{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,9]],"date-time":"2026-08-09T02:45:34Z","timestamp":1786243534047,"version":"build-2736575974"},"reference-count":82,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"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":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.engappai.2026.115599","type":"journal-article","created":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T06:38:36Z","timestamp":1783751916000},"page":"115599","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P5","title":["Image enhancement: A necessity for effective underwater object detection?"],"prefix":"10.1016","volume":"181","author":[{"given":"Lujun","family":"Zhai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ye","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olga","family":"Russakovsky","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suxia","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2026.115599_b1","article-title":"YOLO-NAS: Faster and more accurate object detection with NAS","author":"AI","year":"2023","journal-title":"Deci AI Res."},{"key":"10.1016\/j.engappai.2026.115599_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.image.2020.115978","article-title":"Diving deeper into underwater image enhancement: A survey","volume":"89","author":"Anwar","year":"2020","journal-title":"Signal Process., Image Commun."},{"key":"10.1016\/j.engappai.2026.115599_b3","article-title":"Natural-based underwater image color enhancement through fusion of swarm intelligence algorithm","volume":"85","author":"Azmi","year":"2019","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.engappai.2026.115599_b4","doi-asserted-by":"crossref","first-page":"128973","DOI":"10.1109\/ACCESS.2020.3009161","article-title":"Underwater image enhancement based on global and local equalization of histogram and dual-image multi-scale fusion","volume":"8","author":"Bai","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.115599_b5","doi-asserted-by":"crossref","DOI":"10.1364\/AO.565695","article-title":"Joint optimization technique of image enhancement and object detection based on genetic algorithm","author":"Bi","year":"2025","journal-title":"Appl. Opt."},{"issue":"5","key":"10.1016\/j.engappai.2026.115599_b6","doi-asserted-by":"crossref","first-page":"1483","DOI":"10.1109\/TPAMI.2019.2956516","article-title":"Cascade R-CNN: Delving into high quality object detection","volume":"43","author":"Cai","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"10.1016\/j.engappai.2026.115599_b7","series-title":"Reveal of domain effect: How visual restoration contributes to object detection in aquatic scenes","author":"Chen","year":"2020"},{"key":"10.1016\/j.engappai.2026.115599_b8","doi-asserted-by":"crossref","unstructured":"Chen, H., Wang, Y., Guo, T., Xu, C., Deng, Y., Liu, Z., Ma, S., Xu, C., Xu, C., Gao, W., 2021. Pre-trained image processing transformer. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 12299\u201312310.","DOI":"10.1109\/CVPR46437.2021.01212"},{"issue":"1","key":"10.1016\/j.engappai.2026.115599_b9","article-title":"Fish detection using deep learning","volume":"2020","author":"Cui","year":"2020","journal-title":"Appl. Comput. Intell. Soft Comput."},{"key":"10.1016\/j.engappai.2026.115599_b10","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops","first-page":"295","article-title":"AquaGAN: Restoration of underwater images","author":"Desai","year":"2022"},{"key":"10.1016\/j.engappai.2026.115599_b11","series-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020"},{"key":"10.1016\/j.engappai.2026.115599_b12","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.125271","article-title":"UIEDP: Boosting underwater image enhancement with diffusion prior","volume":"259","author":"Du","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.engappai.2026.115599_b13","series-title":"2018 IEEE International Conference on Robotics and Automation","first-page":"7159","article-title":"Enhancing underwater imagery using generative adversarial networks","author":"Fabbri","year":"2018"},{"key":"10.1016\/j.engappai.2026.115599_b14","series-title":"2018 IEEE International Conference on Robotics and Automation","first-page":"7159","article-title":"Enhancing underwater imagery using generative adversarial networks","author":"Fabbri","year":"2018"},{"key":"10.1016\/j.engappai.2026.115599_b15","doi-asserted-by":"crossref","unstructured":"Finlayson, G., Trezzi, E., 2004. Shades of gray and colour constancy. In: Proceedings of Color Imaging. pp. 