| Records |
| Author |
Idoia Ruiz; Joan Serrat |
| Title |
Hierarchical Novelty Detection for Traffic Sign Recognition |
Type |
Journal Article |
| Year |
2022 |
Publication  |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
22 |
Issue |
12 |
Pages |
4389 |
| Keywords |
Novelty detection; hierarchical classification; deep learning; traffic sign recognition; autonomous driving; computer vision |
| Abstract |
Recent works have made significant progress in novelty detection, i.e., the problem of detecting samples of novel classes, never seen during training, while classifying those that belong to known classes. However, the only information this task provides about novel samples is that they are unknown. In this work, we leverage hierarchical taxonomies of classes to provide informative outputs for samples of novel classes. We predict their closest class in the taxonomy, i.e., its parent class. We address this problem, known as hierarchical novelty detection, by proposing a novel loss, namely Hierarchical Cosine Loss that is designed to learn class prototypes along with an embedding of discriminative features consistent with the taxonomy. We apply it to traffic sign recognition, where we predict the parent class semantics for new types of traffic signs. Our model beats state-of-the art approaches on two large scale traffic sign benchmarks, Mapillary Traffic Sign Dataset (MTSD) and Tsinghua-Tencent 100K (TT100K), and performs similarly on natural images benchmarks (AWA2, CUB). For TT100K and MTSD, our approach is able to detect novel samples at the correct nodes of the hierarchy with 81% and 36% of accuracy, respectively, at 80% known class accuracy. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS; 600.154 |
Approved |
no |
| Call Number |
Admin @ si @ RuS2022 |
Serial |
3684 |
| Permanent link to this record |
| |
|
| |
| Author |
Rafael E. Rivadeneira; Angel Sappa; Boris X. Vintimilla; Riad I. Hammoud |
| Title |
A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super-Resolution |
Type |
Journal Article |
| Year |
2022 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
22 |
Issue |
6 |
Pages |
2254 |
| Keywords |
Thermal image super-resolution; unsupervised super-resolution; thermal images; attention module; semiregistered thermal images |
| Abstract |
This paper presents a transfer domain strategy to tackle the limitations of low-resolution thermal sensors and generate higher-resolution images of reasonable quality. The proposed technique employs a CycleGAN architecture and uses a ResNet as an encoder in the generator along with an attention module and a novel loss function. The network is trained on a multi-resolution thermal image dataset acquired with three different thermal sensors. Results report better performance benchmarking results on the 2nd CVPR-PBVS-2021 thermal image super-resolution challenge than state-of-the-art methods. The code of this work is available online. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
MSIAU; |
Approved |
no |
| Call Number |
Admin @ si @ RSV2022b |
Serial |
3688 |
| Permanent link to this record |
| |
|
| |
| Author |
Aura Hernandez-Sabate; Jose Elias Yauri; Pau Folch; Daniel Alvarez; Debora Gil |
| Title |
EEG Dataset Collection for Mental Workload Predictions in Flight-Deck Environment |
Type |
Journal Article |
| Year |
2024 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
24 |
Issue |
4 |
Pages |
1174 |
| Keywords |
|
| Abstract |
High mental workload reduces human performance and the ability to correctly carry out complex tasks. In particular, aircraft pilots enduring high mental workloads are at high risk of failure, even with catastrophic outcomes. Despite progress, there is still a lack of knowledge about the interrelationship between mental workload and brain functionality, and there is still limited data on flight-deck scenarios. Although recent emerging deep-learning (DL) methods using physiological data have presented new ways to find new physiological markers to detect and assess cognitive states, they demand large amounts of properly annotated datasets to achieve good performance. We present a new dataset of electroencephalogram (EEG) recordings specifically collected for the recognition of different levels of mental workload. The data were recorded from three experiments, where participants were induced to different levels of workload through tasks of increasing cognition demand. The first involved playing the N-back test, which combines memory recall with arithmetical skills. The second was playing Heat-the-Chair, a serious game specifically designed to emphasize and monitor subjects under controlled concurrent tasks. The third was flying in an Airbus320 simulator and solving several critical situations. The design of the dataset has been validated on three different levels: (1) correlation of the theoretical difficulty of each scenario to the self-perceived difficulty and performance of subjects; (2) significant difference in EEG temporal patterns across the theoretical difficulties and (3) usefulness for the training and evaluation of AI models. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
