Search Results for author: Erik Blasch

Found 20 papers, 2 papers with code

DeFakePro: Decentralized DeepFake Attacks Detection using ENF Authentication

no code implementations22 Jul 2022 Deeraj Nagothu, Ronghua Xu, Yu Chen, Erik Blasch, Alexander Aved

The similarity in ENF signal fluctuations is utilized in the PoENF algorithm to authenticate the media broadcasted in conferencing tools.

DeepFake Detection Face Swapping

Automatic Concept Extraction for Concept Bottleneck-based Video Classification

no code implementations21 Jun 2022 Jeya Vikranth Jeyakumar, Luke Dickens, Luis Garcia, Yu-Hsi Cheng, Diego Ramirez Echavarria, Joseph Noor, Alessandra Russo, Lance Kaplan, Erik Blasch, Mani Srivastava

CoDEx identifies a rich set of complex concept abstractions from natural language explanations of videos-obviating the need to predefine the amorphous set of concepts.

Classification Video Classification

AAAI FSS-21: Artificial Intelligence in Government and Public Sector Proceedings

no code implementations10 Dec 2021 Mihai Boicu, Erik Blasch, Alun Preece

Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Government and Public Sector, Washington, DC, USA, November 4-6, 2021

Certifiable Artificial Intelligence Through Data Fusion

no code implementations3 Nov 2021 Erik Blasch, Junchi Bin, Zheng Liu

This paper reviews and proposes concerns in adopting, fielding, and maintaining artificial intelligence (AI) systems.

Object Recognition

The Powerful Use of AI in the Energy Sector: Intelligent Forecasting

no code implementations3 Nov 2021 Erik Blasch, Haoran Li, Zhihao Ma, Yang Weng

To meet society requirements, this paper proposes a methodology to develop, deploy, and evaluate AI systems in the energy sector by: (1) understanding the power system measurements with physics, (2) designing AI algorithms to forecast the need, (3) developing robust and accountable AI methods, and (4) creating reliable measures to evaluate the performance of the AI model.

Dimensionality Reduction

Adversarial twin neural networks: maximizing physics recovery for physical system

no code implementations29 Sep 2021 Haoran Li, Erik Blasch, Jingyi Yuan, Yang Weng

Thus, we propose (1) sparsity regularization for the physical model and (2) physical superiority over the virtual model.

WHAT TO DO IF SPARSE REPRESENTATION LEARNING FAILS UNEXPECTEDLY?

no code implementations29 Sep 2021 Jingyi Yuan, Haoran Li, Erik Blasch, Yang Weng

RISE is based on a complete analysis for the generalizability of data properties for physical systems.

Active Learning Representation Learning

UAV-Assisted Communication in Remote Disaster Areas using Imitation Learning

no code implementations2 Apr 2021 Alireza Shamsoshoara, Fatemeh Afghah, Erik Blasch, Jonathan Ashdown, Mehdi Bennis

The damage to cellular towers during natural and man-made disasters can disturb the communication services for cellular users.

Imitation Learning

Multisource AI Scorecard Table for System Evaluation

no code implementations8 Feb 2021 Erik Blasch, James Sung, Tao Nguyen

The paper describes a Multisource AI Scorecard Table (MAST) that provides the developer and user of an artificial intelligence (AI)/machine learning (ML) system with a standard checklist focused on the principles of good analysis adopted by the intelligence community (IC) to help promote the development of more understandable systems and engender trust in AI outputs.

Aerial Imagery Pile burn detection using Deep Learning: the FLAME dataset

1 code implementation28 Dec 2020 Alireza Shamsoshoara, Fatemeh Afghah, Abolfazl Razi, Liming Zheng, Peter Z Fulé, Erik Blasch

FLAME (Fire Luminosity Airborne-based Machine learning Evaluation) offers a dataset of aerial images of fires along with methods for fire detection and segmentation which can help firefighters and researchers to develop optimal fire management strategies.

BIG-bench Machine Learning Fire Detection +1

I-ViSE: Interactive Video Surveillance as an Edge Service using Unsupervised Feature Queries

no code implementations9 Mar 2020 Seyed Yahya Nikouei, Yu Chen, Alexander Aved, Erik Blasch

Adopting unsupervised methods that do not reveal any private information, the I-ViSE scheme utilizes general features of a human body and color of clothes.

Face Recognition Scene Recognition

Artificial Intelligence Strategies for National Security and Safety Standards

no code implementations3 Nov 2019 Erik Blasch, James Sung, Tao Nguyen, Chandra P. Daniel, Alisa P. Mason

Recent advances in artificial intelligence (AI) have lead to an explosion of multimedia applications (e. g., computer vision (CV) and natural language processing (NLP)) for different domains such as commercial, industrial, and intelligence.

Microchain: A Hybrid Consensus Mechanism for Lightweight Distributed Ledger for IoT

no code implementations24 Sep 2019 Ronghua Xu, Yu Chen, Erik Blasch, Genshe Chen

In this paper, Microchain, based on a hybrid Proof-of-Credit (PoC)-Voting-based Chain Finality (VCF) consensus protocol, is proposed to provide a secure, scalable and lightweight distributed ledger for IoT systems.

Distributed, Parallel, and Cluster Computing

I-SAFE: Instant Suspicious Activity identiFication at the Edge using Fuzzy Decision Making

no code implementations12 Sep 2019 Seyed Yahya Nikouei, Yu Chen, Alexander Aved, Erik Blasch, Timothy R. Faughnan

This paper presents a forensic surveillance strategy by introducing an Instant Suspicious Activity identiFication at the Edge (I-SAFE) using fuzzy decision making.

Decision Making Edge-computing

Clustered Object Detection in Aerial Images

1 code implementation ICCV 2019 Fan Yang, Heng Fan, Peng Chu, Erik Blasch, Haibin Ling

The key components in ClusDet include a cluster proposal sub-network (CPNet), a scale estimation sub-network (ScaleNet), and a dedicated detection network (DetecNet).

object-detection Object Detection In Aerial Images

IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation

no code implementations25 Jun 2018 Shuo Liu, Vijay John, Erik Blasch, Zheng Liu, Ying Huang

Context enhancement is critical for night vision (NV) applications, especially for the dark night situation without any artificial lights.

Translation

A Federated Capability-based Access Control Mechanism for Internet of Things (IoTs)

no code implementations1 May 2018 Ronghua Xu, Yu Chen, Erik Blasch, Genshe Chen

Implemented and tested on both resources-constrained devices, like smart sensors and Raspberry PI, and non-resource-constrained devices, like laptops and smart phones, our experimental results demonstrate the feasibility of the proposed FedCAC approach to offer a scalable, lightweight and fine-grained access control solution to IoT systems connected to a system network.

Networking and Internet Architecture

BlendCAC: A BLockchain-ENabled Decentralized Capability-based Access Control for IoTs

no code implementations24 Apr 2018 Ronghua Xu, Yu Chen, Erik Blasch, Genshe Chen

The BlendCAC aims at an effective access control processes to devices, services and information in large scale IoT systems.

Networking and Internet Architecture Cryptography and Security Distributed, Parallel, and Cluster Computing

A Comparative Study of Object Trackers for Infrared Flying Bird Tracking

no code implementations18 Jan 2016 Ying Huang, Hong Zheng, Haibin Ling, Erik Blasch, Hao Yang

Bird strikes present a huge risk for aircraft, especially since traditional airport bird surveillance is mainly dependent on inefficient human observation.

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