Search Results for author:
Found 24 papers, 8 papers with code
Vehicle Occurrence-based Parking Space Detection
Smart-parking solutions use sensors, cameras, and data analysis to improve parking efficiency and reduce traffic congestion.
Fast & Furious: Modelling Malware Detection as Evolving Data Streams
This constant evolution of malware samples causes changes to the data distribution (i. e., concept drifts) that directly affect ML model detection rates, something not considered in the majority of the literature work.
Classifier Pool Generation based on a Two-level Diversity Approach
This paper describes a classifier pool generation method guided by the diversity estimated on the data complexity and classifier decisions.
Machine Learning (In) Security: A Stream of Problems
Machine Learning (ML) has been widely applied to cybersecurity and is considered state-of-the-art for solving many of the open issues in that field.
A Comprehensive Comparison of End-to-End Approaches for Handwritten Digit String Recognition
Over the last decades, most approaches proposed for handwritten digit string recognition (HDSR) have resorted to digit segmentation, which is dominated by heuristics, thereby imposing substantial constraints on the final performance.
Intrapersonal Parameter Optimization for Offline Handwritten Signature Augmentation
The method is used to generate offline signatures in the image and the feature space and train an ASVS.
Legal Document Classification: An Application to Law Area Prediction of Petitions to Public Prosecution Service
In recent years, there has been an increased interest in the application of Natural Language Processing (NLP) to legal documents.
Impact of lung segmentation on the diagnosis and explanation of COVID-19 in chest X-ray images
We assessed the impact of creating a CXR image database from different sources, and the COVID-19 generalization from one source to another.
Computed Tomography (CT)
Explainable artificial intelligence
+2
Single-sample writers -- "Document Filter" and their impacts on writer identification
The writing can be used as an important biometric modality which allows to unequivocally identify an individual.
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.
Meta-learning for fast classifier adaptation to new users of Signature Verification systems
This is particularly challenging for skilled forgeries, where a forger practices imitating the user's signature, and often is able to create forgeries visually close to the original signatures.
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.
Evaluating Competence Measures for Dynamic Regressor Selection
Three DRS systems were compared against individual regressor and static systems that use the Mean and the Median to combine the outputs of the regressors from the ensemble.
Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification
The phenomenon of Adversarial Examples is attracting increasing interest from the Machine Learning community, due to its significant impact to the security of Machine Learning systems.
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses
Research on adversarial examples in computer vision tasks has shown that small, often imperceptible changes to an image can induce misclassification, which has security implications for a wide range of image processing systems.
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.
Fixed-sized representation learning from Offline Handwritten Signatures of different sizes
Methods for learning feature representations for Offline Handwritten Signature Verification have been successfully proposed in recent literature, using Deep Convolutional Neural Networks to learn representations from signature pixels.
A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector
First, in the SSIG dataset, composed of 2, 000 frames from 101 vehicle videos, our system achieved a recognition rate of 93. 53% and 47 Frames Per Second (FPS), performing better than both Sighthound and OpenALPR commercial systems (89. 80% and 93. 03%, respectively) and considerably outperforming previous results (81. 80%).
Ranked #2 on
License Plate Recognition
on SSIG-SegPlate
Multi-scale Forest Species Recognition Systems for Reduced Cost
This work focuses on cost reduction methods for forest species recognition systems.
Learning Features for Offline Handwritten Signature Verification using Deep Convolutional Neural Networks
Verifying the identity of a person using handwritten signatures is challenging in the presence of skilled forgeries, where a forger has access to a person's signature and deliberately attempt to imitate it.
Analyzing features learned for Offline Signature Verification using Deep CNNs
Research on Offline Handwritten Signature Verification explored a large variety of handcrafted feature extractors, ranging from graphology, texture descriptors to interest points.
Writer-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networks
Automatic Offline Handwritten Signature Verification has been researched over the last few decades from several perspectives, using insights from graphology, computer vision, signal processing, among others.
Offline Handwritten Signature Verification - Literature Review
The area of Handwritten Signature Verification has been broadly researched in the last decades, but remains an open research problem.
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.
