Ghazal Farhani
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View article: 3D Roadway Scene Object Detection with LiDARs in Snowfall Conditions
3D Roadway Scene Object Detection with LiDARs in Snowfall Conditions Open
Because 3D structure of a roadway environment can be characterized directly by a Light Detection and Ranging (LiDAR) sensors, they can be used to obtain exceptional situational awareness for assitive and autonomous driving systems. Althoug…
View article: Enhancing Semantic Clarity: Discriminative and Fine-grained Information Mining for Remote Sensing Image-Text Retrieval
Enhancing Semantic Clarity: Discriminative and Fine-grained Information Mining for Remote Sensing Image-Text Retrieval Open
Remote sensing image-text retrieval is a fundamental task in remote sensing multimodal analysis, promoting the alignment of visual and language representations. The mainstream approaches commonly focus on capturing shared semantic represen…
View article: Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations
Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations Open
The residual loss in Physics-Informed Neural Networks (PINNs) alters the simple recursive relation of layers in a feed-forward neural network by applying a differential operator, resulting in a loss landscape that is inherently different f…
View article: Unlocking Dual Utility: 1D-CNN for Milling Tool Health Assessment and Experimental Optimization
Unlocking Dual Utility: 1D-CNN for Milling Tool Health Assessment and Experimental Optimization Open
In a novel application of 1D Convolutional Neural Networks (1D-CNN), this study pioneers a tri-class classification framework for accurately forecasting the Remaining Useful Life (RUL) of milling tools. By harnessing the 1D-CNN’s innate ca…
View article: A Clustering Approach for Remotely Sensed Data in the Western United States
A Clustering Approach for Remotely Sensed Data in the Western United States Open
The increasing frequency and scale of wildfires carry significant ecological, socioeconomic, and environmental implications, prompting the need for a deeper grasp of wildfire characteristics. Essential meteorological factors like temperatu…
View article: A Bayesian Neural Network Approach for Tropospheric Temperature Retrievals from a Lidar Instrument
A Bayesian Neural Network Approach for Tropospheric Temperature Retrievals from a Lidar Instrument Open
We have constructed a Bayesian neural network able of retrieving tropospheric temperature profiles from rotational Raman-scatter measurements of nitrogen and oxygen and applied it to measurements taken by the RAman Lidar for Meteorological…
View article: Using Deep Learning for Task and Tremor Type Classification in People with Parkinson’s Disease
Using Deep Learning for Task and Tremor Type Classification in People with Parkinson’s Disease Open
Hand tremor is one of the dominating symptoms of Parkinson’s disease (PD), which significantly limits activities of daily living. Along with medications, wearable devices have been proposed to suppress tremor. However, suppressing tremor w…
View article: Momentum Diminishes the Effect of Spectral Bias in Physics-Informed Neural Networks
Momentum Diminishes the Effect of Spectral Bias in Physics-Informed Neural Networks Open
Physics-informed neural network (PINN) algorithms have shown promising results in solving a wide range of problems involving partial differential equations (PDEs). However, they often fail to converge to desirable solutions when the target…
View article: Updated Climatology of Mesospheric Temperature Inversions Detected by Rayleigh Lidar above Observatoire de Haute Provence, France, Using a K-Mean Clustering Technique
Updated Climatology of Mesospheric Temperature Inversions Detected by Rayleigh Lidar above Observatoire de Haute Provence, France, Using a K-Mean Clustering Technique Open
A climatology of Mesospheric Inversion Layers (MIL) has been created using the Rayleigh lidar located in the south of France at L’Observatoire de Haute Provence (OHP). Using criteria based on lidar measurement uncertainties and climatologi…
View article: Implementing Machine Learning Algorithms to Classify Postures and Forecast Motions When Using a Dynamic Chair
Implementing Machine Learning Algorithms to Classify Postures and Forecast Motions When Using a Dynamic Chair Open
Many modern jobs require long periods of sitting on a chair that may result in serious health complications. Dynamic chairs are proposed as alternatives to the traditional sitting chairs; however, previous studies have suggested that most …
View article: Classification of lidar measurements using supervised and unsupervised machine learning methods
Classification of lidar measurements using supervised and unsupervised machine learning methods Open
While it is relatively straightforward to automate the processing of lidar signals, it is more difficult to choose periods of “good” measurements to process. Groups use various ad hoc procedures involving either very simple (e.g. signal-to…
View article: Classification of Lidar Measurements Using Supervised and Unsupervised Machine Learning Methods
Classification of Lidar Measurements Using Supervised and Unsupervised Machine Learning Methods Open
While it is relatively straightforward to automate the processing of lidar signals, it is more difficult to choose periods of "good" measurements to process. Groups use various ad hoc procedures involving either very simple (e.g. signal-to…
View article: Optimal estimation method retrievals of stratospheric ozone profiles from a DIAL
Optimal estimation method retrievals of stratospheric ozone profiles from a DIAL Open
This paper provides a detailed description of a first-principle optimal estimation method (OEM) applied to ozone retrieval analysis using differential absorption lidar (DIAL) measurements. The air density, detector dead times, background c…
View article: Improved ozone DIAL retrievals in the upper troposphere and lower stratosphere using an optimal estimation method
Improved ozone DIAL retrievals in the upper troposphere and lower stratosphere using an optimal estimation method Open
We have implemented a first-principle optimal estimation method to retrieve ozone density profiles using simultaneously tropospheric and stratospheric differential absorption lidar (DIAL) measurements. Our retrieval extends from 2.5 km to …
View article: Optimal Estimation Method Retrievals of Stratospheric OzoneProfiles from a DIAL Lidar
Optimal Estimation Method Retrievals of Stratospheric OzoneProfiles from a DIAL Lidar Open
This paper provides a detailed description of the first principle Optimal Estimation Method (OEM) which is applied to ozone retrieval analysis using Differential Absorption Lidar (DIAL) measurements. The air density, detector dead times, b…
View article: Stratospheric Ozone Density Retrieval Using the Optimal Estimation Method (OEM)
Stratospheric Ozone Density Retrieval Using the Optimal Estimation Method (OEM) Open
We use an Optimal Estimation Method (OEM) to retrieve ozone profiles from the CANDAC Stratospheric Ozone Differential Absorption Lidar in Eureka, Canada. The OEM is a well known inverse method in which a forward model (FM) is used to descr…
View article: How to apply the optimal estimation method to your lidar measurements for improved retrievals of temperature and composition
How to apply the optimal estimation method to your lidar measurements for improved retrievals of temperature and composition Open
The optimal estimation method (OEM) has a long history of use in passive remote sensing, but has only recently been applied to active instruments like lidar. The OEM’s advantage over traditional techniques includes obtaining a full systema…
View article: Improved techniques for atmospheric ozone retrievals from lidar measurements using the Optimal Estimation Method and Machine Learning
Improved techniques for atmospheric ozone retrievals from lidar measurements using the Optimal Estimation Method and Machine Learning Open
A new first-principle Optimal Estimation Method (OEM) to retrieve ozone number density profiles in both the troposphere and stratosphere using Differential Absorption Lidar (DIAL) measurements obtained at the Observatoire de Haute Provence…