Artificial intelligence (AI) capabilities have grown rapidly with the introduction of cutting-edge
deep-model architectures and learning strategies. Explainable AI (XAI) methods aim to …

Significant progress has been made in computational imaging (CI), in which deep
convolutional neural networks (CNNs) have demonstrated that sparse speckle patterns can …

We investigate the application of convolutional neural networks (CNNs) to the classification
of liquid crystal phases from images of their experimental textures. Three CNN classifier …

Abstract Vision Transformers (ViTs) have emerged as a promising approach for visual
recognition tasks, revolutionizing the field by leveraging the power of transformer-based …

Object detection is a critical component of transportation systems, particularly for
applications such as autonomous driving, traffic monitoring, and infrastructure maintenance …

Recent years have witnessed the remarkable performance of diffusion models in various
vision tasks. However, for image restoration that aims to recover clear images with sharper …

Pixel‐wise classification of hyperspectral image (HSI) is a hot spot in the field of remote
sensing. The classification of HSI requires the model to be more sensitive to dense features …

Skin cancer represents a significant global health concern, where early and precise
diagnosis plays a pivotal role in improving treatment efficacy and patient survival rates …

We propose an optical flow-guided approach for semi-supervised video object
segmentation. Optical flow is usually exploited as additional guidance information in …

We present a case for low batch-size inference with the potential for adaptive training of a
lean encoder model. We do so in the context of a paradigmatic example of machine learning …