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Human gesture recognition under degraded environments using 3D-integral imaging and deep learning
(Optical Society of America, 2020)
In this paper, we propose a spatio-temporal human gesture recognition algorithm under degraded conditions using three-dimensional integral imaging and deep learning. The proposed algorithm leverages the advantages of ...
Two-stage procedure based on smoothed ensembles of neural networks applied to weed detection in orange groves
(Elsevier, 2014-07)
The potential impacts of herbicide utilization compel producers to use new methods of weed control. The problem of how to reduce the amount of herbicide and yet maintain crop production has stimulated many researchers to ...
Exploring some practical issues of SVM+: Is really privileged information that helps?
(Elsevier, 2014)
Learning using privileged information (LUPI) is a machine learning paradigm which aims at improving classification by taking advantage of information that is only available at training time —not at test time. SVM+ is an ...
Capsule Networks for Hyperspectral Image Classification
(IEEE, 2018-10)
Convolutional neural networks (CNNs) have recently exhibited an excellent performance in hyperspectral image classification tasks. However, the straightforward CNN-based network architecture still finds obstacles when ...
Hyperspectral Unmixing Based on Dual-Depth Sparse Probabilistic Latent Semantic Analysis
(IEEE, 2018-06)
This paper presents a novel approach for spectral unmixing of remotely sensed hyperspectral data. It exploits probabilistic latent topics in order to take advantage of the semantics pervading the latent topic space when ...
A New Deep Generative Network for Unsupervised Remote Sensing Single-Image Super-Resolution
(IEEE, 2018-11)
Super-resolution (SR) brings an excellent opportunity to improve a wide range of different remote sensing applications. SR techniques are concerned about increasing the image resolution while providing finer spatial details ...
Deep Pyramidal Residual Networks for Spectral-Spatial Hyperspectral Image Classification
(IEEE, 2018-08)
Convolutional neural networks (CNNs) exhibit good performance in image processing tasks, pointing themselves as the current state-of-the-art of deep learning methods. However, the intrinsic complexity of remotely sensed ...
Hypnos: a Hardware and Software Toolkit for Energy-Aware Sensing in Low-Cost IoT Nodes
(Institute of Electrical and Electronics EngineersIEEE, 2022)
Through the Internet of Things, autonomous sensing
devices can be deployed to regularly capture environmental and
other sensor measurements for a variety of usage scenarios.
However, for the market segment of stand-alone, ...
Effects of mitigation of pixel crosstalk in the encoding of complex fields using the double-phase method
(Society of Photo-optical Instrumentation Engineers, 2020)
We report on unwanted effects of pixel cross-talk and its mitigation on the experimental realization
of the double-phase method with phase-only spatial light modulators. We experimentally demonstrate that a
generalized ...
Common-Path Dual-Comb Spectroscopy Using a Single Electro-Optic Modulator
(IEEE, 2020-09-15)
Dual frequency comb (DFC) spectroscopy using electro-optic comb generators stands out for its flexibility, easy implementation, and low cost. Typically, two combs with different line spacing are generated from a common ...