{"data":{"id":"358d0089-176d-4453-988b-1b5aa91b9698","title":"Visual Safety Mapping for UAV Landings Using Ordinal Regression Networks","summary":"Researchers developed OR-SLZNet, a deep learning model that helps drones automatically identify safe landing zones by analyzing camera images in real time. The model assigns each pixel a safety score by combining visual features like color and texture with geometric information like flatness and slope, enabling drones to make quick landing decisions in emergencies or autonomous missions.","solution":"N/A -- no mitigation discussed in source.","labels":["research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11264827","publishedAt":"2025-11-24T13:16:56.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":"2025-11-24T13:16:56.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.75,"researchCategory":"peer_reviewed","atlasIds":null}}