{"id":2035,"date":"2025-02-13T11:59:00","date_gmt":"2025-02-13T02:59:00","guid":{"rendered":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/?p=2035"},"modified":"2026-07-24T16:49:40","modified_gmt":"2026-07-24T07:49:40","slug":"creation-of-an-image-classification-model-with-data-augmentation-for-mixed-breed-dog-identificationfy-2024-graduation-research","status":"publish","type":"post","link":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/en\/archives\/2035","title":{"rendered":"Creation of an Image Classification Model with Data Augmentation for Mixed-Breed Dog Identification(FY 2024 Graduation Research)"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">This study evaluates an image classification model developed with data augmentation to identify mixed-breed dogs. While their popularity is rising, identifying mixed-breeds remains challenging due to overlapping parental traits and the purebred focus of existing systems. We trained a model on three mixed breeds\u2014Maltese and Toy Poodle, Pomeranian and Toy Poodle, and Chihuahua and Dachshund\u2014using 250 augmented images per breed, and visualized key focus areas using Grad-CAM.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The classification achieved high performance for Maltese and Toy Poodle and Chihuahua and Dachshund (recall: 1.00, precision: 0.89), but lower precision for Pomeranian and Toy Poodle (0.53), indicating a tendency for misclassification. Grad-CAM visualization confirmed that the model focused on distinct features depending on the breed, such as the face, ears, or facial markings (Figure 1).<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"435\" height=\"150\" src=\"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wordpress\/wp-content\/uploads\/2026\/07\/20260721_\u30b3\u30f3\u30c6\u30f3\u30c4B-1.png\" alt=\"\" class=\"wp-image-2033\" style=\"aspect-ratio:2.8998958333333333;width:840px;height:auto\" srcset=\"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wordpress\/wp-content\/uploads\/2026\/07\/20260721_\u30b3\u30f3\u30c6\u30f3\u30c4B-1.png 435w, https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wordpress\/wp-content\/uploads\/2026\/07\/20260721_\u30b3\u30f3\u30c6\u30f3\u30c4B-1-300x103.png 300w\" sizes=\"auto, (max-width: 435px) 100vw, 435px\" \/><figcaption class=\"wp-element-caption\">Figure 1. Grad-CAM visualization of three mixed-breed dogs<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Future work includes expanding training data and refining the architecture to realize a practical web-based system.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This study evaluates an image classification model developed with data augmentation to identify mixed-breed dogs.&hellip;<\/p>\n","protected":false},"author":19,"featured_media":2033,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_lmt_disableupdate":"","_lmt_disable":"","_locale":"en_US","_original_post":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/?p=2031","footnotes":""},"categories":[24],"tags":[],"class_list":["post-2035","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-24","en-US"],"modified_by":"\u5e0c\u76f4\u846d\u539f","_links":{"self":[{"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/posts\/2035","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/comments?post=2035"}],"version-history":[{"count":2,"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/posts\/2035\/revisions"}],"predecessor-version":[{"id":2051,"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/posts\/2035\/revisions\/2051"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/media\/2033"}],"wp:attachment":[{"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/media?parent=2035"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/categories?post=2035"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.comm.tcu.ac.jp\/masuda-lab\/wp-json\/wp\/v2\/tags?post=2035"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}