Boxcars: 3d boxes as cnn input for improved fine-grained vehicle recognition
We are dealing with the problem of fine-grained vehicle make&model recognition and
verification. Our contribution is showing that extracting additional data from the video stream …
verification. Our contribution is showing that extracting additional data from the video stream …
Vehicle re-identification: an efficient baseline using triplet embedding
In this paper we tackle the problem of vehicle re-identification in a camera network utilizing
triplet embeddings. Re-identification is the problem of matching appearances of objects …
triplet embeddings. Re-identification is the problem of matching appearances of objects …
A unified matrix-based convolutional neural network for fine-grained image classification of wheat leaf diseases
Z Lin, S Mu, F Huang, KA Mateen, M Wang… - IEEE …, 2019 - ieeexplore.ieee.org
Fine-grained image classification methods often suffer from the challenge that the
subordinate categories within an entry-level category can only be distinguished by subtle …
subordinate categories within an entry-level category can only be distinguished by subtle …
Boxcars: Improving fine-grained recognition of vehicles using 3-d bounding boxes in traffic surveillance
In this paper, we focus on fine-grained recognition of vehicles mainly in traffic surveillance
applications. We propose an approach that is orthogonal to recent advancements in fine …
applications. We propose an approach that is orthogonal to recent advancements in fine …
Multi-path deep cnns for fine-grained car recognition
H Wang, J Peng, Y Zhao, X Fu - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Along with the growing demands of intelligent traffic system, how to recognize the category
information of a car from surveillance cameras has been an important task. Fine-grained car …
information of a car from surveillance cameras has been an important task. Fine-grained car …
Deep CNNs with spatially weighted pooling for fine-grained car recognition
Fine-grained car recognition aims to recognize the category information of a car, such as car
make, car model, or even the year of manufacture. A number of recent studies have shown …
make, car model, or even the year of manufacture. A number of recent studies have shown …
Vehicle weight identification system for spatiotemporal load distribution on bridges based on non-contact machine vision technology and deep learning algorithms
Y Zhou, Y Pei, Z Li, L Fang, Y Zhao, W Yi - Measurement, 2020 - Elsevier
Accurate information regarding the weight of vehicle loads plays a significant role in
maintaining the structural health of bridges. However, the only method currently available for …
maintaining the structural health of bridges. However, the only method currently available for …
Vehicle type recognition in surveillance images from labeled web-nature data using deep transfer learning
Vehicle type recognition from surveillance images represents a challenging task in the
domain of intelligent monitoring systems. Recently, deep learning methods have been …
domain of intelligent monitoring systems. Recently, deep learning methods have been …
An efficient fine-grained vehicle recognition method based on part-level feature optimization
L Lu, Y Cai, H Huang, P Wang - Neurocomputing, 2023 - Elsevier
This paper presents an effective method for strengthening the discriminative ability of high-
level deep features by enhancing and aggregating discriminative part-level features for the …
level deep features by enhancing and aggregating discriminative part-level features for the …
Training neural networks for vehicle re-identification
In various examples, a neural network may be trained for use in vehicle re-identification
tasks—eg, matching appearances and classifications of vehicles across frames—in a …
tasks—eg, matching appearances and classifications of vehicles across frames—in a …