Bandit-based data poisoning attack against federated learning for autonomous driving models
Abstract In Internet of Things (IoT) applications, federated learning is commonly used for
distributedly training models in a privacy-preserving manner. Recently, federated learning is …
distributedly training models in a privacy-preserving manner. Recently, federated learning is …
LACTA: A lightweight and accurate algorithm for cherry tomato detection in unstructured environments
Developing cherry tomato detection algorithms for selective harvesting robots faces many
challenges due to the influence of various environmental factors such as lighting, water mist …
challenges due to the influence of various environmental factors such as lighting, water mist …
Dynamic analysis of emergency evacuation in a rolling passenger ship using a two-layer social force model
It is vital to effectively quantify the human movement parameters in rolling ships to save lives
in maritime emergency and/or accidents. This study aims to develop a new two-layer social …
in maritime emergency and/or accidents. This study aims to develop a new two-layer social …
[HTML][HTML] Deep transfer learning enabled intelligent object detection for crowd density analysis on video surveillance systems
Object detection is a computer vision based technique which is used to detect instances of
semantic objects of a particular class in digital images and videos. Crowd density analysis is …
semantic objects of a particular class in digital images and videos. Crowd density analysis is …
Fusion attention mechanism bidirectional LSTM for short-term traffic flow prediction
Z Li, H Xu, X Gao, Z Wang, W Xu - Journal of Intelligent …, 2022 - Taylor & Francis
Short term forecasting is essential and challenging in time series data analysis for traffic flow
research. A novel deep learning architecture on short-term traffic flow prediction was …
research. A novel deep learning architecture on short-term traffic flow prediction was …
[HTML][HTML] Enhanced open biomass burning detection: The BranTNet approach using UAV aerial imagery and deep learning for environmental protection and health …
Open biomass burning (OBB) in agriculture presents a significant and well-documented
challenge, posing severe consequences for both environmental and human health. OBB …
challenge, posing severe consequences for both environmental and human health. OBB …
Surface stress monitoring of laser shock peening using AE time-scale texture image and multi-scale blueprint separable convolutional networks with attention …
The quality monitoring of the laser shock peening (LSP) process is of great significance for
improving the intelligence of precision manufacturing. At present, the monitoring method …
improving the intelligence of precision manufacturing. At present, the monitoring method …
[HTML][HTML] Image patch-based deep learning approach for crop and weed recognition
Accurate classification of weed species in crop plants plays a crucial role in precision
agriculture by enabling targeted treatment. Recent studies show that artificial intelligence …
agriculture by enabling targeted treatment. Recent studies show that artificial intelligence …
Edge-enabled federated sequential recommendation with knowledge-aware Transformer
The increasing ubiquity of recommendation systems in modern applications has brought
about significant changes in various aspects of our daily lives. However, the emergence of …
about significant changes in various aspects of our daily lives. However, the emergence of …
A Conv-Transformer network for heart rate estimation using ballistocardiographic signals
M Zhang, L Qiu, Y Chen, S Yang, Z Zhang… - … Signal Processing and …, 2023 - Elsevier
Objective Continuous heart rate (HR) monitoring has great implications for the prevention of
chronic diseases, and we use non-contact ballistocardiography (BCG) technology to …
chronic diseases, and we use non-contact ballistocardiography (BCG) technology to …