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Found 18 papers, 1 papers with code
Do We Train on Test Data? The Impact of Near-Duplicates on License Plate Recognition
This work draws attention to the large fraction of near-duplicates in the training and test sets of datasets widely adopted in License Plate Recognition (LPR) research.
Evaluation of Different Annotation Strategies for Deployment of Parking Spaces Classification Systems
When using vision-based approaches to classify individual parking spaces between occupied and empty, human experts often need to annotate the locations and label a training set containing images collected in the target parking lot to fine-tune the system.
Multiscale Analysis for Improving Texture Classification
Image pyramid multiresolution representations are a useful data structure for image analysis and manipulation over a spectrum of spatial scales.
A New Periocular Dataset Collected by Mobile Devices in Unconstrained Scenarios
Thus, the use of datasets containing many subjects is essential to assess biometric systems' capacity to extract discriminating information from the periocular region.
Ranked #1 on
Image Classification
on Imbalanced CUB-200-2011
A multimodal approach for multi-label movie genre classification
Based on the F-Score metric, our best result, 0. 628, was obtained by the fusion of a classifier created using LSTM on the synopses, and a classifier created using CNN on movie trailer frames.
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.
CNN Hyperparameter tuning applied to Iris Liveness Detection
The iris pattern has significantly improved the biometric recognition field due to its high level of stability and uniqueness.
Ocular Recognition Databases and Competitions: A Survey
The use of the iris and periocular region as biometric traits has been extensively investigated, mainly due to the singularity of the iris features and the use of the periocular region when the image resolution is not sufficient to extract iris information.
Deep Representations for Cross-spectral Ocular Biometrics
One of the major challenges in ocular biometrics is the cross-spectral scenario, i. e., how to match images acquired in different wavelengths (typically visible (VIS) against near-infrared (NIR)).
Image Retrieval and Pattern Spotting using Siamese Neural Network
This paper presents a novel approach for image retrieval and pattern spotting in document image collections.
Memory Integrity of CNNs for Cross-Dataset Facial Expression Recognition
A common way to circumvent the lack of data is to use CNNs trained on large datasets of different domains and fine-tuning the layers of such networks to the target domain.
Facial Expression Recognition
Facial Expression Recognition (FER)
Texture CNN for Thermoelectric Metal Pipe Image Classification
In this paper, the concept of representation learning based on deep neural networks is applied as an alternative to the use of handcrafted features in a method for automatic visual inspection of corroded thermoelectric metallic pipes.
Robust Iris Segmentation Based on Fully Convolutional Networks and Generative Adversarial Networks
In this paper, two approaches for robust iris segmentation based on Fully Convolutional Networks (FCNs) and Generative Adversarial Networks (GANs) are described.
The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments
The use of iris as a biometric trait is widely used because of its high level of distinction and uniqueness.
Fully Convolutional Networks and Generative Adversarial Networks Applied to Sclera Segmentation
The initial and paramount step for performing this type of recognition is the segmentation of the region of interest, i. e. the sclera.
People Counting in Crowded and Outdoor Scenes using a Hybrid Multi-Camera Approach
For such an aim, corner points are extracted from groups of people in a foreground image and computed by a learning algorithm which estimates the number of people in the scene.
PKLot-A robust dataset for parking lot classification
To mitigate this difficulty, in this paper we introduce a new parking lot dataset composed of 695, 899 images captured from two parking lots with three different camera views.
