YOLO has become a central real-time object detection system for robotics, driverless cars,
and video monitoring applications. We present a comprehensive analysis of YOLO's …

Pretrained Foundation Models (PFMs) are regarded as the foundation for various
downstream tasks with different data modalities. A PFM (eg, BERT, ChatGPT, and GPT-4) is …

Compared to the great progress of large-scale vision transformers (ViTs) in recent years,
large-scale models based on convolutional neural networks (CNNs) are still in an early …

Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-
modality-dominated remote sensing (RS) applications, especially with an emphasis on …

Open-vocabulary semantic segmentation aims to segment an image into semantic regions
according to text descriptions, which may not have been seen during training. Recent two …

Abstract Universal Image Segmentation is not a new concept. Past attempts to unify image
segmentation include scene parsing, panoptic segmentation, and, more recently, new …

Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …

This paper presents a new framework for open-vocabulary semantic segmentation with the
pre-trained vision-language model, named SAN. Our approach models the semantic …

While originally designed for natural language processing tasks, the self-attention
mechanism has recently taken various computer vision areas by storm. However, the 2D …

Visual recognition in low-data regimes requires deep neural networks to learn generalized
representations from limited training samples. Recently, CLIP-based methods have shown …