搜索结果: 46-60 共查到“Deep learning”相关记录71条 . 查询时间(0.032 秒)
DEEP LEARNING FOR LOWTEXTURED IMAGE MATCHING
image matching deep convolutional neural networks auto-encoders cultural heritage
2018/6/4
Low-textured objects pose challenges for an automatic 3D model reconstruction. Such objects are common in archeological applications of photogrammetry. Most of the common feature point descriptors fai...
RAPID OBJECT DETECTION SYSTEMS, UTILISING DEEP LEARNING AND UNMANNED AERIAL SYSTEMS (UAS) FOR CIVIL ENGINEERING APPLICATIONS
Object detection Deep Learning Unmanned Aerial Systems Railway, Rapid
2018/6/4
With deep learning approaches now out-performing traditional image processing techniques for image understanding, this paper accesses the potential of rapid generation of Convolutional Neural Networks...
ROOFN3D: DEEP LEARNING TRAINING DATA FOR 3D BUILDING RECONSTRUCTION
3D Database Machine Learning 3D Building Models Classification Segmentation Reconstruction
2018/6/5
Machine learning methods have gained in importance through the latest development of artificial intelligence and computer hardware. Particularly approaches based on deep learning have shown that they ...
Non-Profiled Deep Learning-Based Side-Channel Attacks
side-channel attacks deep learning machine learning
2018/3/5
Deep Learning has recently been introduced as a new alternative to perform Side-Channel analysis. Until now, studies have been focused on applying Deep Learning techniques to perform Profiled Side-Cha...
Study of Deep Learning Techniques for Side-Channel Analysis and Introduction to ASCAD Database
Deep Learning Side-Channel Analysis AES
2018/1/15
To provide insurance on the resistance of a system against side-channel analysis, several national or private schemes are today promoting an evaluation strategy, common in classical cryptography, whic...
On the Performance of Deep Learning for Side-channel Analysis
Side-channel analysis Machine learning Deep learning
2018/1/12
Profiled side-channel attacks represent the most powerful category of side-channel attacks. There we have a number of methods promising to work well in a number of different scenarios. Still, the area...
In recent years, artificial neural networks a.k.a. deep learning have significantly improved the fields of computer vision, speech recognition, and natural language processing. The success relies on t...
Supercomputing Speeds Up Deep Learning Training（图）
Supercomputing Speeds Up Learning Training
2017/11/24
A team of researchers from the University of California, Berkeley, the University of California, Davis and the Texas Advanced Computing Center (TACC) published the results of an effort to harness the ...
Privacy-Preserving Deep Learning via Additively Homomorphic Encryption
SGD privacy-preserving deep learning system
2017/7/28
We build a privacy-preserving deep learning system in which many learning participants perform neural network-based deep learning over a combined dataset of all, without actually revealing the partici...
2017年深度学习的实际应用专题会议（Special Session on Practical Applications of Deep Learning）
2017年 深度学习 实际应用 专题会议
2017/6/23
In the recent years, deep learning methods have emerged as a powerful machine learning method for many fields. Deep learning methods are different from all traditional approaches. They automatically l...
Recent advances in deep learning techniques have made impressive progress in many areas of computer vision, including classification, detection, and segmentation. While all of these areas are relevant...
DeepSecure: Scalable Provably-Secure Deep Learning
Deep Learning Secure Function Evaluation Garbled Circuit
2017/6/5
This paper proposes DeepSecure, a novel framework that enables scalable execution of the state-of-the-art Deep Learning (DL) models in a privacy-preserving setting. DeepSecure targets scenarios in whi...
Rice U. scientists slash computations for ‘deep learning’
Rice U. scientists slash computations deep learning
2017/7/21
Rice University computer scientists have adapted a widely used technique for rapid data lookup to slash the amount of computation — and thus energy and time — required for deep learning, a computation...
MANHOLE COVER LOCALIZATION IN AERIAL IMAGES WITH A DEEP LEARNING APPROACH
Deep learning high resolution imagery urban object detection Convolutional Neural Network
2017/7/12
Urban growth is an ongoing trend and one of its direct consequences is the development of buried utility networks. Locating these networks is becoming a challenging task. While the labeling of large o...
ROOF TYPE SELECTION BASED ON PATCH-BASED CLASSIFICATION USING DEEP LEARNING FOR HIGH RESOLUTION SATELLITE IMAGERY
Roof Reconstruction High Resolution Satellite Imagery Deep Learning Method Convolutional Neural Networks
2017/7/13
3D building reconstruction from remote sensing image data from satellites is still an active research topic and very valuable for 3D city modelling. The roof model is the most important component to r...