Search Results for author:
Found 25 papers, 13 papers with code
The Potential of Wearable Sensors for Assessing Patient Acuity in Intensive Care Unit (ICU)
In this study, we evaluated the impact of integrating mobility data collected from wrist-worn accelerometers with clinical data obtained from EHR for developing an AI-driven acuity assessment score.
Open-Set Face Recognition with Maximal Entropy and Objectosphere Loss
MEL modifies the traditional Cross-Entropy loss in favor of increasing the entropy for negative samples and attaches a penalty to known target classes in pursuance of gallery specialization.
Open-set Face Recognition with Neural Ensemble, Maximal Entropy Loss and Feature Augmentation
Open-set face recognition refers to a scenario in which biometric systems have incomplete knowledge of all existing subjects.
Open-set Face Recognition using Ensembles trained on Clustered Data
It is composed of clustering and an ensemble of binary learning algorithms that estimates when query face samples belong to the face gallery and then retrieves their correct identity.
Super-Resolution of License Plate Images Using Attention Modules and Sub-Pixel Convolution Layers
As a result, the generated images have a Structural Similarity Index Measure (SSIM) of less than 0. 10.
Combining Attention Module and Pixel Shuffle for License Plate Super-Resolution
The License Plate Recognition (LPR) field has made impressive advances in the last decade due to novel deep learning approaches combined with the increased availability of training data.
Face Attributes as Cues for Deep Face Recognition Understanding
Deeply learned representations are the state-of-the-art descriptors for face recognition methods.
Stage-Wise Neural Architecture Search
Motivated by this, we propose a NAS approach to efficiently design accurate and low-cost convolutional architectures and demonstrate that an efficient strategy for designing these architectures is to learn the depth stage-by-stage.
The SWAX Benchmark: Attacking Biometric Systems with Wax Figures
A face spoofing attack occurs when an intruder attempts to impersonate someone who carries a gainful authentication clearance.
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction Method
Dimensionality reduction plays an important role in computer vision problems since it reduces computational cost and is often capable of yielding more discriminative data representation.
Skeleton Image Representation for 3D Action Recognition based on Tree Structure and Reference Joints
The proposed representation has the advantage of combining the use of reference joints and a tree structure skeleton.
Ranked #15 on
Action Recognition
on NTU RGB+D 120
An Efficient and Layout-Independent Automatic License Plate Recognition System Based on the YOLO detector
This paper presents an efficient and layout-independent Automatic License Plate Recognition (ALPR) system based on the state-of-the-art YOLO object detector that contains a unified approach for license plate (LP) detection and layout classification to improve the recognition results using post-processing rules.
Ranked #1 on
License Plate Recognition
on Caltech Cars
SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition
Due to the availability of large-scale skeleton datasets, 3D human action recognition has recently called the attention of computer vision community.
Ranked #16 on
Action Recognition
on NTU RGB+D 120
Convolutional Neural Networks for Automatic Meter Reading
This dataset is, to the best of our knowledge, three times larger than the largest public dataset found in the literature and contains a well-defined evaluation protocol to assist the development and evaluation of AMR methods.
Ranked #3 on
Meter Reading
on UFPR-AMR
Pruning Deep Neural Networks using Partial Least Squares
Finally, we show that the proposed method achieves the highest FLOPs reduction and the smallest drop in accuracy when compared to state-of-the-art pruning approaches.
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art
Inspired by this, we conduct an extensive set of experiments that analyze different sample generation processes and validation protocols to indicate the vulnerable points in human activity recognition based on wearable sensor data.
A Content-Based Late Fusion Approach Applied to Pedestrian Detection
We propose a novel method called Content-Based Spatial Consensus (CSBC), which, in addition to relying on spatial consensus, considers the content of the detection windows to learn a weighted-fusion of pedestrian detectors.
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
Latent hypernet: Exploring all Layers from Convolutional Neural Networks
To demonstrate the robustness and accuracy of the LHN, we evaluate it using four different networks architectures in five publicly available HAR datasets based on wearable sensors, which vary in the sampling rate and number of activities.
Activity Recognition based on a Magnitude-Orientation Stream Network
The temporal component of videos provides an important clue for activity recognition, as a number of activities can be reliably recognized based on the motion information.
Kernel Cross-View Collaborative Representation based Classification for Person Re-Identification
It assumes that a probe and its corresponding gallery image are represented with similar coding vectors using individuals from the training set.
Meat adulteration detection through digital image analysis of histological cuts using LBP
Food fraud has been an area of great concern due to its risk to public health, reduction of food quality or nutritional value and for its economic consequences.
Benchmark for License Plate Character Segmentation
In general, ALPR is divided into the following problems: detection of on-track vehicles, license plates detection, segmention of license plate characters and optical character recognition (OCR).
A Mid-level Video Representation based on Binary Descriptors: A Case Study for Pornography Detection
Although these approaches provide good results, they generally have the disadvantage of a high false positive rate since not all images with large areas of skin exposure are necessarily pornographic images, such as people wearing swimsuits or images related to sports.
Deep Representations for Iris, Face, and Fingerprint Spoofing Detection
We assume a very limited knowledge about biometric spoofing at the sensor to derive outstanding spoofing detection systems for iris, face, and fingerprint modalities based on two deep learning approaches.
