WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...
Large-size remote sensing images contain rich geographical information. Efficient and accurate semantic segmentation of these images is of significant importance in various fields. However, the ...
Abstract: Vision-language foundation models (VLMs) have shown great potential in feature transfer and generalization across a wide spectrum of medical-related downstream tasks. However, fine-tuning ...
Abstract: Bone fracture can be defined as the complete or partial disruption of the integrity of bone tissue. Early and accurate diagnosis of fractures plays a decisive role in the effectiveness of ...
Abstract: The rising amount of waste produced worldwide presents serious environmental concerns, and there is a need to create automated waste classification systems to enable effective recycling ...
Abstract: In remote sensing classification problems, high visual similarity between scenes reduces the classification performance of traditional methods. Therefore, advanced deep neural network models ...
Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...
Abstract: Glaucoma, a leading cause of irreversible blindness, requires precise segmentation of the optic disc and optic cup in fundus images for early diagnosis and progression monitoring. This study ...
Abstract: Parkinson's disease is a neurological disorder hat effects the movements including shaking, stiffness, difficulty while walking and speaking. This condition will occur when the nerve cells ...
Abstract: Deep learning models have shown impressive performance across a range of computer vision tasks. However, their lack of transparency limits their adoption in tasks where a clear understanding ...
Abstract: This study investigates the utilization of a hybrid Convolutional Neural Network (CNN) and Vision Transformer (ViT) model, employing transfer learning methods, to enhance brain stroke ...