IAM |
Approved |
no |
| Call Number |
Admin @ si @ HYF2024 |
Serial |
4019 |
| Permanent link to this record |
| |
|
| |
| Author |
Saad Minhas; Zeba Khanam; Shoaib Ehsan; Klaus McDonald Maier; Aura Hernandez-Sabate |
| Title |
Weather Classification by Utilizing Synthetic Data |
Type |
Journal Article |
| Year |
2022 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
22 |
Issue |
9 |
Pages |
3193 |
| Keywords |
Weather classification; synthetic data; dataset; autonomous car; computer vision; advanced driver assistance systems; deep learning; intelligent transportation systems |
| Abstract |
Weather prediction from real-world images can be termed a complex task when targeting classification using neural networks. Moreover, the number of images throughout the available datasets can contain a huge amount of variance when comparing locations with the weather those images are representing. In this article, the capabilities of a custom built driver simulator are explored specifically to simulate a wide range of weather conditions. Moreover, the performance of a new synthetic dataset generated by the above simulator is also assessed. The results indicate that the use of synthetic datasets in conjunction with real-world datasets can increase the training efficiency of the CNNs by as much as 74%. The article paves a way forward to tackle the persistent problem of bias in vision-based datasets. |
| Address |
21 April 2022 |
| Corporate Author |
|
Thesis |
|
| Publisher |
MDPI |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
IAM; 600.139; 600.159; 600.166; 600.145; |
Approved |
no |
| Call Number |
Admin @ si @ MKE2022 |
Serial |
3761 |
| Permanent link to this record |
| |
|
| |
| Author |
Javier Jimenez; Antonio Lopez; Joan Serrat |
| Title |
Un enfoque ABP aplicado a Ingenieria del Software |
Type |
Miscellaneous |
| Year |
2007 |
Publication |
Seminario Internacional RED–U 2–07 para El desarrollo de la autonomia en el aprendizaje |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
Barcelona (Spain) |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ JLS2007 |
Serial |
937 |
| Permanent link to this record |
| |
|
| |
| Author |
Carles Fernandez; Jordi Gonzalez |
| Title |
Ontology for Semantic Integration in a Cognitive Surveillance System |
Type |
Conference Article |
| Year |
2007 |
Publication |
Semantic Multimedia, 2nd International Conference on Semantics and Digital Media Technologies |
Abbreviated Journal |
|
| Volume |
4816 |
Issue |
|
Pages |
263–263 |
| Keywords |
|
| Abstract |
|
| Address |
Genova (Italy) |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
SAMT’07 |
| Notes |
ISE |
Approved |
no |
| Call Number |
ISE @ ise @ FeG2007 |
Serial |
919 |
| Permanent link to this record |
| |
|
| |
| Author |
Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez |
| Title |
On-line lumen centre detection in gastrointestinal and respiratory endoscopy |
Type |
Conference Article |
| Year |
2013 |
Publication |
Second International Workshop Clinical Image-Based Procedures |
Abbreviated Journal |
|
| Volume |
8361 |
Issue |
|
Pages |
31-38 |
| Keywords |
Lumen centre detection; Bronchoscopy; Colonoscopy |
| Abstract |
We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %). |
| Address |
Nagoya; Japan; September 2013 |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
978-3-319-05665-4 |
Medium |
|
| Area |
800 |
Expedition |
|
Conference |
CLIP |
| Notes |
MV; IAM; 600.047; 600.044; 600.060 |
Approved |
no |
| Call Number |
Admin @ si @ SBG2013 |
Serial |
2302 |
| Permanent link to this record |
| |
|
| |
| Author |
Josep Llados; Gemma Sanchez; Enric Marti |
| Title |
A String-Based Method to Recognize Symbols and Structural Textures in Architectural Plans. |
Type |
Miscellaneous |
| Year |
1997 |
Publication |
Second IAPR Workshop on Graphics Recognition, pp. 287–294. |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ LSM1997 |
Serial |
44 |
| Permanent link to this record |
| |
|
| |
| Author |
David Masip; Jordi Vitria |
| Title |
