Beijing, Jan. 15, 2026 (GLOBE NEWSWIRE) -- WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ...
Elon Musk’s Grok artificial intelligence chatbot appears to have new guardrails around image generation, following global outrage after it was found to be complying with user requests to digitally ...
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 ...