{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T15:58:05Z","timestamp":1780934285970,"version":"3.54.1"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.patcog.2026.113956","type":"journal-article","created":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T15:53:21Z","timestamp":1779292401000},"page":"113956","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["DCH-Net: A hyperspectral object detection network with differential convolution and spectral gradient fusion"],"prefix":"10.1016","volume":"180","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7412-961X","authenticated-orcid":false,"given":"Ailin","family":"Niu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3720-608X","authenticated-orcid":false,"given":"Xinyu","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6719-4167","authenticated-orcid":false,"given":"Qiang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiuchen","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolin","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qizhi","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2026.113956_b1","doi-asserted-by":"crossref","first-page":"3053","DOI":"10.1109\/JSTARS.2023.3349175","article-title":"S2DCN: Spectral\u2013spatial difference convolution network for hyperspectral image classification","volume":"17","author":"Zhang","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"10.1016\/j.patcog.2026.113956_b2","article-title":"HADDNLP: Hyperspectral anomaly detection via double nonlocal priors","author":"Ren","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113956_b3","doi-asserted-by":"crossref","DOI":"10.1109\/TGRS.2024.3476116","article-title":"Transformer-based cross-domain few-shot learning for hyperspectral target detection","author":"Feng","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b4","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.110140","article-title":"CS-Net: Conv-simpleformer network for agricultural image segmentation","volume":"147","author":"Liu","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113956_b5","doi-asserted-by":"crossref","unstructured":"J. Chen, X. Yan, Q. Xu, K. Li, Tokenize Image Patches: Global Context Fusion for Effective Haze Removal in Large Images, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2025, pp. 2258\u20132268.","DOI":"10.1109\/CVPR52734.2025.00216"},{"key":"10.1016\/j.patcog.2026.113956_b6","article-title":"Mitigating texture bias: A remote sensing super-resolution method focusing on high-frequency texture reconstruction","author":"Yan","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b7","article-title":"MRF-Net: An infrared remote sensing image thin cloud removal method with the intra-inter coherent constraint","author":"Xu","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b8","first-page":"1","article-title":"Hyperspectral target detection based on a background-aware sparse transformer network","volume":"63","author":"Wang","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b9","series-title":"Yolov12: Attention-centric real-time object detectors","author":"Tian","year":"2025"},{"key":"10.1016\/j.patcog.2026.113956_b10","article-title":"Heterogeneous mixture of experts for remote sensing image super-resolution","author":"Chen","year":"2025","journal-title":"IEEE Geosci. Remote. Sens. Lett."},{"key":"10.1016\/j.patcog.2026.113956_b11","series-title":"Dino: Detr with improved denoising anchor boxes for end-to-end object detection","author":"Zhang","year":"2022"},{"issue":"11","key":"10.1016\/j.patcog.2026.113956_b12","doi-asserted-by":"crossref","first-page":"5345","DOI":"10.1109\/TIP.2016.2601268","article-title":"Beyond the sparsity-based target detector: A hybrid sparsity and statistics-based detector for hyperspectral images","volume":"25","author":"Du","year":"2016","journal-title":"IEEE Trans. Image Process."},{"issue":"12","key":"10.1016\/j.patcog.2026.113956_b13","doi-asserted-by":"crossref","first-page":"3138","DOI":"10.1117\/1.1327499","article-title":"Target-constrained interference-minimized approach to subpixel target detection for hyperspectral images","volume":"39","author":"Ren","year":"2000","journal-title":"Opt. Eng., Bellingham"},{"key":"10.1016\/j.patcog.2026.113956_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.adhoc.2020.102369","article-title":"Salient object detection on hyperspectral images in wireless network using CNN and saliency optimization","volume":"112","author":"Huang","year":"2021","journal-title":"Ad Hoc Networks"},{"key":"10.1016\/j.patcog.2026.113956_b15","doi-asserted-by":"crossref","DOI":"10.3389\/fmars.2024.1447189","article-title":"Tensor adaptive reconstruction cascaded with spatial-spectral fusion for marine target detection","volume":"11","author":"Zhao","year":"2024","journal-title":"Front. Mar. Sci."},{"key":"10.1016\/j.patcog.2026.113956_b16","doi-asserted-by":"crossref","unstructured":"S. Kumar, I. Arevalo, A. Iftekhar, B. Manjunath, Methanemapper: Spectral absorption aware hyperspectral transformer for methane detection, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 17609\u201317618.","DOI":"10.1109\/CVPR52729.2023.01689"},{"issue":"23","key":"10.1016\/j.patcog.2026.113956_b17","doi-asserted-by":"crossref","first-page":"4482","DOI":"10.3390\/rs16234482","article-title":"Hyperspectral object detection based on spatial\u2013spectral fusion and visual mamba","volume":"16","author":"Li","year":"2024","journal-title":"Remote. Sens."},{"key":"10.1016\/j.patcog.2026.113956_b18","series-title":"European Conference on Computer Vision","first-page":"740","article-title":"Microsoft coco: Common objects in context","author":"Lin","year":"2014"},{"key":"10.1016\/j.patcog.2026.113956_b19","series-title":"2021 International Conference on Artificial Intelligence in Information and Communication","first-page":"181","article-title":"Small object detection using context and attention","author":"Lim","year":"2021"},{"key":"10.1016\/j.patcog.2026.113956_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.109801","article-title":"Construction of a feature enhancement network for small object detection","volume":"143","author":"Zhang","year":"2023","journal-title":"Pattern Recognit."