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Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Regional Inventories for the Complex, Mixed-Species Forests of the Eastern United States
LiDAR airborne laser scanning enhanced forest inventory aboveground biomass forest carbon deep learning Maine New Hampshire Vermont Massachusetts Connecticut Rhode Island
2023/12/5
Light detection and ranging (LiDAR) has become a commonly-used tool for generating remotely-sensed forest inventories. However, LiDAR-derived forest inventories have remained uncommon at a regional sc...
Climate-Based Regionalization and Inclusion of Spectral Indices for Enhancing Transboundary Land-Use/Cover Classification Using Deep Learning and Machine Learning
machine learning ratio-based indices orthogonal indices Koppen–Geiger climate regionalization landscape change remote sensing landcover
2023/12/4
Accurate land use and cover data are essential for effective land-use planning, hydrological modeling, and policy development. Since the Okavango Delta is a transboundary Ramsar site, managing natural...
Forest Farm Fire Drone Monitoring System Based on Deep Learning and Unmanned Aerial Vehicle Imagery
Forest Farm Fire Monitoring System Deep Learning
2023/12/1
Forest fires represent one of the main problems threatening forest sustainability. Therefore, an early prevention system of forest fire is urgently needed. To address the problem of forest farm fire m...
Deep Learning Model Generalization in Side-Channel Analysis
Side-Channel Analysis Deep Learning Model Generalization
2019/8/30
The adoption of deep neural networks for profiled side-channel attacks provides different capabilities for leakage detection of secure products. Research papers provide a variety of arguments with res...
X-DeepSCA: Cross-Device Deep Learning Side Channel Attack
Side-channel Attacks Profiling attacks Cross-device Attack
2019/7/17
This article, for the first time, demonstrates Cross-device Deep Learning Side-Channel Attack (X-DeepSCA), achieving an accuracy of >99.9%>99.9%, even in presence of significantly higher inter-device ...
How Diversity Affects Deep-Learning Side-Channel Attacks
Side-channel attack power analysis deep learning
2019/6/6
Deep learning side-channel attacks are an emerging threat to the security of implementations of cryptographic algorithms. The attacker first trains a model on a large set of side-channel traces captur...
Simulating Homomorphic Evaluation of Deep Learning Predictions
neural networks homomorphic encryption TFHE
2019/5/31
Convolutional neural networks (CNNs) is a category of deep neural networks that are primarily used for classifying image data. Yet, their continuous gain in popularity poses important privacy concerns...
Deep Learning based Side Channel Attacks in Practice
Deep Learning based Side-Channel Attacks Data Dimensionality Data Scaling
2019/5/29
A recent line of research has investigated a new profiling technique based on deep learning as an alternative to the well-known template attack. The advantage of this new profiling approach is twofold...
Deep Learning based Model Building Attacks on Arbiter PUF Compositions
physically unclonable function machine learning deep learning
2019/5/28
Robustness to modeling attacks is an important requirement for PUF circuits. Several reported Arbiter PUF com- positions have resisted modeling attacks. and often require huge computational resources ...
DL-LA: Deep Learning Leakage Assessment: A modern roadmap for SCA evaluations
side channel leakage assessment deep learning
2019/5/21
In recent years, deep learning has become an attractive ingredient to side-channel analysis (SCA) due to its potential to improve the success probability or enhance the performance of certain frequent...
A Comprehensive Study of Deep Learning for Side-Channel Analysis
Side Channel Analysis Profiling Attacks Machine Learning
2019/5/5
In Side Channel Analysis, masking is known to be a reliable and robust counter-measure. Recently, several papers have focused on the application of the Deep Learning (DL) theory to improve the efficie...
nGraph-HE: A Graph Compiler for Deep Learning on Homomorphically Encrypted Data
Homomorphic encryption intermediate representation deep learning
2019/4/3
Homomorphic encryption (HE)---the ability to perform computation on encrypted data---is an attractive remedy to increasing concerns about data privacy in deep learning (DL). However, building DL model...
TOWARDS DEEP LEARNING FOR ARCHITECTURE: A MONUMENT RECOGNITION MOBILE APP
Artificial Intelligence Machine Learning Deep Learning Convolutional Neural Networks
2019/3/4
In recent years, the diffusion of large image datasets and an unprecedented computational power have boosted the development of a class of artificial intelligence (AI) algorithms referred to as deep l...
Deep Learning to Evaluate Secure RSA Implementations
Side-Channel Attacks RSA Deep Learning
2019/1/26
This paper presents the results of several successful profiled side-channel attacks against a secure implementation of the RSA algorithm. The implementation was running on a ARM Core SC 100 completed ...
This paper presents a very practical key recovery attack on Speck32/64 reduced to 11 rounds based on a novel type of differential distinguisher using machine learning. These distinguishers exceed dist...