| Records |
| Author |
Maryam Asadi-Aghbolaghi; Hugo Bertiche; Vicent Roig; Shohreh Kasaei; Sergio Escalera |
| Title |
Action Recognition from RGB-D Data: Comparison and Fusion of Spatio-temporal Handcrafted Features and Deep Strategies |
Type |
Conference Article |
| Year |
2017 |
Publication |
Chalearn Workshop on Action, Gesture, and Emotion Recognition: Large Scale Multimodal Gesture Recognition and Real versus Fake expressed emotions at ICCV |
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Venice; Italy; October 2017 |
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ICCVW |
| Notes |
HUPBA; no menciona |
Approved |
no |
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Admin @ si @ ABR2017 |
Serial |
3068 |
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| Author |
Ana Maria Ares; Jorge Bernal; Maria Jesus Nozal; F. Javier Sanchez; Jose Bernal |
| Title |
Results of the use of Kahoot! gamification tool in a course of Chemistry |
Type |
Conference Article |
| Year |
2018 |
Publication |
4th International Conference on Higher Education Advances |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1215-1222 |
| Keywords |
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| Abstract |
The present study examines the use of Kahoot! as a gamification tool to explore mixed learning strategies. We analyze its use in two different groups of a theoretical subject of the third course of the Degree in Chemistry. An empirical-analytical methodology was used using Kahoot! in two different groups of students, with different frequencies. The academic results of these two group of students were compared between them and with those obtained in the previous course, in which Kahoot! was not employed, with the aim of measuring the evolution in the students´ knowledge. The results showed, in all cases, that the use of Kahoot! has led to a significant increase in the overall marks, and in the number of students who passed the subject. Moreover, some differences were also observed in students´ academic performance according to the group. Finally, it can be concluded that the use of a gamification tool (Kahoot!) in a university classroom had generally improved students´ learning and marks, and that this improvement is more prevalent in those students who have achieved a better Kahoot! performance. |
| Address |
Valencia; June 2018 |
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HEAD |
| Notes |
MV; no proj |
Approved |
no |
| Call Number |
Admin @ si @ ABN2018 |
Serial |
3246 |
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| Author |
Tadashi Araki; Sumit K. Banchhor; Narendra D. Londhe; Nobutaka Ikeda; Petia Radeva; Devarshi Shukla; Luca Saba; Antonella Balestrieri; Andrew Nicolaides; Shoaib Shafique; John R. Laird; Jasjit S. Suri |
| Title |
Reliable and Accurate Calcium Volume Measurement in Coronary Artery Using Intravascular Ultrasound Videos |
Type |
Journal Article |
| Year |
2016 |
Publication |
Journal of Medical Systems |
Abbreviated Journal |
JMS |
| Volume |
40 |
Issue |
3 |
Pages |
51:1-51:20 |
| Keywords |
Interventional cardiology; Atherosclerosis; Coronary arteries; IVUS; calcium volume; Soft computing; Performance Reliability; Accuracy |
| Abstract |
Quantitative assessment of calcified atherosclerotic volume within the coronary artery wall is vital for cardiac interventional procedures. The goal of this study is to automatically measure the calcium volume, given the borders of coronary vessel wall for all the frames of the intravascular ultrasound (IVUS) video. Three soft computing fuzzy classification techniques were adapted namely Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) for automated segmentation of calcium regions and volume computation. These methods were benchmarked against previously developed threshold-based method. IVUS image data sets (around 30,600 IVUS frames) from 15 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/s). Calcium mean volume for FCM, K-means, HMRF and threshold-based method were 37.84 ± 17.38 mm3, 27.79 ± 10.94 mm3, 46.44 ± 19.13 mm3 and 35.92 ± 16.44 mm3 respectively. Cross-correlation, Jaccard Index and Dice Similarity were highest between FCM and threshold-based method: 0.99, 0.92 ± 0.02 and 0.95 + 0.02 respectively. Student’s t-test, z-test and Wilcoxon-test are also performed to demonstrate consistency, reliability and accuracy of the results. Given the vessel wall region, the system reliably and automatically measures the calcium volume in IVUS videos. Further, we validated our system against a trained expert using scoring: K-means showed the best performance with an accuracy of 92.80 %. Out procedure and protocol is along the line with method previously published clinically. |
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MILAB; |
Approved |
no |
| Call Number |
