Search
Now showing items 1-7 of 7
Tracking more than 100 arbitrary objects at 25 FPS through deep learning
(Elsevier, 2022)
Most video analytics applications rely on object detectors to localize objects in frames. However, when real-time is a requirement, running the detector at all the frames is usually not possible. This is somewhat circumvented ...
Deep Neural Networks for Chronological Age Estimation From OPG Images
(IEEE, 2020)
Chronological age estimation is crucial labour in many clinical procedures, where the teeth have proven to be one of the best estimators. Although some methods to estimate the age from tooth measurements in orthopantomogram ...
Sparse matrix classification on imbalanced datasets using convolutional neural networks
(IEEE, 2019)
This paper deals with the class imbalance problem in the context of the automatic selection
of the best storage format for a sparse matrix with the aim of maximizing the performance of the sparse
matrix vector multiplication ...
STDnet: Exploiting high resolution feature maps for small object detection
(Elsevier, 2020)
The accuracy of small object detection with convolutional neural networks (ConvNets) lags behind that of larger objects. This can be observed in popular contests like MS COCO. This is in part caused by the lack of specific ...
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
(Elsevier, 2020)
Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era ...
Dual-Window Superpixel Data Augmentation for Hyperspectral Image Classification
(MDPI, 2020)
Deep learning (DL) has been shown to obtain superior results for classification tasks in the field of remote sensing hyperspectral imaging. Superpixel-based techniques can be applied to DL, significantly decreasing training ...
Automated description of the mandible shape by deep learning
(Springer, 2021)
Purpose: The shape of the mandible has been analyzed in a variety of fields, whether to diagnose conditions like osteoporosis or osteomyelitis, in forensics, to estimate biological information such as age, gender, and race ...