In recent years, 3D point cloud has gained increasing attention as a new representation for
objects. However, the raw point cloud is often noisy and contains outliers. Therefore, it is …

Medical imaging methods, such as CT scans, MRI scans, X-rays, and ultrasound imaging,
are widely used for diagnosis in the healthcare domain. However, these methods are often …

Denoising diffusion models are a powerful type of generative models used to capture
complex distributions of real-world signals. However, their applicability is limited to …

Self-attention has the promise of improving computer vision systems due to parameter-
independent scaling of receptive fields and content-dependent interactions, in contrast to …

Convolutions are the fundamental building blocks of CNNs. The fact that their weights are
spatially shared is one of the main reasons for their widespread use, but it is also a major …

Backdoor attacks embed hidden malicious behaviors into deep learning models, which only
activate and cause misclassifications on model inputs containing a specific" trigger." Existing …

Image processing pipelines combine the challenges of stencil computations and stream
programs. They are composed of large graphs of different stencil stages, as well as complex …

In order to achieve perceptually better fusion of infrared (IR) and visible images than
conventional pixel-level fusion algorithms based on multi-scale decomposition (MSD), we …

One of the most common modalities to examine the human eye is the eye‐fundus
photograph. The evaluation of fundus photographs is carried out by medical experts during …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …