Search Results for author:
Found 7 papers, 4 papers with code
Deep Learning for Frame Error Prediction using a DARPA Spectrum Collaboration Challenge (SC2) Dataset
We demonstrate a first example for employing deep learning in predicting frame errors for a Collaborative Intelligent Radio Network (CIRN) using a dataset collected during participation in the final scrimmages of the DARPA SC2 challenge.
A Study on Transferability of Deep Learning Models for Network Intrusion Detection
In this paper, we explore transferability in learning between different attack classes in a network intrusion detection setup.
Improving Transferability of Network Intrusion Detection in a Federated Learning Setup
Network Intrusion Detection Systems (IDS) aim to detect the presence of an intruder by analyzing network packets arriving at an internet connected device.
A Comprehensive Comparison of Machine Learning Based Methods Used in Bengali Question Classification
QA classification system maps questions asked by humans to an appropriate answer category.
Knowledge Distillation For Wireless Edge Learning
In this paper, we propose a framework for predicting frame errors in the collaborative spectrally congested wireless environments of the DARPA Spectrum Collaboration Challenge (SC2) via a recently collected dataset.
Data-Driven Subsampling in the Presence of an Adversarial Actor
In this paper, we investigate the effects of an adversarial attack on an AMC system that employs deep learning models both for AMC and for subsampling.
Deep OFDM Channel Estimation: Capturing Frequency Recurrence
In this paper, we propose a deep-learning-based channel estimation scheme in an orthogonal frequency division multiplexing (OFDM) system.
