Weather forecasting is dominated by numerical weather prediction that tries to model
accurately the physical properties of the atmosphere. A downside of numerical weather …

The recent 3D medical ViTs (eg, SwinUNETR) achieve the state-of-the-art performances on
several 3D volumetric data benchmarks, including 3D medical image segmentation …

While parameter efficient tuning (PET) methods have shown great potential with transformer
architecture on Natural Language Processing (NLP) tasks their effectiveness with large …

Vision is a major component in several digital technologies and tools used in agriculture.
Object detection plays a pivotal role in digital farming by automating the task of detecting …

This paper proposes a convolutional neural network (CNN), called SCGNet, for low-
complexity and robust modulation recognition in intelligent communication receivers …

This study proposes and evaluates five deep fully convolutional networks (FCNs) for the
semantic segmentation of a single tree species: SegNet, U-Net, FC-DenseNet, and two …

In this work, we study multi-domain learning for face anti-spoofing (MD-FAS), where a pre-
trained FAS model needs to be updated to perform equally well on both source and target …

Fully convolutional neural networks like U-Net have been the state-of-the-art methods in
medical image segmentation. Practically, a network is highly specialized and trained …

Vision is a major component in several digital technologies and tools used in agriculture.
The object detector, You Look Only Once (YOLO), has gained popularity in agriculture in a …

Deploying deep learning (DL) on mobile devices has been a notable trend in recent years.
To support fast inference of on-device DL, DL libraries play a critical role as algorithms and …