|
Records |
Links |
|
Author |
Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
|
|
Title |
3D Texton Spaces for color-texture retrieval |
Type |
Conference Article |
|
Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
6111 |
Issue |
|
Pages |
354–363 |
|
|
Keywords |
|
|
|
Abstract |
Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
A.C. Campilho and M.S. Kamel |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-13771-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIAR |
|
|
Notes |
CIC |
Approved |
no |
|
|
Call Number |
CAT @ cat @ ASV2010a |
Serial |
1325 |
|
Permanent link to this record |
|
|
|
|
Author |
Naveen Onkarappa; Angel Sappa |
|
|
Title |
On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow |
Type |
Conference Article |
|
Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
6111 |
Issue |
|
Pages |
230-239 |
|
|
Keywords |
|
|
|
Abstract |
This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach. |
|
|
Address |
Povoa de Varzim (Portugal) |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-13771-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIAR |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ OnS2010 |
Serial |
1342 |
|
Permanent link to this record |
|
|
|
|
Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
|
|
Title |
Monocular Depth-based Background Estimation |
Type |
Conference Article |
|
Year |
2012 |
Publication |
7th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
323-328 |
|
|
Keywords |
|
|
|
Abstract |
In this paper, we address the problem of reconstructing the background of a scene from a video sequence with occluding objects. The images are taken by hand-held cameras. Our method composes the background by selecting the appropriate pixels from previously aligned input images. To do that, we minimize a cost function that penalizes the deviations from the following assumptions: background represents objects whose distance to the camera is maximal, and background objects are stationary. Distance information is roughly obtained by a supervised learning approach that allows us to distinguish between close and distant image regions. Moving foreground objects are filtered out by using stationariness and motion boundary constancy measurements. The cost function is minimized by a graph cuts method. We demonstrate the applicability of our approach to recover an occlusion-free background in a set of sequences. |
|
|
Address |
Roma |
|
|
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 |
VISAPP |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e |
Serial |
2012 |
|
Permanent link to this record |
|
|
|
|
Author |
Pedro Martins; Carlo Gatta; Paulo Carvalho |
|
|
Title |
Feature-driven Maximally Stable Extremal Regions |
Type |
Conference Article |
|
Year |
2012 |
Publication |
7th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
490-497 |
|
|
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 |
VISAPP |
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ MGC2012 |
Serial |
2139 |
|
Permanent link to this record |
|
|
|
|
Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
|
|
Title |
Visual Registration Method For A Low Cost Robot: Computer Vision Systems |
Type |
Conference Article |
|
Year |
2009 |
Publication |
7th International Conference on Computer Vision Systems |
Abbreviated Journal |
|
|
|
Volume |
5815 |
Issue |
|
Pages |
204–214 |
|
|
Keywords |
|
|
|
Abstract |
An autonomous mobile robot must face the correspondence or data association problem in order to carry out tasks like place recognition or unknown environment mapping. In order to put into correspondence two maps, most methods estimate the transformation relating the maps from matches established between low level feature extracted from sensor data. However, finding explicit matches between features is a challenging and computationally expensive task. In this paper, we propose a new method to align obstacle maps without searching explicit matches between features. The maps are obtained from a stereo pair. Then, we use a vocabulary tree approach to identify putative corresponding maps followed by the Newton minimization algorithm to find the transformation that relates both maps. The proposed method is evaluated in a typical office environment showing good performance. |
|
|
Address |
Belgica |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-04666-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICVS |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ ATR2009b |
Serial |
1247 |
|
Permanent link to this record |
|
|
|
|
Author |
Agata Lapedriza; David Masip; Jordi Vitria |
|
|
Title |
Face Verification using External Features |
Type |
Miscellaneous |
|
Year |
2006 |
Publication |
7th International Conference on Automatic Face and Gesture Recognition (FG´06), 132– 137 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Southampton (United Kingdom) |
|
|
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 @ LMV2006a |
Serial |
707 |
|
Permanent link to this record |
|
|
|
|
Author |
Jose Seabra; F. Javier Sanchez; Francesco Ciompi; Petia Radeva |
|
|
Title |
Ultrasonographic Plaque Characterization using a Rayleigh Mixture Model |
Type |
Conference Article |
|
Year |
2010 |
Publication |
7th IEEE International Symposium on Biomedical Imaging |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1–4 |
|
|
Keywords |
|
|
|
Abstract |
From Nano to Macro
A correct modelling of tissue morphology is determinant for the identification of vulnerable plaques. This paper aims at describing the plaque composition by means of a Rayleigh Mixture Model applied to ultrasonic data. The effectiveness of using a mixture of distributions is established through synthetic and real ultrasonic data samples. Furthermore, the proposed mixture model is used in a plaque classification problem in Intravascular Ultrasound (IVUS) images of coronary plaques. A classifier tested on a set of 67 in-vitro plaques, yields an overall accuracy of 86% and sensitivity of 92%, 94% and 82%, for fibrotic, calcified and lipidic tissues, respectively. These results strongly suggest that different plaques types can be distinguished by means of the coefficients and Rayleigh parameters of the mixture distribution. |
|
|
Address |
Rotterdam (Netherlands) |
|
|
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 |
1945-7928 |
ISBN |
978-1-4244-4125-9 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ISBI |
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ SSC2010 |
Serial |
1366 |
|
Permanent link to this record |
|
|
|
|
Author |
Zhengying Liu; Adrien Pavao; Zhen Xu; Sergio Escalera; Isabelle Guyon; Julio C. S. Jacques Junior; Meysam Madadi; Sebastien Treguer |
|
|
Title |
How far are we from true AutoML: reflection from winning solutions and results of AutoDL challenge |
Type |
Conference Article |
|
Year |
2020 |
Publication |
7th ICML Workshop on Automated Machine Learning |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Following the completion of the AutoDL challenge (the final challenge in the ChaLearn
AutoDL challenge series 2019), we investigate winning solutions and challenge results to
answer an important motivational question: how far are we from achieving true AutoML?
