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Found 15 papers, 5 papers with code
The Tsinghua University-Ma Huateng Telescopes for Survey: Overview and Performance of the System
The TMTS system can have a FoV of about 9 deg2 when monitoring the sky with two bands (i. e., SDSS g and r filters) at the same time, and a maximum FoV of ~18 deg2 when four telescopes monitor different sky areas in monochromatic filter mode.
Instrumentation and Methods for Astrophysics
Molecule Property Prediction Based on Spatial Graph Embedding
And, multiple C-SGELs are stacked to construct a convolution spatial graph embedding network (C-SGEN) for end-to-end representation learning.
Ranked #2 on
Graph Regression
on Lipophilicity
Demon in the Variant: Statistical Analysis of DNNs for Robust Backdoor Contamination Detection
A security threat to deep neural networks (DNN) is backdoor contamination, in which an adversary poisons the training data of a target model to inject a Trojan so that images carrying a specific trigger will always be classified into a specific label.
Cryptography and Security
On the Ca-strong 1991bg-like type Ia supernova 2016hnk: evidence for a Chandrasekhar-mass explosion
Our modeling suggests that the narrow [Ca II] features observed in the nebular spectrum are associated with $^{48}$Ca from electron capture during the explosion, which is expected to occur only in white dwarfs that explode near or at the $M_{\rm Ch}$ limit.
Solar and Stellar Astrophysics High Energy Astrophysical Phenomena
LISA: a MATLAB package for Longitudinal Image Sequence Analysis
Given two contrasting sequences of images, the image processing in LISA starts with selecting a region of interest in two representative images, followed by automatic or manual segmentation and registration.
Understanding and Mitigating the Security Risks of Voice-Controlled Third-Party Skills on Amazon Alexa and Google Home
The significance of our findings have already been acknowledged by Amazon and Google, and further evidenced by the risky skills discovered on Alexa and Google markets by the new detection systems we built.
Cryptography and Security
Invisible Mask: Practical Attacks on Face Recognition with Infrared
We propose a kind of brand new attack against face recognition systems, which is realized by illuminating the subject using infrared according to the adversarial examples worked out by our algorithm, thus face recognition systems can be bypassed or misled while simultaneously the infrared perturbations cannot be observed by raw eyes.
Cryptography and Security
Understanding Membership Inferences on Well-Generalized Learning Models
Membership Inference Attack (MIA) determines the presence of a record in a machine learning model's training data by querying the model.
CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition
For this purpose, we developed novel techniques that address a key technical challenge: integrating the commands into a song in a way that can be effectively recognized by ASR through the air, in the presence of background noise, while not being detected by a human listener.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild
In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild.
Cryptography and Security
Privacy Loss in Apple's Implementation of Differential Privacy on MacOS 10.12
We discover and describe Apple's set-up for differentially private data processing, including the overall data pipeline, the parameters used for differentially private perturbation of each piece of data, and the frequency with which such data is sent to Apple's servers.
Optimizing Filter Size in Convolutional Neural Networks for Facial Action Unit Recognition
Most recently, Convolutional Neural Networks (CNNs) have shown promise for facial AU recognition, where predefined and fixed convolution filter sizes are employed.
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction
Consequently, the adversarial example can be effectively detected by comparing the classification results of a given sample and its denoised version, without referring to any prior knowledge of attacks.
DIMM-SC: A Dirichlet mixture model for clustering droplet-based single cell transcriptomic data
More importantly, as a model-based approach, DIMM-SC is able to quantify the clustering uncertainty for each single cell, facilitating rigorous statistical inference and biological interpretations, which are typically unavailable from existing clustering methods.
Understanding IoT Security Through the Data Crystal Ball: Where We Are Now and Where We Are Going to Be
We systemize this process, by proposing a taxonomy for the IoT ecosystem and organizing IoT security into five problem areas.
Cryptography and Security