Real Time Face Detection and Verification for Uncontrolled Environments |
Type |
Miscellaneous |
| Year |
2004 |
Publication |
Second COST 275 Workshop Biometrics on the Internet: Fundamentals, Advances and Applications, 55–58. |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
Vigo |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ MaV2004a |
Serial |
446 |
| Permanent link to this record |
| |
|
| |
| Author |
Xavier Otazu; Olivier Penacchio; Xim Cerda-Company |
| Title |
Brightness and colour induction through contextual influences in V1 |
Type |
Conference Article |
| Year |
2015 |
Publication |
Scottish Vision Group 2015 SGV2015 |
Abbreviated Journal |
|
| Volume |
12 |
Issue |
9 |
Pages |
1208-2012 |
| Keywords |
|
| Abstract |
|
| Address |
Carnoustie; Scotland; March 2015 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
SGV |
| Notes |
NEUROBIT;CIC |
Approved |
no |
| Call Number |
Admin @ si @ OPC2015a |
Serial |
2632 |
| Permanent link to this record |
| |
|
| |
| Author |
Victor M. Campello; Carlos Martin-Isla; Cristian Izquierdo; Andrea Guala; Jose F. Rodriguez Palomares; David Vilades; Martin L. Descalzo; Mahir Karakas; Ersin Cavus; Zahra Zahra Raisi-Estabragh; Steffen E. Petersen; Sergio Escalera; Santiago Segui; Karim Lekadir |
| Title |
Minimising multi-centre radiomics variability through image normalisation: a pilot study |
Type |
Journal Article |
| Year |
2022 |
Publication |
Scientific Reports |
Abbreviated Journal |
ScR |
| Volume |
12 |
Issue |
1 |
Pages |
12532 |
| Keywords |
|
| Abstract |
Radiomics is an emerging technique for the quantification of imaging data that has recently shown great promise for deeper phenotyping of cardiovascular disease. Thus far, the technique has been mostly applied in single-centre studies. However, one of the main difficulties in multi-centre imaging studies is the inherent variability of image characteristics due to centre differences. In this paper, a comprehensive analysis of radiomics variability under several image- and feature-based normalisation techniques was conducted using a multi-centre cardiovascular magnetic resonance dataset. 218 subjects divided into healthy (n = 112) and hypertrophic cardiomyopathy (n = 106, HCM) groups from five different centres were considered. First and second order texture radiomic features were extracted from three regions of interest, namely the left and right ventricular cavities and the left ventricular myocardium. Two methods were used to assess features’ variability. First, feature distributions were compared across centres to obtain a distribution similarity index. Second, two classification tasks were proposed to assess: (1) the amount of centre-related information encoded in normalised features (centre identification) and (2) the generalisation ability for a classification model when trained on these features (healthy versus HCM classification). The results showed that the feature-based harmonisation technique ComBat is able to remove the variability introduced by centre information from radiomic features, at the expense of slightly degrading classification performance. Piecewise linear histogram matching normalisation gave features with greater generalisation ability for classification ( balanced accuracy in between 0.78 ± 0.08 and 0.79 ± 0.09). Models trained with features from images without normalisation showed the worst performance overall ( balanced accuracy in between 0.45 ± 0.28 and 0.60 ± 0.22). In conclusion, centre-related information removal did not imply good generalisation ability for classification. |
| Address |
2022/07/22 |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Nature |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ CMI2022 |
Serial |
3749 |
| Permanent link to this record |
| |
|
| |
| Author |
Iban Berganzo-Besga; Hector A. Orengo; Felipe Lumbreras; Aftab Alam; Rosie Campbell; Petrus J Gerrits; Jonas Gregorio de Souza; Afifa Khan; Maria Suarez Moreno; Jack Tomaney; Rebecca C Roberts; Cameron A Petrie |
| Title |
Curriculum learning-based strategy for low-density archaeological mound detection from historical maps in India and Pakistan |
Type |
Journal Article |
| Year |
2023 |
Publication |
Scientific Reports |
Abbreviated Journal |
ScR |
| Volume |
13 |
Issue |
|
Pages |
11257 |
| Keywords |
|
| Abstract |
