搜索结果: 1-15 共查到“Adversarial”相关记录22条 . 查询时间(0.031 秒)
Using adversarial attacks to refine molecular energy predictions（图）
对抗性攻击 分子能量预测 量化神经网络 分子能量 不确定性
2023/6/7
Neural networks (NNs) are increasingly being used to predict new materials, the rate and yield of chemical reactions, and drug-target interactions, among others. For these applications, they are order...
Multi-owner Secure Encrypted Search Using Searching Adversarial Networks
Searchable Symmetric Encryption Multi-owner Ranked Search
2019/8/14
Searchable symmetric encryption (SSE) for multi-owner model draws much attention as it enables data users to perform searches over encrypted cloud data outsourced by data owners. However, implementing...
Multi-client Secure Encrypted Search Using Searching Adversarial Networks
Searchable Encryption Multi-keyword Ranked Search Multi-owner Model
2019/8/8
With the rapid development of cloud computing, searchable encryption for multiple data owners model (multi-owner model) draws much attention as it enables data users to perform searches on encrypted c...
The Adversarial Robustness of Sampling
random sampling adversarial model epsilon-approximation
2019/7/8
Random sampling is a fundamental primitive in modern algorithms, statistics, and machine learning, used as a generic method to obtain a small yet ``representative'' subset of the data. In this work, w...
GENERATIVE ADVERSARIAL NETWORKS FOR SINGLE PHOTO 3D RECONSTRUCTION
generative adversarial networks deep convolutional neural networks
2019/3/2
Fast but precise 3D reconstructions of cultural heritage scenes are becoming very requested in the archaeology and architecture. While modern multi-image 3D reconstruction approaches provide impressiv...
GENERATIVE ADVERSARIAL NETWORKS FOR SINGLE PHOTO 3D RECONSTRUCTION
generative adversarial networks deep convolutional neural networks
2019/3/2
Fast but precise 3D reconstructions of cultural heritage scenes are becoming very requested in the archaeology and architecture. While modern multi-image 3D reconstruction approaches provide impressiv...
Prime and Prejudice: Primality Testing Under Adversarial Conditions
Primality testing Miller-Rabin test Lucas test
2018/8/20
This work provides a systematic analysis of primality testing under adversarial conditions, where the numbers being tested for primality are not generated randomly, but instead provided by a possibly ...
CHANGE DETECTION IN REMOTE SENSING IMAGES USING CONDITIONAL ADVERSARIAL NETWORKS
Change Detection Database Deep Convolutional Neural Networks Generative Adversarial Networks
2018/6/4
We present a method for change detection in images using Conditional Adversarial Network approach. The original network architecture based on pix2pix is proposed and evaluated for difference map creat...
AUTOMATIC LARGE-SCALAE 3D BUILDING SHAPE REFINEMENT USING CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
Conditional generative adversarial networks (cGANs) Digital Surface Model 3D scene refinement 3D building shape
2018/6/4
Three-dimensional building reconstruction from remote sensing imagery is one of the most difficult and important 3D modeling problems for complex urban environments. The main data sources provided the...
How to (not) share a password: Privacy preserving protocols for finding heavy hitters with adversarial behavior
passwords secure computation differential privacy, heavy hitters
2018/1/12
Bad choices of passwords were and are a pervasive problem. Most password alternatives (such as two-factor authentication) may increase cost and arguably hurt the usability of the system. This is of sp...
Illusion and Dazzle: Adversarial Optical Channel Exploits against Lidars for Automotive Applications
attack autonomous car sensor
2017/6/27
With the advancement in computing, sensing, and vehicle electronics, autonomous vehicles are being realized. For autonomous driving, environment perception sensors such as radars, lidars, and vision s...
No Bot Expects the DeepCAPTCHA! Introducing Immutable Adversarial Examples with Applications to CAPTCHA
deep learning CAPTCHAs
2016/4/7
Recent advances in Deep Learning (DL) allow for solving complex AI problems that used to be very hard. While this progress has advanced many fields, it is considered to be bad news for CAPTCHAs (Compl...
Many efficient data structures use randomness, allowing them to improve upon deterministic
ones. Usually, their efficiency and/or correctness are analyzed using probabilistic tools under
the assumpt...
A Unified Security Model of Authenticated Key Exchange with Specific Adversarial Capabilities
Authenticated Key Exchange Provable Security Security Model
2014/3/5
The most widely accepted models in the security proofs of Authenticated Key Exchange protocols are the Canetti-Krawczyk model and the extended Canetti-Krawczyk model that admit different adversarial q...
Private Interactive Communication Across an Adversarial Channel
Interactive communication coding
2014/3/13
Consider two parties Alice and Bob, who hold private inputs x and y, and wish to compute a function f(x,y) privately in the information theoretic sense; that is, each party should learn nothing beyond...