Search Results for author:
Found 25 papers, 6 papers with code
Enhanced Cooperative Perception for Autonomous Vehicles Using Imperfect Communication
To validate our approach, we used the CARLA simulator to create a dataset of annotated videos for different driving scenarios where pedestrian detection is challenging for an AV with compromised vision.
VisionGPT: LLM-Assisted Real-Time Anomaly Detection for Safe Visual Navigation
This paper explores the potential of Large Language Models(LLMs) in zero-shot anomaly detection for safe visual navigation.
FLAME Diffuser: Grounded Wildfire Image Synthesis using Mask Guided Diffusion
Thus, our proposed framework can generate a massive dataset of that images are high-quality and ground truth-paired, which well addresses the needs of the annotated datasets in specific tasks.
Opinion Dynamics in Social Multiplex Networks with Mono and Bi-directional Interactions in the Presence of Leaders
We further scrutinize the convergence rates of opinion dynamics in networks with one-way versus two-way interactions.
Driving Towards Inclusion: Revisiting In-Vehicle Interaction in Autonomous Vehicles
This paper presents a comprehensive literature review of the current state of in-vehicle human-computer interaction (HCI) in the context of self-driving vehicles, with a specific focus on inclusion and accessibility.
Enhancing Digital Hologram Reconstruction Using Reverse-Attention Loss for Untrained Physics-Driven Deep Learning Models with Uncertain Distance
Untrained Physics-based Deep Learning (DL) methods for digital holography have gained significant attention due to their benefits, such as not requiring an annotated training dataset, and providing interpretability since utilizing the governing laws of hologram formation.
A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management
Wildfires have emerged as one of the most destructive natural disasters worldwide, causing catastrophic losses in both human lives and forest wildlife.
Quantification of cardiac capillarization in single-immunostained myocardial slices using weakly supervised instance segmentation
Quantitative assessment of cardiac capillarization typically involves double immunostaining of cardiomyocytes (CMs) and capillaries in myocardial slices.
Actuator Trajectory Planning for UAVs with Overhead Manipulator using Reinforcement Learning
In this paper, we investigate the operation of an aerial manipulator system, namely an Unmanned Aerial Vehicle (UAV) equipped with a controllable arm with two degrees of freedom to carry out actuation tasks on the fly.
Obscured Wildfire Flame Detection By Temporal Analysis of Smoke Patterns Captured by Unmanned Aerial Systems
This research paper addresses the challenge of detecting obscured wildfires (when the fire flames are covered by trees, smoke, clouds, and other natural barriers) in real-time using drones equipped only with RGB cameras.
Energy Optimization for HVAC Systems in Multi-VAV Open Offices: A Deep Reinforcement Learning Approach
It takes only a total of 40 minutes for 5 epochs (about 7. 75 minutes per epoch) to train a network with superior performance and covering diverse conditions for its low-complexity architecture; therefore, it easily adapts to changes in the building setups, weather conditions, occupancy rate, etc.
Learning on Bandwidth Constrained Multi-Source Data with MIMO-inspired DPP MAP Inference
A determinant-preserved sparse representation of selected samples is used to perform sample precoding in local sources to be processed by DPP.
RD-DPP: Rate-Distortion Theory Meets Determinantal Point Process to Diversify Learning Data Samples
However, the number of selected samples is restricted to the rank of the kernel matrix implied by the dimensionality of data samples.
Fast Key Points Detection and Matching for Tree-Structured Images
The proposed algorithm is applicable to a variety of tree-structured image matching, but our focus is on dendrites, recently-developed visual identifiers.
DH-GAN: A Physics-driven Untrained Generative Adversarial Network for 3D Microscopic Imaging using Digital Holography
Digital holography is a 3D imaging technique by emitting a laser beam with a plane wavefront to an object and measuring the intensity of the diffracted waveform, called holograms.
Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review
This paper explores Deep Learning (DL) methods that are used or have the potential to be used for traffic video analysis, emphasizing driving safety for both Autonomous Vehicles (AVs) and human-operated vehicles.
Network-level Safety Metrics for Overall Traffic Safety Assessment: A Case Study
To bridge these two perspectives, we define a new set of network-level safety metrics (NSM) to assess the overall safety profile of traffic flow by processing imagery taken by RSU cameras.
Fully-echoed Q-routing with Simulated Annealing Inference for Flying Adhoc Networks
Current networking protocols deem inefficient in accommodating the two key challenges of Unmanned Aerial Vehicle (UAV) networks, namely the network connectivity loss and energy limitations.
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.
Towards Boosting the Channel Attention in Real Image Denoising : Sub-band Pyramid Attention
We equip the SPA blocks on a network designed for real image denoising.
Deep DIH : Statistically Inferred Reconstruction of Digital In-Line Holography by Deep Learning
Recently, end-to-end deep learning-based methods have been utilized to reconstruct the object wavefront (as a surrogate for the 3D structure of the object) directly from a single-shot in-line digital hologram.
An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations
This paper studies the problem of spectrum shortage in an unmanned aerial vehicle (UAV) network during critical missions such as wildfire monitoring, search and rescue, and disaster monitoring.
A Solution for Dynamic Spectrum Management in Mission-Critical UAV Networks
In this paper, we study the problem of spectrum scarcity in a network of unmanned aerial vehicles (UAVs) during mission-critical applications such as disaster monitoring and public safety missions, where the pre-allocated spectrum is not sufficient to offer a high data transmission rate for real-time video-streaming.
A Unified Framework for Joint Mobility Prediction and Object Profiling of Drones in UAV Networks
In recent years, using a network of autonomous and cooperative unmanned aerial vehicles (UAVs) without command and communication from the ground station has become more imperative, in particular in search-and-rescue operations, disaster management, and other applications where human intervention is limited.
A Shapley Value Solution to Game Theoretic-based Feature Reduction in False Alarm Detection
False alarm is one of the main concerns in intensive care units and can result in care disruption, sleep deprivation, and insensitivity of care-givers to alarms.