37\u201341.","DOI":"10.2352\/CIC.2004.12.1.art00008"},{"key":"10.1016\/j.engappai.2026.115599_b16","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.neucom.2022.10.039","article-title":"Rethinking general underwater object detection: datasets, challenges, and solutions","volume":"517","author":"Fu","year":"2023","journal-title":"Neurocomputing"},{"key":"10.1016\/j.engappai.2026.115599_b17","series-title":"Joint perceptual learning for enhancement and object detection in underwater scenarios","author":"Fu","year":"2023"},{"key":"10.1016\/j.engappai.2026.115599_b18","series-title":"Proceedings of the IEEE International Conference on Image Processing","first-page":"4572","article-title":"A retinex-based enhancing approach for single underwater image","author":"Fu","year":"2014"},{"key":"10.1016\/j.engappai.2026.115599_b19","series-title":"2014 IEEE International Conference on Image Processing","first-page":"4572","article-title":"A retinex-based enhancing approach for single underwater image","author":"Fu","year":"2014"},{"key":"10.1016\/j.engappai.2026.115599_b20","series-title":"CVPR","article-title":"Image style transfer using convolutional neural networks","author":"Gatys","year":"2016"},{"key":"10.1016\/j.engappai.2026.115599_b21","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J., 2014. Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 580\u2013587.","DOI":"10.1109\/CVPR.2014.81"},{"key":"10.1016\/j.engappai.2026.115599_b22","series-title":"Advances in Neural Information Processing Systems (NeurIPS)","first-page":"2672","article-title":"Generative adversarial nets","author":"Goodfellow","year":"2014"},{"key":"10.1016\/j.engappai.2026.115599_b23","article-title":"Underwater object detection algorithm integrating image enhancement module","author":"Guo","year":"2025","journal-title":"J. Vis. Commun. Image Represent."},{"key":"10.1016\/j.engappai.2026.115599_b24","series-title":"2019 IEEE Intelligent Transportation Systems Conference","first-page":"3675","article-title":"Semantic understanding of foggy scenes with purely synthetic data","author":"Hahner","year":"2019"},{"key":"10.1016\/j.engappai.2026.115599_b25","series-title":"\u03b2-VAE: Learning basic visual concepts with a constrained variational framework","author":"Higgins","year":"2016"},{"key":"10.1016\/j.engappai.2026.115599_b26","unstructured":"Ho, J., Jain, A., Abbeel, P., 2020. Denoising diffusion probabilistic models. In: Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems (NeurIPS). Virtual Conference."},{"key":"10.1016\/j.engappai.2026.115599_b27","doi-asserted-by":"crossref","first-page":"111925","DOI":"10.1109\/ACCESS.2021.3103737","article-title":"A novel automatic white balance method for color constancy under different color temperatures","volume":"9","author":"Hsu","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.115599_b28","series-title":"DACA-net: A degradation-aware conditional diffusion network for underwater image enhancement","author":"Huang","year":"2025"},{"issue":"2","key":"10.1016\/j.engappai.2026.115599_b29","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/S0146-664X(77)80011-7","article-title":"Image enhancement by histogram transformation","volume":"6","author":"Hummel","year":"1977","journal-title":"Comput. Graph. Image Process."},{"key":"10.1016\/j.engappai.2026.115599_b30","series-title":"2021 IEEE\/CVF International Conference on Computer Vision Workshops","first-page":"1944","article-title":"Efficient wavelet boost learning-based multi-stage progressive refinement network for underwater image enhancement","author":"Huo","year":"2021"},{"issue":"2","key":"10.1016\/j.engappai.2026.115599_b31","doi-asserted-by":"crossref","first-page":"3227","DOI":"10.1109\/LRA.2020.2974710","article-title":"Fast underwater image enhancement for improved visual perception","volume":"5","author":"Islam","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.engappai.2026.115599_b32","doi-asserted-by":"crossref","unstructured":"Iwamoto, K., Ochiai, T., Delcroix, M., Ikeshita, R., Sato, H., Araki, S., Katagiri, S., 2022. How Bad Are Artifacts? Analyzing the Impact of Speech Enhancement Errors on ASR. In: Proc. Interspeech. pp. 5418\u20135422.","DOI":"10.21437\/Interspeech.2022-318"},{"issue":"10","key":"10.1016\/j.engappai.2026.115599_b33","doi-asserted-by":"crossref","first-page":"6584","DOI":"10.1109\/TCSVT.2022.3174817","article-title":"Target oriented perceptual adversarial fusion network for underwater image enhancement","volume":"32","author":"Jiang","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.engappai.2026.115599_b34","series-title":"2013 