},{"issue":"6","key":"10.1016\/j.patcog.2026.113956_b21","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.3390\/rs16061071","article-title":"DCEF2-YOLO: Aerial detection YOLO with deformable convolution\u2013efficient feature fusion for small target detection","volume":"16","author":"Shin","year":"2024","journal-title":"Remote. Sens."},{"key":"10.1016\/j.patcog.2026.113956_b22","article-title":"Cross-layer feature pyramid transformer for small object detection in aerial images","author":"Du","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b23","first-page":"1","article-title":"Triplet spectralwise transformer network for hyperspectral target detection","volume":"61","author":"Jiao","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b24","first-page":"1","article-title":"Hyperspectral target detection: Learning faithful background representations via orthogonal subspace-guided variational autoencoder","volume":"62","author":"Tian","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b25","first-page":"1","article-title":"A point-set topology-based information entropy estimation method for hyperspectral target detection","volume":"62","author":"Sun","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b26","series-title":"An isotropic 3 \u00d7 3 image gradient operator","author":"Sobel","year":"2014"},{"issue":"1167","key":"10.1016\/j.patcog.2026.113956_b27","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1098\/rspb.1980.0020","article-title":"Theory of edge detection","volume":"207","author":"Marr","year":"1980","journal-title":"Proc. R. Soc. Lond. B. Biol. Sci."},{"issue":"3","key":"10.1016\/j.patcog.2026.113956_b28","doi-asserted-by":"crossref","first-page":"352","DOI":"10.3390\/brainsci11030352","article-title":"Differential deep convolutional neural network model for brain tumor classification","volume":"11","author":"Abd El Kader","year":"2021","journal-title":"Brain Sci."},{"key":"10.1016\/j.patcog.2026.113956_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111379","article-title":"DCANet: Differential convolution attention network for RGB-D semantic segmentation","volume":"162","author":"Bai","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113956_b30","article-title":"ESOD-YOLOv8: Small object detection enhanced with auto-disturbance rejection convolution","author":"Yu","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.patcog.2026.113956_b31","series-title":"Deformable detr: Deformable transformers for end-to-end object detection","author":"Zhu","year":"2020"},{"issue":"10","key":"10.1016\/j.patcog.2026.113956_b32","doi-asserted-by":"crossref","first-page":"5600","DOI":"10.1109\/TGRS.2017.2710145","article-title":"Hyperspectral anomaly detection with attribute and edge-preserving filters","volume":"55","author":"Kang","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b33","first-page":"1","article-title":"FFCA-YOLO for small object detection in remote sensing images","volume":"62","author":"Zhang","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b34","doi-asserted-by":"crossref","unstructured":"J. Li, Y. Liu, X. Wang, Y. Peng, C. Sun, S. Wang, Z. Sun, T. Ke, X. Jiang, T. Lu, et al., Hyperfree: A channel-adaptive and tuning-free foundation model for hyperspectral remote sensing imagery, in: Proceedings of the Computer Vision and Pattern Recognition Conference, 2025, pp. 23048\u201323058.","DOI":"10.1109\/CVPR52734.2025.02146"},{"issue":"4","key":"10.1016\/j.patcog.2026.113956_b35","doi-asserted-by":"crossref","DOI":"10.3390\/rs16040718","article-title":"Target detection adapting to spectral variability in multi-temporal hyperspectral images using implicit contrastive learning","volume":"16","author":"Zhang","year":"2024","journal-title":"Remote. Sens."},{"key":"10.1016\/j.patcog.2026.113956_b36","first-page":"1","article-title":"Self-supervised spectral-level contrastive learning for hyperspectral target detection","volume":"61","author":"Wang","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b37","article-title":"Self-supervised learning with deep clustering for target detection in hyperspectral images with insufficient spectral variation prior","volume":"122","author":"Zhang","year":"2023","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.patcog.2026.113956_b38","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.isprsjprs.2025.05.005","article-title":"SpecDETR: A transformer-based hyperspectral point object detection network","volume":"226","author":"Li","year":"2025","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.patcog.2026.113956_b39","article-title":"Optimal strategies for wide-area small object detection using deep learning: Practices from a global flying aircraft dataset","volume":"127","author":"Zhao","year":"2024","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.patcog.2026.113956_b40","doi-asserted-by":"crossref","unstructured":"B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, A. Torralba, Learning deep features for discriminative localization, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 2921\u20132929.","DOI":"10.1109\/CVPR.2016.319"}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326009210?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326009210?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T15:03:48Z","timestamp":1780931028000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326009210"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":40,"alternative-id":["S0031320326009210"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113956","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"DCH-Net: A hyperspectral object detection network with differential convolution and spectral gradient fusion","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113956","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"113956"}}