{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T11:07:06Z","timestamp":1790075226916,"version":"4.0.1"},"reference-count":37,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T00:00:00Z","timestamp":1789948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Aerial detection requires fine detail for small targets and broad context for large structures. Sampling loss, blur, and noise can weaken detail without changing feature-map resolution, creating a demand\u2013reliability mismatch. We present Physical Imaging Reliability-Guided Scale-Biased Feature Reweighting (PIR-SBFR), a sensor-to-inference interface that separates scene-scale demand from observation reliability. A visual branch estimates demand, while a fixed analytic rule converts relative sampling, sharpness, noise, and field availability into an ordered multiscale prior. The routing rule requires no sensor-specific response fitting. On public DIOR images, ten paired runs increase average precision (AP) from 62.98% (SD 0.32) to 65.52% (SD 0.40). On the study-specific AI-TOD-v2 split, AP rises from 29.58% (SD 0.27) to 32.10% (SD 0.41). Matched local reproductions of three contemporary tiny-object detectors reach 30.42\u201331.59% AP under the same protocol. PIR-SBFR also improves three compatible host detectors by 2.09\u20132.54 percentage points. All 27 controlled quality conditions and nine held-out degradation types favor PIR-SBFR. On a Jetson Orin NX, its FP16 end-to-end median latency is 19.55 ms. These results demonstrate effective acquisition-conditioned routing under controlled observation changes on public aerial imagery.<\/jats:p>","DOI":"10.3390\/s26185985","type":"journal-article","created":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T10:21:48Z","timestamp":1790072508000},"page":"5985","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["PIR-SBFR: A Calibration-Free Sensor-to-Inference Routing Interface for Aerial Optical Object Detection"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-1632-2824","authenticated-orcid":false,"given":"Zixin","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science, Xijing University, Xi\u2019an 710123, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"given":"Jingchao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Xijing University, Xi\u2019an 710123, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Zizheng","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science, Xijing University, Xi\u2019an 710123, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Xiaoyu","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Computer Science, Xijing University, Xi\u2019an 710123, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Zhirui","family":"Xue","sequence":"additional","affiliation":[{"name":"School of Computer Science, Xijing University, Xi\u2019an 710123, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"}]},{"given":"Junhao","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Xijing University, Xi\u2019an 710123, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"resources","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Chengxin","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Xijing University, Xi\u2019an 710123, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"resources","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.isprsjprs.2016.03.014","article-title":"A Survey on Object Detection in Optical Remote Sensing Images","volume":"117","author":"Cheng","year":"2016","journal-title":"ISPRS J. 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