Using machine learning approaches for multi-omics data analysis: A review
With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …
become essential for biomedical studies to undertake an integrative (combined) approach to …
[HTML][HTML] An overview of machine learning applications for smart buildings
The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …
challenged by unpredicted changes in operational environments due to climate change and …
Milestones in autonomous driving and intelligent vehicles: Survey of surveys
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …
due to the convenience, safety, and economic benefits. Although a number of surveys have …
On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
Keep your eyes on the lane: Real-time attention-guided lane detection
Modern lane detection methods have achieved remarkable performances in complex real-
world scenarios, but many have issues maintaining real-time efficiency, which is important …
world scenarios, but many have issues maintaining real-time efficiency, which is important …
A Survey of Autonomous Driving: Common Practices and Emerging Technologies
Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …
Rethinking efficient lane detection via curve modeling
This paper presents a novel parametric curve-based method for lane detection in RGB
images. Unlike state-of-the-art segmentation-based and point detection-based methods that …
images. Unlike state-of-the-art segmentation-based and point detection-based methods that …
A review of visual SLAM methods for autonomous driving vehicles
Autonomous driving vehicles require both a precise localization and mapping solution in
different driving environment. In this context, Simultaneous Localization and Mapping …
different driving environment. In this context, Simultaneous Localization and Mapping …
Joint object detection and multi-object tracking with graph neural networks
Object detection and data association are critical components in multi-object tracking (MOT)
systems. Despite the fact that the two components are dependent on each other, prior works …
systems. Despite the fact that the two components are dependent on each other, prior works …
Applications of convolutional neural networks for intelligent waste identification and recycling: A review
With the implementations of “Zero Waste” and Industry 4.0, the rapidly increasing
applications of artificial intelligence in waste management have generated a large amount of …
applications of artificial intelligence in waste management have generated a large amount of …