Search Results for author: Safwan Wshah

Found 7 papers, 2 papers with code

Adaptive Agents and Data Quality in Agent-Based Financial Markets

no code implementations27 Nov 2023 Colin M. Van Oort, Ethan Ratliff-Crain, Brian F. Tivnan, Safwan Wshah

As a baseline, we populate ABMMS with simple trading agents and investigate properties of the generated data.

Meta Reinforcement Learning

GeoDTR+: Toward generic cross-view geolocalization via geometric disentanglement

no code implementations18 Aug 2023 Xiaohan Zhang, Xingyu Li, Waqas Sultani, Chen Chen, Safwan Wshah

We attribute this deficiency to the lack of ability to extract the geometric layout of visual features and models' overfitting to low-level details.

Attribute Disentanglement

Cross-view Geo-localization via Learning Disentangled Geometric Layout Correspondence

1 code implementation8 Dec 2022 Xiaohan Zhang, Xingyu Li, Waqas Sultani, Yi Zhou, Safwan Wshah

We attribute this deficiency to the lack of ability to extract the spatial configuration of visual feature layouts and models' overfitting on low-level details from the training set.

Attribute counterfactual

Cross-View Image Sequence Geo-localization

1 code implementation25 Oct 2022 Xiaohan Zhang, Waqas Sultani, Safwan Wshah

In this paper, we present the first cross-view geo-localization method that works on a sequence of limited FOV images.

Visual and Object Geo-localization: A Comprehensive Survey

no code implementations30 Dec 2021 Daniel Wilson, Xiaohan Zhang, Waqas Sultani, Safwan Wshah

The concept of geo-localization refers to the process of determining where on earth some `entity' is located, typically using Global Positioning System (GPS) coordinates.

3D Reconstruction Object

Object Tracking and Geo-localization from Street Images

no code implementations13 Jul 2021 Daniel Wilson, Thayer Alshaabi, Colin Van Oort, Xiaohan Zhang, Jonathan Nelson, Safwan Wshah

Geo-localizing static objects from street images is challenging but also very important for road asset mapping and autonomous driving.

Autonomous Driving Object +1

Identification and Correction of False Data Injection Attacks against AC State Estimation using Deep Learning

no code implementations4 Aug 2020 Fayha ALmutairy, Reem Shadid, Safwan Wshah

recent literature has proposed various detection and identification methods for FDIAs, but few studies have focused on a solution that would prevent such attacks from occurring.

Denoising

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