Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector

doi:doi:10.57702/dn2vz0m7

Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector

A deep learning model that learns subject-level representation from a set of local features. The model represents the image volume as a bag (or set) of local features and can accommodate input images of variable sizes.

BibTex:

@dataset{Sumedha_Singla_and_Mingming_Gong_and_Siamak_Ravanbakhsh_and_Frank_Sciurba_and_Barnabas_Poczos_and_Kayhan_N_Batmanghelich_2024,
    abstract = {A deep learning model that learns subject-level representation from a set of local features. The model represents the image volume as a bag (or set) of local features and can accommodate input images of variable sizes.},
    author = {Sumedha Singla and Mingming Gong and Siamak Ravanbakhsh and Frank Sciurba and Barnabas Poczos and Kayhan N. Batmanghelich},
    doi = {10.57702/dn2vz0m7},
    institution = {No Organization},
    keyword = {'computer vision', 'deep learning', 'image patches', 'local features', 'subject-level representation'},
    month = {dec},
    publisher = {TIB},
    title = {Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector},
    url = {https://service.tib.eu/ldmservice/dataset/subject2vec--generative-discriminative-approach-from-a-set-of-image-patches-to-a-vector},
    year = {2024}
}