A systematic survey of control techniques and applications in connected and automated vehicles
Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
Unleashing the power of self-supervised image denoising: A comprehensive review
The advent of deep learning has brought a revolutionary transformation to image denoising
techniques. However, the persistent challenge of acquiring noise-clean pairs for supervised …
techniques. However, the persistent challenge of acquiring noise-clean pairs for supervised …
[PDF][PDF] Neural Network Architectures in Cybersecurity: Optimizing Anomaly Detection and Prevention
BR Maddireddy, BR Maddireddy - International Journal of Advanced …, 2024 - ijaeti.com
Neural networks have emerged as powerful tools in cybersecurity, offering advanced
capabilitiesfor anomaly detection and prevention in complex and dynamic network …
capabilitiesfor anomaly detection and prevention in complex and dynamic network …
Multi-task hierarchical adversarial inverse reinforcement learning
Abstract Multi-task Imitation Learning (MIL) aims to train a policy capable of performing a
distribution of tasks based on multi-task expert demonstrations, which is essential for …
distribution of tasks based on multi-task expert demonstrations, which is essential for …
A multisource data approach for estimating vehicle queue length at metered on-ramps
Queue length information is a critical input for ramp metering management. Based on
accurate and reliable queue length, the inflow rate can be optimized to maximize the benefit …
accurate and reliable queue length, the inflow rate can be optimized to maximize the benefit …
An automatic classifier for monitoring applied behaviors of cage-free laying hens with deep learning
Poultry behavior is an important indicator of their welfare, health, and production
performance. The welfare of layers and broilers such as walking ability, breast blisters, hock …
performance. The welfare of layers and broilers such as walking ability, breast blisters, hock …
Every parameter matters: Ensuring the convergence of federated learning with dynamic heterogeneous models reduction
H Zhou, T Lan, GP Venkataramani… - Advances in Neural …, 2024 - proceedings.neurips.cc
Abstract Cross-device Federated Learning (FL) faces significant challenges where low-end
clients that could potentially make unique contributions are excluded from training large …
clients that could potentially make unique contributions are excluded from training large …
High dynamic range imaging with context-aware transformer
F Zhou, Z Fu, D Zhang - 2023 International Joint Conference on …, 2023 - ieeexplore.ieee.org
Avoiding the introduction of ghosts when synthesising LDR images as high dynamic range
(HDR) images is a challenging task. Convolutional neural networks (CNNs) are effective for …
(HDR) images is a challenging task. Convolutional neural networks (CNNs) are effective for …
Serverless federated auprc optimization for multi-party collaborative imbalanced data mining
To address the big data challenges, serverless multi-party collaborative training has recently
attracted attention in the data mining community, since they can cut down the …
attracted attention in the data mining community, since they can cut down the …
Trep: Transformer-based evidential prediction for pedestrian intention with uncertainty
With rapid development in hardware (sensors and processors) and AI algorithms, automated
driving techniques have entered the public's daily life and achieved great success in …
driving techniques have entered the public's daily life and achieved great success in …