Search Results for author:
Found 12 papers, 4 papers with code
An Integrated AI-Enabled System Using One Class Twin Cross Learning (OCT-X) for Early Gastric Cancer Detection
Early detection of gastric cancer, a leading cause of cancer-related mortality worldwide, remains hampered by the limitations of current diagnostic technologies, leading to high rates of misdiagnosis and missed diagnoses.
Enhancing Diagnostic Precision in Gastric Bleeding through Automated Lesion Segmentation: A Deep DuS-KFCM Approach
Timely and precise classification and segmentation of gastric bleeding in endoscopic imagery are pivotal for the rapid diagnosis and intervention of gastric complications, which is critical in life-saving medical procedures.
MsMemoryGAN: A Multi-scale Memory GAN for Palm-vein Adversarial Purification
At the testing stage, given an adversarial sample, the MsMemoryGAN retrieves its most relevant normal patterns in memory for the reconstruction.
Leveraging Foundation Models for Zero-Shot IoT Sensing
To address this, zero-shot learning (ZSL) aims to classify data of unseen classes with the help of semantic information.
A First Physical-World Trajectory Prediction Attack via LiDAR-induced Deceptions in Autonomous Driving
To the best of our knowledge, this study is the first security analysis spanning from LiDAR-based perception to prediction in autonomous driving, leading to a realistic attack on prediction.
Instant Answering in E-Commerce Buyer-Seller Messaging using Message-to-Question Reformulation
E-commerce customers frequently seek detailed product information for purchase decisions, commonly contacting sellers directly with extended queries.
EmMixformer: Mix transformer for eye movement recognition
To this end, we propose a mixed block consisting of three modules, transformer, attention Long short-term memory (attention LSTM), and Fourier transformer.
Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving
Multi-modal fusion has shown initial promising results for object detection of autonomous driving perception.
PriMask: Cascadable and Collusion-Resilient Data Masking for Mobile Cloud Inference
This paper presents the design of a system called PriMask, in which the mobile device uses a secret small-scale neural network called MaskNet to mask the data before transmission.
Indoor Smartphone SLAM with Learned Echoic Location Features
Indoor self-localization is a highly demanded system function for smartphones.
Sardino: Ultra-Fast Dynamic Ensemble for Secure Visual Sensing at Mobile Edge
This paper presents extensive evaluation of Sardino's performance in counteracting adversarial examples and applies it to build a real-time car-borne traffic sign recognition system.
Moving Target Defense for Deep Visual Sensing against Adversarial Examples
Specifically, once the attackers obtain the deep model, they can construct adversarial examples to mislead the model to yield wrong classification results.
