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Exploring Permission-Induced Risk in Android Applications for Malicious Application Detection
TLDR
We explore the permission-induced risk in Android apps on three levels in a systematic manner. Expand
Exploring Pre-trained Language Models for Event Extraction and Generation
TLDR
This paper proposes a framework based on pre-trained language models, which includes an event extraction model as our baseline and a labeled event generation method. Expand
A mobile recommendation system based on logistic regression and Gradient Boosting Decision Trees
TLDR
In this paper, we present a fused model based on the LR algorithm and the GBDT algorithm to recommend vertical industry commodities in a mobile setting. Expand
Resource allocation with multi-factor node ranking in data center networks
TLDR
We consider the hops of the substrate paths in the node mapping stage. Expand
Mixup-Based Acoustic Scene Classification Using Multi-Channel Convolutional Neural Network
TLDR
We present a multi-channel convolutional neural network-based method for the multi-class acoustic scene classification task. Expand
An Adversarial Feature Distillation Method for Audio Classification
TLDR
We proposed a distillation method which transfers knowledge from well-trained networks to a small network, and the method can compress model size while improving audio classification precision. Expand
A Quantitative Analysis Platform for PD-L1 Immunohistochemistry based on Point-level Supervision Model
TLDR
In this paper, we describe the development of a platform for PD-L1 pathological image quantitative analysis using deep learning approaches. Expand
Deep Convolutional Neural Network-Based Early Automated Detection of Diabetic Retinopathy Using Fundus Image
TLDR
In this paper, we explored the use of deep convolutional neural network methodology for the automatic classification of diabetic retinopathy using color fundus image, and obtained an accuracy of 94.5% on our dataset. Expand
Sample Dropout for Audio Scene Classification Using Multi-Scale Dense Connected Convolutional Neural Network
TLDR
We explore the use of multi-scale Dense connected convolutional neural network (DenseNet) for the classification task, with the goal to improve the classification performance as multi- scale features can be extracted from the time-frequency representation of the audio signal. Expand
Multistructure-Based Collaborative Online Distillation
TLDR
We propose a cross-architecture online-distillation approach to solve this problem by transmitting supplementary information on different networks. Expand
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