Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
It is well known that query-based attacks tend to have relatively higher success rates in adversarial black-box attacks. While research on black-box attacks is actively being conducted, relatively few studies have focused on pixel attacks that target only a limited number of pixels. In image classification, query-based pixel attacks often rely on patches, which heavily depend on randomness and n...
The ethical, social and legal issues surrounding facial analysis technologies have been widely debated in recent years. Key critics have argued that these technologies can perpetuate bias and discrimination, particularly against marginalized groups. We contribute to this field of research by reporting on the limitations of facial analysis systems with the faces of people with Down syndrome: this...
White blood cells (WBC) are important parts of our immune system, and they protect our body against infections by eliminating viruses, bacteria, par...
Map construction task plays a vital role in providing precise and comprehensive static environmental information essential for autonomous driving sy...
Attention-based arbitrary style transfer methods have gained significant attention recently due to their impressive ability to synthesize style deta...
Deep Learning approaches in dermatological image classification have shown promising results, yet the field faces significant methodological challen...
Spatial transformations that capture population-level morphological statistics are critical for medical image analysis. Commonly used smoothness reg...
Few-shot learning (FSL) has recently been extensively utilized to overcome the scarcity of training data in domain-specific visual recognition. In r...
OBJECTIVES: To evaluate the interobserver agreement and diagnostic accuracy of ovarian-adnexal reporting and data system magnetic resonance imaging (O...
Recent advancements in Vision-Language-Action (VLA) models have leveraged pre-trained Vision-Language Models (VLMs) to improve the generalization ca...
Bluetooth Low Energy (BLE) location trackers, or "tags", are popular consumer devices for monitoring personal items. These tags rely on their respec...
Integrated sensing and communication (ISAC) boosts network efficiency by using existing resources for diverse sensing applications. In this work, we...
Automated segmentation plays a pivotal role in medical image analysis and computer-assisted interventions. Despite the promising performance of exis...
Artificial intelligence (AI) systems in healthcare have demonstrated remarkable potential to improve patient outcomes. However, if not designed with...
In this study, we reveal that the interaction between haze degradation and JPEG compression introduces complex joint loss effects, which significant...
Given multi-type point maps from different place-types (e.g., tumor regions), our objective is to develop a classifier trained on the source place-t...
Pretrained visual-language models have made significant advancements in multimodal tasks, including image-text retrieval. However, a major challenge...
Federated learning has emerged as a key paradigm in privacy-preserving computing due to its "data usable but not visible" property, enabling users t...
Knowledge distillation has been widely adopted in computer vision task processing, since it can effectively enhance the performance of lightweight s...
Recommender systems aim to provide personalized item recommendations by capturing user behaviors derived from their interaction history. Considering...