This paper presents two algorithms for the large-scale automatic detection and instance segmentation of potential archaeological mounds on historical maps. Historical maps present a unique source of information for the reconstruction of ancient landscapes. The last 100 years have seen unprecedented landscape modifications with the introduction and large-scale implementation of mechanised agriculture, channel-based irrigation schemes, and urban expansion to name but a few. Historical maps offer a window onto disappearing landscapes where many historical and archaeological elements that no longer exist today are depicted. The algorithms focus on the detection and shape extraction of mound features with high probability of being archaeological settlements, mounds being one of the most commonly documented archaeological features to be found in the Survey of India historical map series, although not necessarily recognised as such at the time of surveying. Mound features with high archaeological potential are most commonly depicted through hachures or contour-equivalent form-lines, therefore, an algorithm has been designed to detect each of those features. Our proposed approach addresses two of the most common issues in archaeological automated survey, the low-density of archaeological features to be detected, and the small amount of training data available. It has been applied to all types of maps available of the historic 1″ to 1-mile series, thus increasing the complexity of the detection. Moreover, the inclusion of synthetic data, along with a Curriculum Learning strategy, has allowed the algorithm to better understand what the mound features look like. Likewise, a series of filters based on topographic setting, form, and size have been applied to improve the accuracy of the models. The resulting algorithms have a recall value of 52.61% and a precision of 82.31% for the hachure mounds, and a recall value of 70.80% and a precision of 70.29% for the form-line mounds, which allowed the detection of nearly 6000 mound features over an area of 470,500 km2, the largest such approach to have ever been applied. If we restrict our focus to the maps most similar to those used in the algorithm training, we reach recall values greater than 60% and precision values greater than 90%. This approach has shown the potential to implement an adaptive algorithm that allows, after a small amount of retraining with data detected from a new map, a better general mound feature detection in the same map. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
MSIAU |
Approved |
no |
| Call Number |
Admin @ si @ BOL2023 |
Serial |
3976 |
| Permanent link to this record |
| |
|
| |
| Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez |
| Title |
Stereo Vision Camera Pose Estimation for On-Board Applications |
Type |
Book Chapter |
| Year |
2007 |
Publication |
Scene Reconstruction, Pose Estimation and Traking |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
39-50 |
| Keywords |
|
| Abstract |
|
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Rustam Stolking |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
978-3-902613-06-6 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ SGD2007 |
Serial |
797 |
| Permanent link to this record |
| |
|
| |
| Author |
Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira |
| Title |
Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives |
Type |
Journal Article |
| Year |
2016 |
Publication |
Robotics and Autonomous Systems |
Abbreviated Journal |
RAS |
| Volume |
83 |
Issue |
|
Pages |
312-325 |
| Keywords |
Incremental scene reconstruction; Point clouds; Autonomous vehicles; Polygonal primitives |
| Abstract |
When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Elsevier B.V. |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS; 600.086, 600.076 |
Approved |
no |
| Call Number |
Admin @ si @OSS2016a |
Serial |
2806 |
| Permanent link to this record |
| |
|
| |
| Author |
Angel Sappa; Cristhian A. Aguilera-Carrasco; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo |
| Title |
Monocular visual odometry: A cross-spectral image fusion based approach |
Type |
Journal Article |
| Year |
2016 |
Publication |
Robotics and Autonomous Systems |
Abbreviated Journal |
RAS |
| Volume |
85 |
Issue |
|
Pages |
26-36 |
| Keywords |
Monocular visual odometry; LWIR-RGB cross-spectral imaging; Image fusion |
| Abstract |
This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is empirically obtained by means of a mutual information based evaluation metric. The objective is to have a flexible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odometry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Elsevier B.V. |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS;600.086; 600.076 |
Approved |
no |
| Call Number |
Admin @ si @SAC2016 |
Serial |
2811 |
| Permanent link to this record |
