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Found 8 papers, 1 papers with code
Automatic Chronic Degenerative Diseases Identification Using Enteric Nervous System Images
In the proposed approach, we have performed the classification task with handcrafted features and deep learning based techniques, also known as non-handcrafted features.
Two-View Fine-grained Classification of Plant Species
Automatic plant classification is a challenging problem due to the wide biodiversity of the existing plant species in a fine-grained scenario.
An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings
An end-to-end solution for handwritten numeral string recognition is proposed, in which the numeral string is considered as composed of objects automatically detected and recognized by a YoLo-based model.
Data Augmentation for Histopathological Images Based on Gaussian-Laplacian Pyramid Blending
Such a problem is troublesome because most of the ML algorithms attempt to optimize a loss function that does not take into account the data imbalance.
Double Transfer Learning for Breast Cancer Histopathologic Image Classification
This work proposes a classification approach for breast cancer histopathologic images (HI) that uses transfer learning to extract features from HI using an Inception-v3 CNN pre-trained with ImageNet dataset.
Histopathologic Image Processing: A Review
In this work we present a literature review about the computing techniques to process HI, including shallow and deep methods.
Segmentation-Free Approaches for Handwritten Numeral String Recognition
This paper presents segmentation-free strategies for the recognition of handwritten numeral strings of unknown length.
A Classifier-free Ensemble Selection Method based on Data Diversity in Random Subspaces
Our scheme is the first ensemble selection method to be presented in the literature based on the concept of data diversity.
