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Found 13 papers, 2 papers with code
TinyVQA: Compact Multimodal Deep Neural Network for Visual Question Answering on Resource-Constrained Devices
Traditional machine learning models often require powerful hardware, making them unsuitable for deployment on resource-limited devices.
Mixed Precision Quantization to Tackle Gradient Leakage Attacks in Federated Learning
We empirically proved the validity of our method with three benchmark datasets and found a minimal accuracy drop in the global model after applying quantization.
An Edge-Cloud Integrated Framework for Flexible and Dynamic Stream Analytics
In this paper, we study how to best leverage edge and cloud resources to achieve better accuracy and latency for stream analytics using a type of RNN model called long short-term memory (LSTM).
TinyM$^2$Net: A Flexible System Algorithm Co-designed Multimodal Learning Framework for Tiny Devices
With the emergence of Artificial Intelligence (AI), new attention has been given to implement AI algorithms on resource constrained tiny devices to expand the application domain of IoT.
Reproducible and Portable Big Data Analytics in the Cloud
To tackle these problems, we leverage serverless computing and containerization techniques for automated scalable execution and reproducibility, and utilize the adapter design pattern to enable application portability and reproducibility across different clouds.
CCS-GAN: COVID-19 CT-scan classification with very few positive training images
CCS-GAN achieves high accuracy with few positive images and thereby greatly reduces the barrier of acquiring large training volumes in order to train a diagnostic classifier for COVID-19.
Toward Generating Synthetic CT Volumes using a 3D-Conditional Generative Adversarial Network
We present a novel conditional Generative Adversarial Network (cGAN) architecture that is capable of generating 3D Computed Tomography scans in voxels from noisy and/or pixelated approximations and with the potential to generate full synthetic 3D scan volumes.
Generating Realistic COVID19 X-rays with a Mean Teacher + Transfer Learning GAN
We present a novel Mean Teacher + Transfer GAN (MTT-GAN) that generates COVID19 chest X-ray images of high quality.
AutoCogniSys: IoT Assisted Context-Aware Automatic Cognitive Health Assessment
Cognitive impairment has become epidemic in older adult population.
Localized Flood DetectionWith Minimal Labeled Social Media Data Using Transfer Learning
We investigate the problem of localized flood detection using the social sensing model (Twitter) in order to provide an efficient, reliable and accurate flood text classification model with minimal labeled data.
FLATM: A Fuzzy Logic Approach Topic Model for Medical Documents
One of the challenges for text analysis in medical domains is analyzing large-scale medical documents.
Fuzzy Approach Topic Discovery in Health and Medical Corpora
The majority of medical documents and electronic health records (EHRs) are in text format that poses a challenge for data processing and finding relevant documents.
