Soodeh Nikan
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View article: TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving
TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Open
Vision Language Models (VLMs) employed for visual question-answering (VQA) in autonomous driving often require substantial computational resources that pose a challenge for their deployment in resource-constrained vehicles. To address this…
View article: TS-VLM: Text-Guided SoftSort Pooling for Vision-Language Models in Multi-View Driving Reasoning
TS-VLM: Text-Guided SoftSort Pooling for Vision-Language Models in Multi-View Driving Reasoning Open
Vision-Language Models (VLMs) have shown remarkable potential in advancing autonomous driving by leveraging multi-modal fusion in order to enhance scene perception, reasoning, and decision-making. Despite their potential, existing models s…
View article: From blender to farm: Transforming controlled environment agriculture with synthetic data and SwinUNet for precision crop monitoring
From blender to farm: Transforming controlled environment agriculture with synthetic data and SwinUNet for precision crop monitoring Open
The aim of this study was to train a Vision Transformer (ViT) model for semantic segmentation to differentiate between ripe and unripe strawberries using synthetic data to avoid challenges with conventional data collection methods. The sol…
View article: Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure
Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure Open
With the growing need for real-time processing on IoT devices, optimizing machine learning (ML) models' size, latency, and computational efficiency is essential. This paper investigates a pruning method for anomaly detection in resource-co…
View article: Traffic navigation via reinforcement learning with episodic-guided prioritized experience replay
Traffic navigation via reinforcement learning with episodic-guided prioritized experience replay Open
Deep Reinforcement Learning (DRL) models play a fundamental role in autonomous driving applications; however, they typically suffer from sample inefficiency because they often require many interactions with the environment to learn effecti…
View article: Optimizing Strawberry Disease and Quality Detection with Vision Transformers and Attention-Based Convolutional Neural Networks
Optimizing Strawberry Disease and Quality Detection with Vision Transformers and Attention-Based Convolutional Neural Networks Open
Machine learning and computer vision have proven to be valuable tools for farmers to streamline their resource utilization to lead to more sustainable and efficient agricultural production. These techniques have been applied to strawberry …
View article: Classification Of Strawberry Diseases and Quality Using Different Machine Learning Methods
Classification Of Strawberry Diseases and Quality Using Different Machine Learning Methods Open
Machine learning and computer vision have proven to be valuable tools for farmers to streamline their resource utilization to lead to more sustainable and efficient agricultural production. These techniques have been applied to strawberry …
View article: Efficient Transformer-based Hyper-parameter Optimization for Resource-constrained IoT Environments
Efficient Transformer-based Hyper-parameter Optimization for Resource-constrained IoT Environments Open
The hyper-parameter optimization (HPO) process is imperative for finding the best-performing Convolutional Neural Networks (CNNs). The automation process of HPO is characterized by its sizable computational footprint and its lack of transp…
View article: Navigating the Handover: Reviewing Takeover Requests in Level 3 Autonomous Vehicles
Navigating the Handover: Reviewing Takeover Requests in Level 3 Autonomous Vehicles Open
Autonomous vehicles (AVs) represent a transformative advance in automotive technology, promising increased safety and efficiency by reducing human error. However, integrating human factors remains a critical challenge, especially during ta…
View article: Robust Multiview Multimodal Driver Monitoring System Using Masked Multi-Head Self-Attention
Robust Multiview Multimodal Driver Monitoring System Using Masked Multi-Head Self-Attention Open
Driver Monitoring Systems (DMSs) are crucial for safe hand-over actions in Level-2+ self-driving vehicles. State-of-the-art DMSs leverage multiple sensors mounted at different locations to monitor the driver and the vehicle's interior scen…
View article: An Explainable Attention Zone Estimation for Level 3 Autonomous Driving
An Explainable Attention Zone Estimation for Level 3 Autonomous Driving Open
Accurately assessing the driver’s situational awareness is crucial in level 3 () autonomous driving, where the driver is in the loop. Estimating the attention zone provides essential information about the drivers’ on/off-road visual attent…
View article: Real-Time Driver Monitoring Systems through Modality and View Analysis
Real-Time Driver Monitoring Systems through Modality and View Analysis Open
Driver distractions are known to be the dominant cause of road accidents. While monitoring systems can detect non-driving-related activities and facilitate reducing the risks, they must be accurate and efficient to be applicable. Unfortuna…
View article: Resource Utilization and Costs of Managing Patients with Advanced Melanoma: A Canadian Population-Based Study
Resource Utilization and Costs of Managing Patients with Advanced Melanoma: A Canadian Population-Based Study Open
Background: The use and detailed costs of services provided for people with advanced melanoma (aMEL) are not well known. We conducted an analysis to determine the use of health care services and the associated costs delineated by relevant …
View article: Performance Evaluation of Different Feature Extractors and Classifiers for Recognition of Human Faces with Low Resolution Images
Performance Evaluation of Different Feature Extractors and Classifiers for Recognition of Human Faces with Low Resolution Images Open
Face recognition is an effective biometric identification technique used in many applications such as law enforcement, document validation and video surveillance. In this paper the effect of low resolution images which are captured in real…