Traditional video-based human activity recognition has experienced remarkable progress
linked to the rise of deep learning, but this effect was slower as it comes to the downstream …

While recognition accuracies of video classification models trained on conventional
benchmarks are gradually saturating, recent studies raise alarm about the learned …

Driver distraction behavior recognition is currently a significant study area that involves
analyzing and identifying various movements, actions, and patterns exhibited by drivers …

This paper aims to serve as a comprehensive guide for researchers and practitioners,
offering insights into the current state, potential applications, and future research directions …

As the smallest structural unit of feature map**, the convolution kernel in a deep
convolution neural networks (DCNN) convolutional layer is responsible for the input channel …

High-precision road detection from very high resolution (VHR) remote sensing images has
broad application value. However, the most advanced deep learning based methods often …

Driver observation models are rarely deployed under perfect conditions. In practice,
illumination, camera placement and type differ from the ones present during training and …

Modality selection is an important step when designing multimodal systems, especially in
the case of cross-domain activity recognition as certain modalities are more robust to …

Driver monitoring will be required in many countries for all new vehicles with automation
functions. While the common approach for this task is face and eye gaze monitoring …

Deep neural network pruning is an effective model compression and acceleration method. In
the initial pruning stage, maintaining the integrity of the input channel of the convolution …