Graph-based zero-shot learning for classifying natural and computer-generated image
KV Prasad, A Abdul, B Srikanth, L Paleti… - Multimedia Tools and …, 2024 - Springer
The zero-shot image classification is a stimulating problem that attains the human
recognition level depending upon the tiny quantity of trained images. Image classification …
recognition level depending upon the tiny quantity of trained images. Image classification …
ABNT: Attention Binary Navigation Tree for Fine-Grained Visual Classification
B Ding, X Xu, X Bao, N Yan… - 2024 International Joint …, 2024 - ieeexplore.ieee.org
Fine-grained visual categorization (FGVC) presents a notable challenge owing to the high
intra-class variance and minimal inter-class variability. In multi-stage FGVC tasks, the initial …
intra-class variance and minimal inter-class variability. In multi-stage FGVC tasks, the initial …
[PDF][PDF] EMPHASIZING DATA QUALITY FOR THE IDENTIFICATION OF CHILI VARIETIES IN THE CONTEXT OF SMART AGRICULTURE.
W Suwarningsih, R Kirana, PH Khotimah… - … Journal of Information …, 2024 - ijikm.org
ABSTRACT Aim/Purpose This research aims to evaluate models from meta-learning
techniques, such as Riemannian Model Agnostic Meta-Learning (RMAML), Model-Agnostic …
techniques, such as Riemannian Model Agnostic Meta-Learning (RMAML), Model-Agnostic …
ALMA: Adjustable Location and Multi-Angle Attention for Fine-Grained Visual Classification
B Ding, X Xu, X Bao, N Yan… - 2024 27th International …, 2024 - ieeexplore.ieee.org
Fine-grained visual classification (FGVC) is a challenging but realistic problem that
recognizes objects from common categories with subtle differences. Most previous work …
recognizes objects from common categories with subtle differences. Most previous work …
Ontoloji-Based Generalized Zero-Shot Learning with Generative Networks
E Akdemir, N Barışçı - Gazi Mühendislik Bilimleri Dergisi, 2024 - dergipark.org.tr
Zero-Shot Learning (ZSL) aims to classify images of new categories in the testing phase
without labeled images during training, using examples from categories with labeled images …
without labeled images during training, using examples from categories with labeled images …