On one hand, the winning solutions achieve good (accurate and fast) classification performance on unseen datasets. On the other hand, all winning solutions still contain a
considerable amount of hard-coded knowledge on the domain (or modality) such as image,
video, text, speech and tabular. This form of ad-hoc meta-learning could be replaced by
more automated forms of meta-learning in the future. Organizing a meta-learning challenge could help forging AutoML solutions that generalize to new unseen domains (e.g.
new types of sensor data) as well as gaining insights on the AutoML problem from a more
fundamental point of view. The datasets of the AutoDL challenge are a resource that can
be used for further benchmarks and the code of the winners has been outsourced, which is
a big step towards “democratizing” Deep Learning. |
|
|
Address |
Virtual; July 2020 |
|
|
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 |
ICML |
|
|
Notes |
HUPBA |
Approved |
no |
|
|
Call Number |
Admin @ si @ LPX2020 |
Serial |
3502 |
|
Permanent link to this record |
|
|
|
|
Author |
Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; Horst Bunke |
|
|
Title |
A Recursive Embedding Approach to Median Graph Computation |
Type |
Conference Article |
|
Year |
2009 |
Publication |
7th IAPR – TC–15 Workshop on Graph–Based Representations in Pattern Recognition |
Abbreviated Journal |
|
|
|
Volume |
5534 |
Issue |
|
Pages |
113–123 |
|
|
Keywords |
|
|
|
Abstract |
The median graph has been shown to be a good choice to infer a representative of a set of graphs. It has been successfully applied to graph-based classification and clustering. Nevertheless, its computation is extremely complex. Several approaches have been presented up to now based on different strategies. In this paper we present a new approximate recursive algorithm for median graph computation based on graph embedding into vector spaces. Preliminary experiments on three databases show that this new approach is able to obtain better medians than the previous existing approaches. |
|
|
Address |
Venice, Italy |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-02123-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
GBR |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
DAG @ dag @ FKV2009 |
Serial |
1173 |
|
Permanent link to this record |
|
|
|
|
Author |
Albert Clapes; Miguel Reyes; Sergio Escalera |
|
|
Title |
User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis |
Type |
Conference Article |
|
Year |
2012 |
Publication |
7th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
|
Volume |
7378 |
Issue |
|
Pages |
1-11 |
|
|
Keywords |
|
|
|
Abstract |
We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches. |
|
|
Address |
Mallorca |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-31566-4 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
AMDO |
|
|
Notes |
HUPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ CRE2012 |
Serial |
2010 |
|
Permanent link to this record |
|
|
|
|
Author |
Wenjuan Gong; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
|
|
Title |
A New Image Dataset on Human Interactions |
Type |
Conference Article |
|
Year |
2012 |
Publication |
7th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
|
Volume |
7378 |
Issue |
|
Pages |
204-209 |
|
|
Keywords |
|
|
|
Abstract |
This article describes a new collection of still image dataset which are dedicated to interactions between people. Human action recognition from still images have been a hot topic recently, but most of them are actions performed by a single person, like running, walking, riding bikes, phoning and so on and there is no interactions between people in one image. The dataset collected in this paper are concentrating on human interaction between two people aiming to explore this new topic in the research area of action recognition from still images. |
|
|
Address |
Mallorca |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-31566-4 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
AMDO |
|
|
Notes |
ISE |
Approved |
no |
|
|
Call Number |
Admin @ si @ GGT2012 |
Serial |
2030 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Escalera |
|
|
Title |
Human Behavior Analysis From Depth Maps |
Type |
Conference Article |
|
Year |
2012 |
Publication |
7th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
|
Volume |
7378 |
Issue |
|
Pages |
282-292 |
|
|
Keywords |
|
|
|
Abstract |
