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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. TOOL · arXiv cs.AI English(EN) ·

    Methodology for Creating a Clinically Verified Dermoscopic Image Dataset

    Researchers have developed a new methodology for creating a clinically verified dataset of dermatoscopic images, crucial for advancing AI-driven diagnostic systems in dermatology. The approach standardizes image acquisition using mobile devices, incorporates 16 structured metadata fields, and mandates multi-stage expert verification, including histological confirmation for malignant lesions. A pilot dataset of 1,026 images from 443 patients, collected between June 2025 and May 2026, demonstrates the methodology's effectiveness, featuring verified diagnoses for all 39 malignant lesions. AI

    IMPACT Establishes a standardized framework for high-quality medical image datasets, enabling more reliable AI model development and evaluation in dermatology.

  2. TOOL · arXiv cs.AI English(EN) ·

    Phase-Aware Wavelet-Based-Scattering Encoder-Decoder for Dense Predictions

    Researchers have developed a new Phase-Aware Scattering Encoder-Decoder model designed to improve dense prediction tasks in computer vision. This model enhances scattering transforms by preserving spatial structure and phase information, which are typically lost in global averaging. Initial tests on image denoising show significant improvements in PSNR, and a preliminary study on skin lesion segmentation is also underway. AI

    IMPACT Introduces a novel deep learning architecture that could improve performance on image denoising and segmentation tasks.