IEEE International Conference on Computer Vision Workshops","first-page":"825","article-title":"Transmission estimation in underwater single images","author":"Jr","year":"2013"},{"key":"10.1016\/j.engappai.2026.115599_b35","series-title":"2024 IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"1443","article-title":"Spectroformer: Multi-domain query cascaded transformer network for underwater image enhancement","author":"Khan","year":"2024"},{"key":"10.1016\/j.engappai.2026.115599_b36","series-title":"Auto-encoding variational bayes","author":"Kingma","year":"2013"},{"key":"10.1016\/j.engappai.2026.115599_b37","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2019.107038","article-title":"Underwater scene prior inspired deep underwater image and video enhancement","volume":"98","author":"Li","year":"2020","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.engappai.2026.115599_b38","doi-asserted-by":"crossref","unstructured":"Li, S., Araujo, I.B., Ren, W., Wang, Z., Tokuda, E.K., Junior, R.H., Cesar-Junior, R., Zhang, J., Guo, X., Cao, X., 2019. Single Image Deraining: A Comprehensive Benchmark Analysis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. CVPR.","DOI":"10.1109\/CVPR.2019.00396"},{"key":"10.1016\/j.engappai.2026.115599_b39","doi-asserted-by":"crossref","first-page":"4376","DOI":"10.1109\/TIP.2019.2955241","article-title":"An underwater image enhancement benchmark dataset and beyond","volume":"29","author":"Li","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.engappai.2026.115599_b40","doi-asserted-by":"crossref","DOI":"10.1109\/LRA.2017.2730363","article-title":"WaterGAN: Unsupervised generative network to enable real-time color correction of monocular underwater images","author":"Li","year":"2017","journal-title":"IEEE Robot. Autom. Lett. (RA-L)"},{"issue":"1","key":"10.1016\/j.engappai.2026.115599_b41","first-page":"387","article-title":"WaterGAN: Unsupervised generative network to enable real-time color correction of monocular underwater images","volume":"3","author":"Li","year":"2017","journal-title":"IEEE Robot. Autom. Lett."},{"issue":"2","key":"10.1016\/j.engappai.2026.115599_b42","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","article-title":"Focal loss for dense object detection","volume":"42","author":"Lin","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"10.1016\/j.engappai.2026.115599_b43","first-page":"21","article-title":"SSD: Single shot MultiBox detector","author":"Liu","year":"2016","journal-title":"Eur. Conf. Comput. Vis. (ECCV)"},{"issue":"12","key":"10.1016\/j.engappai.2026.115599_b44","doi-asserted-by":"crossref","first-page":"4861","DOI":"10.1109\/TCSVT.2019.2963772","article-title":"Real-world underwater enhancement: Challenges, benchmarks, and solutions under natural light","volume":"30","author":"Liu","year":"2020","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.engappai.2026.115599_b45","doi-asserted-by":"crossref","first-page":"4922","DOI":"10.1109\/TIP.2022.3190209","article-title":"Twin adversarial contrastive learning for underwater image enhancement and beyond","volume":"31","author":"Liu","year":"2022","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.engappai.2026.115599_b46","series-title":"2021 IEEE International Conference on Multimedia & Expo Workshops","first-page":"1","article-title":"A dataset and benchmark of underwater object detection for robot picking","author":"Liu","year":"2021"},{"key":"10.1016\/j.engappai.2026.115599_b47","series-title":"A novel underwater image enhancement and improved underwater biological detection pipeline","author":"Liu","year":"2022"},{"key":"10.1016\/j.engappai.2026.115599_b48","doi-asserted-by":"crossref","unstructured":"Menne, T., Schl\u00fcter, R., Ney, H., 2019. Investigation into Joint Optimization of Single Channel Speech Enhancement and Acoustic Modeling for Robust ASR. In: Proc. IEEE ICASSP. pp. 6660\u20136664.","DOI":"10.1109\/ICASSP.2019.8682460"},{"key":"10.1016\/j.engappai.2026.115599_b49","series-title":"2020 International Joint Conference on Neural Networks","first-page":"1","article-title":"Eigen-CAM: Class activation map using principal components","author":"Muhammad","year":"2020"},{"key":"10.1016\/j.engappai.2026.115599_b50","doi-asserted-by":"crossref","unstructured":"Pei, Y., Huang, Y., Zou, Q., Lu, Y., Wang, S., 2018. Does Haze Removal Help CNN-based Image Classification?. In: Proceedings of the European Conference on Computer Vision. ECCV.","DOI":"10.1007\/978-3-030-01249-6_42"},{"issue":"4","key":"10.1016\/j.engappai.2026.115599_b51","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1109\/TPAMI.2019.2950923","article-title":"Effects