Pose Recovery (PR) and Human Behavior Analysis (HBA) have been a main focus of interest from the beginnings of Computer Vision and Machine Learning. PR and HBA were originally addressed by the analysis of still images and image sequences. More recent strategies consisted of Motion Capture technology (MOCAP), based on the synchronization of multiple cameras in controlled environments; and the analysis of depth maps from Time-of-Flight (ToF) technology, based on range image recording from distance sensor measurements. Recently, with the appearance of the multi-modal RGBD information provided by the low cost Kinect \textsfTM sensor (from RGB and Depth, respectively), classical methods for PR and HBA have been redefined, and new strategies have been proposed. In this paper, the recent contributions and future trends of multi-modal RGBD data analysis for PR and HBA are reviewed and discussed. |
|
|
Address |
Mallorca |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Heidelberg |
Place of Publication |
|
Editor |
F.J. Perales; R.B. Fisher; T.B. Moeslund |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-31566-4 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
AMDO |
|
|
Notes |
MILAB; HuPBA |
Approved |
no |
|
|
Call Number |
Admin @ si @ Esc2012 |
Serial |
2040 |
|
Permanent link to this record |
|
|
|
|
Author |
Jordi Gonzalez; Javier Varona; Xavier Roca; Juan J. Villanueva |
|
|
Title |
Situation Graph Trees for Human Behavior Modeling |
Type |
Miscellaneous |
|
Year |
2004 |
Publication |
7th Catalan Conference for Artificial Intelligence (CCIA’2004) |
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 |
ISE |
Approved |
no |
|
|
Call Number |
ISE @ ise @ GVR2004b |
Serial |
498 |
|
Permanent link to this record |
|
|
|
|
Author |
Vacit Oguz Yazici; Joost Van de Weijer; Arnau Ramisa |
|
|
Title |
Color Naming for Multi-Color Fashion Items |
Type |
Conference Article |
|
Year |
2018 |
Publication |
6th World Conference on Information Systems and Technologies |
Abbreviated Journal |
|
|
|
Volume |
747 |
Issue |
|
Pages |
64-73 |
|
|
Keywords |
Deep learning; Color; Multi-label |
|
|
Abstract |
There exists a significant amount of research on color naming of single colored objects. However in reality many fashion objects consist of multiple colors. Currently, searching in fashion datasets for multi-colored objects can be a laborious task. Therefore, in this paper we focus on color naming for images with multi-color fashion items. We collect a dataset, which consists of images which may have from one up to four colors. We annotate the images with the 11 basic colors of the English language. We experiment with several designs for deep neural networks with different losses. We show that explicitly estimating the number of colors in the fashion item leads to improved results. |
|
|
Address |
Naples; March 2018 |
|
|
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 |
WORLDCIST |
|
|
Notes |
LAMP; 600.109; 601.309; 600.120 |
Approved |
no |
|
|
Call Number |
Admin @ si @ YWR2018 |
Serial |
3161 |
|
Permanent link to this record |
|
|
|
|
Author |
Adriana Romero; Carlo Gatta; Gustavo Camps-Valls |
|
|
Title |
Unsupervised Deep Feature Extraction Of Hyperspectral Images |
Type |
Conference Article |
|
Year |
2014 |
Publication |
6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
Convolutional networks; deep learning; sparse learning; feature extraction; hyperspectral image classification |
|
|
Abstract |
This paper presents an effective unsupervised sparse feature learning algorithm to train deep convolutional networks on hyperspectral images. Deep convolutional hierarchical representations are learned and then used for pixel classification. Features in lower layers present less abstract representations of data, while higher layers represent more abstract and complex characteristics. We successfully illustrate the performance of the extracted representations in a challenging AVIRIS hyperspectral image classification problem, compared to standard dimensionality reduction methods like principal component analysis (PCA) and its kernel counterpart (kPCA). The proposed method largely outperforms the previous state-ofthe-art results on the same experimental setting. Results show that single layer networks can extract powerful discriminative features only when the receptive field accounts for neighboring pixels. Regarding the deep architecture, we can conclude that: (1) additional layers in a deep architecture significantly improve the performance w.r.t. single layer variants; (2) the max-pooling step in each layer is mandatory to achieve satisfactory results; and (3) the performance gain w.r.t. the number of layers is upper bounded, since the spatial resolution is reduced at each pooling, resulting in too spatially coarse output features. |
|
|
Address |
Lausanne; Switzerland; June 2014 |
|
|
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 |
WHISPERS |
|
|
Notes |
MILAB; LAMP; 600.079 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RGC2014 |
Serial |
2513 |
|
Permanent link to this record |