{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/improving-landmark-recognition-using-saliency","title":"Improving Landmark Recognition using Saliency detection and Feature classification","arxiv_id":"1811.12748","date":"2018-11-30","proceeding":null,"authors":["Akash Kumar","Sagnik Bhowmick","N. Jayanthi","S. Indu"],"abstract":"Image Landmark Recognition has been one of the most sought-after\nclassification challenges in the field of vision and perception. After so many\nyears of generic classification of buildings and monuments from images, people\nare now focussing upon fine-grained problems - recognizing the category of each\nbuilding or monument. We proposed an ensemble network for the purpose of\nclassification of Indian Landmark Images. To this end, our method gives robust\nclassification by ensembling the predictions from Graph-Based Visual Saliency\n(GBVS) network alongwith supervised feature-based classification algorithms\nsuch as kNN and Random Forest. The final architecture is an adaptive learning\nof all the mentioned networks. The proposed network produces a reliable score\nto eliminate false category cases. Evaluation of our model was done on a new\ndataset, which involves challenges such as landmark clutter, variable scaling,\npartial occlusion, etc.","url_abs":"http://arxiv.org/abs/1811.12748v1","url_pdf":"http://arxiv.org/pdf/1811.12748v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"improving-landmark-recognition-using-saliency","repo_url":"https://github.com/AKASH2907/indian_landmark_recognition","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"landmark-recognition","task_name":"Landmark Recognition"},{"task_slug":"robust-classification","task_name":"Robust classification"},{"task_slug":"saliency-detection","task_name":"Saliency Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}