Deep learning has been widely applied to high-dimensional hyperspectral image classification and has achieved significant ... Figure 2. The structure diagram of LRFC block. The proposed LRFC block ...

These are not just research projects—they are powering live services. In computer vision, Google’s V-MoE architecture has improved classification ... images—adds a new layer of capability to AI ...

This project presents ... to classify MRI images of brain tumors into one of three categories. The model was trained using a custom-labeled dataset containing over 6,000 images and is capable of ...

Somatic hypermutation (SHM) of immunoglobulin variable (V) regions modulates antibody-antigen affinity is initiated by activation-induced cytidine deaminase (AID) on single-stranded DNA (ssDNA).

'ZDNET Recommends': What exactly does it mean? ZDNET's recommendations are based on many hours of testing, research, and comparison shopping. We gather data from the best available sources ...

Abstract: Deep learning methods have shown promising results in various hyperspectral image (HSI) analysis tasks. Despite these advancements, existing models still struggle to accurately identify fine ...

Kaizen rethinks cell segmentation by mimicking brain predictions. Using an iterative machine-learning approach to refine boundaries in crowded microscopy images, it enhances accuracy in tissue studies ...

Abstract: When taking images against strong light sources ... we formulate the generalization problem as an adversarial training problem and embed an adversarial curve learning (ACL) paradigm in the ...

School of Computer Science, Wuhan University, Wuhan 430072, P. R. China ...