of image degradation and degradation removal to CNN-based image classification","volume":"43","author":"Pei","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.engappai.2026.115599_b52","series-title":"Advances in Neural Information Processing Systems","first-page":"91","article-title":"Faster r-cnn: Towards real-time object detection with region proposal networks","author":"Ren","year":"2015"},{"issue":"6","key":"10.1016\/j.engappai.2026.115599_b53","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"issue":"1","key":"10.1016\/j.engappai.2026.115599_b54","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1002\/col.20070","article-title":"The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations","volume":"30","author":"Sharma","year":"2005","journal-title":"Color Res. Appl."},{"key":"10.1016\/j.engappai.2026.115599_b55","unstructured":"Sobel, I., 1968. A 3\u00d73 Isotropic Gradient Operator for Image Processing. Stanford Artificial Intelligence Project (SAIL) Technical Report."},{"key":"10.1016\/j.engappai.2026.115599_b56","unstructured":"Song, J., Meng, C., Ermon, S., 2021. Denoising diffusion implicit models. In: 9th International Conference on Learning Representations. ICLR, Virtual Event, Austria."},{"key":"10.1016\/j.engappai.2026.115599_b57","series-title":"International Journal of Computer Vision","first-page":"11","article-title":"Color indexing","volume":"vol. 7","author":"Swain","year":"1991"},{"key":"10.1016\/j.engappai.2026.115599_b58","doi-asserted-by":"crossref","unstructured":"Tang, Y., Iwaguchi, T., Kawasaki, H., Sagawa, R., Furukawa, R., 2022. AutoEnhancer: Transformer on U-Net Architecture search for Underwater Image Enhancement. In: Proceedings of the Asian Conference on Computer Vision. ACCV, pp. 1403\u20131420.","DOI":"10.1007\/978-3-031-26313-2_8"},{"key":"10.1016\/j.engappai.2026.115599_b59","series-title":"Proceedings of the 31st ACM International Conference on Multimedia","first-page":"5419","article-title":"Underwater image enhancement by transformer-based diffusion model with non-uniform sampling for skip strategy","author":"Tang","year":"2023"},{"key":"10.1016\/j.engappai.2026.115599_b60","first-page":"1","article-title":"Tensorized parameter-free multi-view spectral clustering based on fair representation learning","author":"Wang","year":"2026","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.engappai.2026.115599_b61","doi-asserted-by":"crossref","first-page":"9385","DOI":"10.1109\/TMM.2025.3613125","article-title":"Tensor completion framework by graph refinement for incomplete multi-view clustering","volume":"27","author":"Wang","year":"2025","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.engappai.2026.115599_b62","first-page":"1","article-title":"Tensorized fine-grained incomplete multiview clustering via intrinsic structure recovery","author":"Wang","year":"2026","journal-title":"IEEE Trans. Syst. Man, Cybern.: Syst."},{"key":"10.1016\/j.engappai.2026.115599_b63","doi-asserted-by":"crossref","unstructured":"Wang, Z., Cun, X., Bao, J., Zhou, W., Liu, J., Li, H., 2022. Uformer: A general U-shaped transformer for image restoration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 17683\u201317693.","DOI":"10.1109\/CVPR52688.2022.01716"},{"key":"10.1016\/j.engappai.2026.115599_b64","doi-asserted-by":"crossref","DOI":"10.1016\/j.image.2021.116250","article-title":"UIEC2-net: CNN-based underwater image enhancement using two color spaces","volume":"96","author":"Wang","year":"2021","journal-title":"Signal Process., Image Commun."},{"key":"10.1016\/j.engappai.2026.115599_b65","doi-asserted-by":"crossref","first-page":"1442","DOI":"10.1109\/TIP.2023.3244647","article-title":"Domain adaptation for underwater image enhancement","volume":"32","author":"Wang","year":"2023","journal-title":"IEEE Trans. Image Process."},{"issue":"2","key":"10.1016\/j.engappai.2026.115599_b66","doi-asserted-by":"crossref","first-page":"1952","DOI":"10.1109\/TETCI.2024.3359061","article-title":"UIE-convformer: Underwater image enhancement based on convolution and feature fusion transformer","volume":"8","author":"Wang","year":"2024","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"key":"10.1016\/j.engappai.2026.115599_b67","series-title":"UWGAN: Underwater GAN for real-world underwater color restoration and dehazing","author":"Wang","year":"2019"},{"key":"10.1016\/j.engappai.2026.115599_b68","article-title":"An innovative neural network architecture designed for industrial fault diagnosis with hierarchical adaptive attention mechanism","author":"Wu","year":"2025","journal-title":"Process. Saf. Environ. Prot."