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Found 25 papers, 4 papers with code
Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits
We consider the problem of late multi-modal fusion for discriminative learning.
Image Prior and Posterior Conditional Probability Representation for Efficient Damage Assessment
It is important to quantify Damage Assessment (DA) for Human Assistance and Disaster Response (HADR) applications.
Electric Vehicle Aggregation Review: Benefits and Vulnerabilities of Managing a Growing EV Fleet
Electric vehicles (EVs) are becoming more popular within the United States, making up an increasingly large portion of the US's electricity consumption.
Transparent Object Tracking with Enhanced Fusion Module
However, with the existing fusion techniques, the addition of new features causes a change in the latent space making it impossible to incorporate transparency awareness on trackers with fixed latent spaces.
CCTV-Gun: Benchmarking Handgun Detection in CCTV Images
In this paper, we present a meticulously crafted and annotated benchmark, called \textbf{CCTV-Gun}, which addresses the challenges of detecting handguns in real-world CCTV images.
DeFakePro: Decentralized DeepFake Attacks Detection using ENF Authentication
The similarity in ENF signal fluctuations is utilized in the PoENF algorithm to authenticate the media broadcasted in conferencing tools.
Automatic Concept Extraction for Concept Bottleneck-based Video Classification
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.
AAAI FSS-21: Artificial Intelligence in Government and Public Sector Proceedings
Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Government and Public Sector, Washington, DC, USA, November 4-6, 2021
The Powerful Use of AI in the Energy Sector: Intelligent Forecasting
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.
Certifiable Artificial Intelligence Through Data Fusion
This paper reviews and proposes concerns in adopting, fielding, and maintaining artificial intelligence (AI) systems.
NIDA-CLIFGAN: Natural Infrastructure Damage Assessment through Efficient Classification Combining Contrastive Learning, Information Fusion and Generative Adversarial Networks
During natural disasters, aircraft and satellites are used to survey the impacted regions.
Adversarial twin neural networks: maximizing physics recovery for physical system
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?
RISE is based on a complete analysis for the generalizability of data properties for physical systems.
UAV-Assisted Communication in Remote Disaster Areas using Imitation Learning
The damage to cellular towers during natural and man-made disasters can disturb the communication services for cellular users.
Multisource AI Scorecard Table for System Evaluation
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
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.
I-ViSE: Interactive Video Surveillance as an Edge Service using Unsupervised Feature Queries
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.
Artificial Intelligence Strategies for National Security and Safety Standards
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
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
This paper presents a forensic surveillance strategy by introducing an Instant Suspicious Activity identiFication at the Edge (I-SAFE) using fuzzy decision making.
Clustered Object Detection in Aerial Images
The key components in ClusDet include a cluster proposal sub-network (CPNet), a scale estimation sub-network (ScaleNet), and a dedicated detection network (DetecNet).
IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation
Context enhancement is critical for night vision (NV) applications, especially for the dark night situation without any artificial lights.
A Federated Capability-based Access Control Mechanism for Internet of Things (IoTs)
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
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
Bird strikes present a huge risk for aircraft, especially since traditional airport bird surveillance is mainly dependent on inefficient human observation.
