research
∙
08/10/2023
Aphid Cluster Recognition and Detection in the Wild Using Deep Learning Models
Aphid infestation poses a significant threat to crop production, rural c...
share
research
∙
07/12/2023
A New Dataset and Comparative Study for Aphid Cluster Detection
Aphids are one of the main threats to crops, rural families, and global ...
research
∙
06/07/2023
Check Me If You Can: Detecting ChatGPT-Generated Academic Writing using CheckGPT
With ChatGPT under the spotlight, utilizing large language models (LLMs)...
research
∙
05/26/2023
Gender, Smoking History and Age Prediction from Laryngeal Images
Flexible laryngoscopy is commonly performed by otolaryngologists to dete...
research
∙
12/16/2022
Resource-Interaction Graph: Efficient Graph Representation for Anomaly Detection
Security research has concentrated on converting operating system audit ...
research
∙
05/31/2022
Hide and Seek: on the Stealthiness of Attacks against Deep Learning Systems
With the growing popularity of artificial intelligence and machine learn...
research
∙
01/23/2022
Dynamic Label Assignment for Object Detection by Combining Predicted and Anchor IoUs
Label assignment plays a significant role in modern object detection mod...
research
∙
12/25/2021
Semantic Clustering based Deduction Learning for Image Recognition and Classification
The paper proposes a semantic clustering based deduction learning by mim...
research
∙
09/25/2021
Two Souls in an Adversarial Image: Towards Universal Adversarial Example Detection using Multi-view Inconsistency
In the evasion attacks against deep neural networks (DNN), the attacker ...
research
∙
09/21/2020
DeepDyve: Dynamic Verification for Deep Neural Networks
Deep neural networks (DNNs) have become one of the enabling technologies...
research
∙
04/07/2020
CSRN: Collaborative Sequential Recommendation Networks for News Retrieval
Nowadays, news apps have taken over the popularity of paper-based media,...
research
∙
12/05/2019
Region-Wise Attack: On Efficient Generation of Robust Physical Adversarial Examples
Deep neural networks (DNNs) are shown to be susceptible to adversarial e...
research
∙
11/23/2019
On Functional Test Generation for Deep Neural Network IPs
Machine learning systems based on deep neural networks (DNNs) produce st...
research
∙
12/06/2018
On Configurable Defense against Adversarial Example Attacks
Machine learning systems based on deep neural networks (DNNs) have gaine...
research
∙
03/05/2018
I Know What You See: Power Side-Channel Attack on Convolutional Neural Network Accelerators
Deep learning has become the de-facto computational paradigm for various...
research
∙
01/15/2018