},{"issue":"12","key":"10.1016\/j.engappai.2026.115599_b69","doi-asserted-by":"crossref","first-page":"6062","DOI":"10.1109\/TIP.2015.2491020","article-title":"An underwater color image quality evaluation metric","volume":"24","author":"Yang","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.engappai.2026.115599_b70","doi-asserted-by":"crossref","DOI":"10.1016\/j.robot.2024.104817","article-title":"Shape-guided detection: A joint network combining object detection and underwater image enhancement","author":"Yang","year":"2024","journal-title":"Robot. Auton. Syst."},{"key":"10.1016\/j.engappai.2026.115599_b71","series-title":"2022 IEEE International Conference on Image Processing","first-page":"4093","article-title":"Enhancing underwater image using degradation adaptive adversarial network","author":"Zhai","year":"2022"},{"key":"10.1016\/j.engappai.2026.115599_b72","doi-asserted-by":"crossref","first-page":"21049","DOI":"10.1109\/ACCESS.2023.3250616","article-title":"A comprehensive review of deep learning-based real-world image restoration","volume":"11","author":"Zhai","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.115599_b73","doi-asserted-by":"crossref","first-page":"72492","DOI":"10.1109\/ACCESS.2019.2920403","article-title":"Single image defogging based on multi-channel convolutional MSRCR","volume":"7","author":"Zhang","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.115599_b74","doi-asserted-by":"crossref","first-page":"72492","DOI":"10.1109\/ACCESS.2019.2920403","article-title":"Single image defogging based on multi-channel convolutional MSRCR","volume":"7","author":"Zhang","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.115599_b75","series-title":"CVPR","article-title":"The unreasonable effectiveness of deep features as a perceptual metric","author":"Zhang","year":"2018"},{"key":"10.1016\/j.engappai.2026.115599_b76","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2025.113811","article-title":"A lightweight network enhanced by attention-guided cross-scale interaction for underwater object detection","volume":"184","author":"Zhang","year":"2025","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.engappai.2026.115599_b77","doi-asserted-by":"crossref","DOI":"10.1007\/s10462-025-11439-9","article-title":"Reinforcement learning for single-agent to multi-agent systems: From basic theory to industrial application progress, a survey","author":"Zhang","year":"2025","journal-title":"Artif. Intell. Rev."},{"key":"10.1016\/j.engappai.2026.115599_b78","series-title":"2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"8281","article-title":"Wavelet-based Fourier information interaction with frequency diffusion adjustment for underwater image restoration","author":"Zhao","year":"2024"},{"key":"10.1016\/j.engappai.2026.115599_b79","doi-asserted-by":"crossref","unstructured":"Zhao, C., Cai, W., Dong, C., Hu, C., 2024b. Wavelet-based fourier information interaction with frequency diffusion adjustment for underwater image restoration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 8281\u20138291.","DOI":"10.1109\/CVPR52733.2024.00791"},{"key":"10.1016\/j.engappai.2026.115599_b80","series-title":"Image restoration using L1\/L2 loss","author":"Zhao","year":"2017"},{"key":"10.1016\/j.engappai.2026.115599_b81","series-title":"ECCVW","article-title":"WGAN-GP and perceptual loss for realistic image restoration","author":"Zhou","year":"2018"},{"key":"10.1016\/j.engappai.2026.115599_b82","doi-asserted-by":"crossref","first-page":"5442","DOI":"10.1109\/TIP.2022.3196546","article-title":"Underwater image enhancement with hyper-laplacian reflectance priors","volume":"31","author":"Zhuang","year":"2022","journal-title":"IEEE Trans. Image Process."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095219762601883X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095219762601883X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,9]],"date-time":"2026-08-09T02:27:16Z","timestamp":1786242436000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S095219762601883X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":82,"alternative-id":["S095219762601883X"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.115599","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Image enhancement: A necessity for effective underwater object detection?","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.115599","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115599"}}