Search Results for author:
Found 22 papers, 8 papers with code
Mammo-CLIP: Leveraging Contrastive Language-Image Pre-training (CLIP) for Enhanced Breast Cancer Diagnosis with Multi-view Mammography
For framework evaluation, we assembled two datasets retrospectively.
Universal Perturbation-based Secret Key-Controlled Data Hiding
In this paper, we propose a novel universal perturbation-based secret key-controlled data-hiding method, realizing data hiding with a single universal perturbation and data decoding with the secret key-controlled decoder.
RFLA: A Stealthy Reflected Light Adversarial Attack in the Physical World
In this paper, we propose a novel Reflected Light Attack (RFLA), featuring effective and stealthy in both the digital and physical world, which is implemented by placing the color transparent plastic sheet and a paper cut of a specific shape in front of the mirror to create different colored geometries on the target object.
Multi-objective Evolutionary Search of Variable-length Composite Semantic Perturbations
To bridge the gap between AutoML and semantic adversarial attacks, we propose a novel method called multi-objective evolutionary search of variable-length composite semantic perturbations (MES-VCSP).
Efficient Search of Comprehensively Robust Neural Architectures via Multi-fidelity Evaluation
Finally, we propose a multi-fidelity online surrogate during optimization to further decrease the search cost.
Adversarial Infrared Blocks: A Multi-view Black-box Attack to Thermal Infrared Detectors in Physical World
Infrared imaging systems have a vast array of potential applications in pedestrian detection and autonomous driving, and their safety performance is of great concern.
A Plug-and-Play Defensive Perturbation for Copyright Protection of DNN-based Applications
Then, we extract the copyright information from the encoded copyrighted image with the devised copyright decoder.
RecFNO: a resolution-invariant flow and heat field reconstruction method from sparse observations via Fourier neural operator
The MLP embedding is propitious to more sparse input, while the others benefit from spatial information preservation and perform better with the increase of observation data.
Differential Evolution based Dual Adversarial Camouflage: Fooling Human Eyes and Object Detectors
In the first stage, we optimize the global texture to minimize the discrepancy between the rendered object and the scene images, making human eyes difficult to distinguish.
A Survey on Physical Adversarial Attack in Computer Vision
Then, we discuss the existing physical attacks and focus on the technique for improving the robustness of physical attacks under complex physical environmental conditions.
A Multi-objective Memetic Algorithm for Auto Adversarial Attack Optimization Design
Therefore, we propose a multi-objective memetic algorithm for auto adversarial attack optimization design, which realizes the automatical search for the near-optimal adversarial attack towards defensed models.
Heat Source Layout Optimization Using Automatic Deep Learning Surrogate and Multimodal Neighborhood Search Algorithm
In satellite layout design, heat source layout optimization (HSLO) is an effective technique to decrease the maximum temperature and improve the heat management of the whole system.
Algorithms for Bayesian network modeling and reliability inference of complex multistate systems: Part II-Dependent systems
This Part II proposes a novel method for BN reliability modeling and analysis to apply the compression idea to the complex multistate dependent system.
Contrastive Enhancement Using Latent Prototype for Few-Shot Segmentation
This paper proposes a contrastive enhancement approach using latent prototypes to leverage latent classes and raise the utilization of similarity information between prototype and query features.
$A^{3}D$: A Platform of Searching for Robust Neural Architectures and Efficient Adversarial Attacks
To alleviate these problems, in this paper, we first propose a novel platform called auto adversarial attack and defense ($A^{3}D$), which can help search for robust neural network architectures and efficient adversarial attacks.
Predicting Shallow Water Dynamics using Echo-State Networks with Transfer Learning
In this paper we demonstrate that reservoir computing can be used to learn the dynamics of the shallow-water equations.
Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data
As the construction of data pairs in most engineering problems is time-consuming, data acquisition is becoming the predictive capability bottleneck of most deep surrogate models, which also exists in surrogate for thermal analysis and design.
FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack
To bridge the gap between digital attacks and physical attacks, we exploit the full 3D vehicle surface to propose a robust Full-coverage Camouflage Attack (FCA) to fool detectors.
A Machine Learning Surrogate Modeling Benchmark for Temperature Field Reconstruction of Heat-Source Systems
To overcome this problem, this work develops a machine learning modelling benchmark for TFR-HSS task.
IDRLnet: A Physics-Informed Neural Network Library
Physics Informed Neural Network (PINN) is a scientific computing framework used to solve both forward and inverse problems modeled by Partial Differential Equations (PDEs).
A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source Layout
Thermal issue is of great importance during layout design of heat source components in systems engineering, especially for high functional-density products.
Edge Computing Assisted Autonomous Flight for UAV: Synergies between Vision and Communications
By proposing a framework of Edge Computing Assisted Autonomous Flight (ECAAF), we illustrate that vision and communications can interact with and assist each other with the aid of edge computing and offloading, and further speed up the UAV mission completion.
Edge-computing
Trajectory Planning
Networking and Internet Architecture
Robotics
Systems and Control
Systems and Control
