Dataset condensation aims at reducing the network training effort through condensing a
cumbersome training set into a compact synthetic one. State-of-the-art approaches largely …

The combination of infrared and visible videos aims to gather more comprehensive feature
information from multiple sources and reach superior results on various practical tasks, such …

The use of drones and unmanned aerial vehicles has significantly increased in various real-
world applications such as monitoring illegal car parking, tracing vehicles, controlling traffic …

The great success of deep learning heavily relies on increasingly larger training data, which
comes at a price of huge computational and infrastructural costs. This poses crucial …

Hazy images captured under ill-posed scenarios with scattering medium (ie haze, fog, or
smoke) are contaminated in visibility. Inevitably, these images are further degraded by …

A systematic review on electroencephalographic (EEG)-based feature extraction strategies
to diagnosis and therapy of attention deficit hyperactivity disorder (ADHD) in children is …

Encounters between humans and wildlife often lead to injuries, especially in remote
wilderness regions, and highways. Therefore, animal detection is a vital safety and wildlife …

Water-related optics images are often degraded by absorption and scattering effects.
Current underwater image enhancement (UIE) methods improve image quality but neglect …

Safeguarding the data collected by smart meters is essential because the disclosure of this
information may threaten the privacy of the consumer. By obtaining them, hackers can find …

State-of-the-art deep learning-based Head Pose Estimation (HPE) techniques have reached
spectacular performance on High-Resolution (HR) face images. However, they still fail to …