retinex Model for Low-Light Image Enhancement
Then a minimum fusion strategy on the results of these two transforms is utilized to achieve more natural illumination component enhancement.
Hands-on Guidance for Distilling Object Detectors
Knowledge distillation can lead to deploy-friendly networks against the plagued computational complexity problem, but previous methods neglect the feature hierarchy in detectors.
Selective Convolutional Network: An Efficient Object Detector with Ignoring Background
It is well known that attention mechanisms can effectively improve the performance of many CNNs including object detectors.
