Accurate fine-grained object recognition with structure-driven relation graph networks
Fine-grained object recognition (FGOR) aims to learn discriminative features that can
identify the subtle distinctions between visually similar objects. However, less effort has …
identify the subtle distinctions between visually similar objects. However, less effort has …
Artificial intelligent systems for vehicle classification: A survey
Digitalization is revolutionizing our way of life and catalyzing the transformation into smart
city. Intelligent Transportation System (ITS) being an indispensable component of smart city …
city. Intelligent Transportation System (ITS) being an indispensable component of smart city …
Imagenet-hard: The hardest images remaining from a study of the power of zoom and spatial biases in image classification
Image classifiers are information-discarding machines, by design. Yet, how these models
discard information remains mysterious. We hypothesize that one way for image classifiers …
discard information remains mysterious. We hypothesize that one way for image classifiers …
LOFI: LOng-tailed FIne-Grained Network for Food Recognition
JM Rodríguez-De-Vera, IG Estepa… - Proceedings of the …, 2024 - openaccess.thecvf.com
Food recognition plays a crucial role in several healthcare applications. Nevertheless it
presents significant computer vision challenges such as long-tailed and fine-grained …
presents significant computer vision challenges such as long-tailed and fine-grained …
Parsing Objects at a Finer Granularity: A Survey
Fine-grained visual parsing, including fine-grained part segmentation and fine-grained
object recognition, has attracted considerable critical attention due to its importance in many …
object recognition, has attracted considerable critical attention due to its importance in many …
Concept-centric transformers: Enhancing model interpretability through object-centric concept learning within a shared global workspace
Many interpretable AI approaches have been proposed to provide plausible explanations for
a model's decision-making. However, configuring an explainable model that effectively …
a model's decision-making. However, configuring an explainable model that effectively …
A bilinear transformer interactive neural networks-based approach to fine-grained recognition and protection of plant diseases for gardening design
Y Li, L Ma, N Sun - Crop Protection, 2024 - Elsevier
Landscape gardening design is an important part of urban ecology and urban image, which
is of great significance for urban plant protection. Plant diseases are a major challenge that …
is of great significance for urban plant protection. Plant diseases are a major challenge that …
Soft Weight Pruning for Cross-Domain Few-Shot Learning with Unlabeled Target Data
Cross-domain few-shot learning (CDFSL) has received great interest for its effectiveness in
solving the problem of the shift between source and target domains in few-shot scenarios …
solving the problem of the shift between source and target domains in few-shot scenarios …
A deep learning approach for scoring quality in vehicle grading
S Nanayakkara, RGN Meegama - Engineering Applications of Artificial …, 2024 - Elsevier
The demand for used cars is ever-increasing globally, mainly due to availability and
affordability. However, even with such high demand in the used car market, most buyers lack …
affordability. However, even with such high demand in the used car market, most buyers lack …
PartCraft: Crafting Creative Objects by Parts
This paper propels creative control in generative visual AI by allowing users to" select".
Departing from traditional text or sketch-based methods, we for the first time allow users to …
Departing from traditional text or sketch-based methods, we for the first time allow users to …