work on bg section, new referenes

thesis/bib/bibliography.bib

@@ -116,7 +116,7 @@
               on MNIST and CIFAR-10 image benchmark datasets as well as on the
               detection of adversarial examples of GTSRB stop signs.},
 },
-@inproceedings{pmlr-v80-ruff18a,
+@inproceedings{deep_svdd,
   title = {Deep One-Class Classification},
   author = {Ruff, Lukas and Vandermeulen, Robert and Goernitz, Nico and Deecke,
             Lucas and Siddiqui, Shoaib Ahmed and Binder, Alexander and M{\"u}ller
@@ -368,5 +368,93 @@
   year = {2015},
   month = sep,
   pages = {12680–12703},
+},
+
+@article{semi_ad_survey,
+  title = {Semi-supervised anomaly detection algorithms: A comparative summary
+           and future research directions},
+  volume = {218},
+  ISSN = {0950-7051},
+  url = {http://dx.doi.org/10.1016/j.knosys.2021.106878},
+  DOI = {10.1016/j.knosys.2021.106878},
+  journal = {Knowledge-Based Systems},
+  publisher = {Elsevier BV},
+  author = {Villa-Pérez, Miryam Elizabeth and Álvarez-Carmona, Miguel Á. and
+            Loyola-González, Octavio and Medina-Pérez, Miguel Angel and
+            Velazco-Rossell, Juan Carlos and Choo, Kim-Kwang Raymond},
+  year = {2021},
+  month = apr,
+  pages = {106878},
+},
+@inbook{bg_autoencoder_ad,
+  title = {Outlier Detection with Autoencoder Ensembles},
+  ISBN = {9781611974973},
+  url = {http://dx.doi.org/10.1137/1.9781611974973.11},
+  DOI = {10.1137/1.9781611974973.11},
+  booktitle = {Proceedings of the 2017 SIAM International Conference on Data
+               Mining},
+  publisher = {Society for Industrial and Applied Mathematics},
+  author = {Chen, Jinghui and Sathe, Saket and Aggarwal, Charu and Turaga,
+            Deepak},
+  year = {2017},
+  month = jun,
+  pages = {90–98},
+},
+@inproceedings{bg_autoencoder_ad_2,
+  title = {Memorizing Normality to Detect Anomaly: Memory-Augmented Deep
+           Autoencoder for Unsupervised Anomaly Detection},
+  url = {http://dx.doi.org/10.1109/ICCV.2019.00179},
+  DOI = {10.1109/iccv.2019.00179},
+  booktitle = {2019 IEEE/CVF International Conference on Computer Vision (ICCV)},
+  publisher = {IEEE},
+  author = {Gong, Dong and Liu, Lingqiao and Le, Vuong and Saha, Budhaditya and
+            Mansour, Moussa Reda and Venkatesh, Svetha and Van Den Hengel, Anton},
+  year = {2019},
+  month = oct,
+  pages = {1705–1714},
+},
+@article{bg_autoencoder_lidar,
+  title = {Deep Learning Approach for Building Detection Using LiDAR–Orthophoto
+           Fusion},
+  volume = {2018},
+  ISSN = {1687-7268},
+  url = {http://dx.doi.org/10.1155/2018/7212307},
+  DOI = {10.1155/2018/7212307},
+  journal = {Journal of Sensors},
+  publisher = {Wiley},
+  author = {Nahhas, Faten Hamed and Shafri, Helmi Z. M. and Sameen, Maher
+            Ibrahim and Pradhan, Biswajeet and Mansor, Shattri},
+  year = {2018},
+  month = aug,
+  pages = {1–12},
+},
+@article{lidar_denoising_survey,
+  title = {LiDAR Denoising Methods in Adverse Environments: A Review},
+  volume = {25},
+  ISSN = {2379-9153},
+  url = {http://dx.doi.org/10.1109/JSEN.2025.3526175},
+  DOI = {10.1109/jsen.2025.3526175},
+  number = {5},
+  journal = {IEEE Sensors Journal},
+  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
+  author = {Park, Ji-Il and Jo, SeungHyeon and Seo, Hyung-Tae and Park, Jihyuk},
+  year = {2025},
+  month = mar,
+  pages = {7916–7932},
+},
+@inproceedings{lidar_subt_dust_removal,
+  title = {Efficient Real-time Smoke Filtration with 3D LiDAR for Search and
+           Rescue with Autonomous Heterogeneous Robotic Systems},
+  url = {http://dx.doi.org/10.1109/IECON51785.2023.10312303},
+  DOI = {10.1109/iecon51785.2023.10312303},
+  booktitle = {IECON 2023- 49th Annual Conference of the IEEE Industrial
+               Electronics Society},
+  publisher = {IEEE},
+  author = {Kyuroson, Alexander and Koval, Anton and Nikolakopoulos, George},
+  year = {2023},
+  month = oct,
+  pages = {1–7},
 }
 
+
+