Admin @ si @ ABL2016 |
Serial |
2729 |
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| Author |
Cristhian Aguilera; Fernando Barrera; Felipe Lumbreras; Angel Sappa; Ricardo Toledo |
| Title |
Multispectral Image Feature Points |
Type |
Journal Article |
| Year |
2012 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
12 |
Issue |
9 |
Pages |
12661-12672 |
| Keywords |
multispectral image descriptor; color and infrared images; feature point descriptor |
| Abstract |
Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art. |
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ADAS |
Approved |
no |
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Admin @ si @ ABL2012 |
Serial |
2154 |
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| Author |
Marina Alberti; Simone Balocco; Carlo Gatta; Francesco Ciompi; Oriol Pujol; Joana Silva; Xavier Carrillo; Petia Radeva |
| Title |
Automatic Bifurcation Detection in Coronary IVUS Sequences |
Type |
Journal Article |
| Year |
2012 |
Publication |
IEEE Transactions on Biomedical Engineering |
Abbreviated Journal |
TBME |
| Volume |
59 |
Issue |
4 |
Pages |
1022-2031 |
| Keywords |
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| Abstract |
In this paper, we present a fully automatic method which identifies every bifurcation in an intravascular ultrasound (IVUS) sequence, the corresponding frames, the angular orientation with respect to the IVUS acquisition, and the extension. This goal is reached using a two-level classification scheme: first, a classifier is applied to a set of textural features extracted from each image of a sequence. A comparison among three state-of-the-art discriminative classifiers (AdaBoost, random forest, and support vector machine) is performed to identify the most suitable method for the branching detection task. Second, the results are improved by exploiting contextual information using a multiscale stacked sequential learning scheme. The results are then successively refined using a-priori information about branching dimensions and geometry. The proposed approach provides a robust tool for the quick review of pullback sequences, facilitating the evaluation of the lesion at bifurcation sites. The proposed method reaches an F-Measure score of 86.35%, while the F-Measure scores for inter- and intraobserver variability are 71.63% and 76.18%, respectively. The obtained results are positive. Especially, considering the branching detection task is very challenging, due to high variability in bifurcation dimensions and appearance. |
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0018-9294 |
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| Notes |
MILAB;HuPBA |
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no |
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Admin @ si @ ABG2012 |
Serial |
1996 |
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| Author |
Fernando Alonso; Xavier Baro; Sergio Escalera; Jordi Gonzalez; Martha Mackay; Anna Serrahima |
| Title |
CARE RESPITE: TAKING CARE OF THE CAREGIVERS, Theme 5 The Strategic use of Mobile and Digital Health and Care Solutions |
Type |
Conference Article |
| Year |
2016 |
Publication |
16th International Conference for Integrated Care |
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Poster |
| Address |
Barcelona; Spain; May 2016 |
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Conference |
ICIC |
| Notes |
HuPBA; ISE;MV |
Approved |
no |
| Call Number |
Admin @ si @ ABE2016 |
Serial |
2855 |
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| Author |
Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva |
| Title |
Automatic non-rigid temporal alignment of IVUS sequences: method and quantitative validation |
Type |
Journal Article |
| Year |
2013 |
Publication |
Ultrasound in Medicine and Biology |
Abbreviated Journal |
UMB |
| Volume |
39 |
Issue |
9 |
Pages |
1698-712 |
| Keywords |
Intravascular ultrasound; Dynamic time warping; Non-rigid alignment; Sequence matching; Partial overlapping strategy |
| Abstract |
Clinical studies on atherosclerosis regression/progression performed by intravascular ultrasound analysis would benefit from accurate alignment of sequences of the same patient before and after clinical interventions and at follow-up. In this article, a methodology for automatic alignment of intravascular ultrasound sequences based on the dynamic time warping technique is proposed. The non-rigid alignment is adapted to the specific task by applying it to multidimensional signals describing the morphologic content of the vessel. Moreover, dynamic time warping is embedded into a framework comprising a strategy to address partial overlapping between acquisitions and a term that regularizes non-physiologic temporal compression/expansion of the sequences. Extensive validation is performed on both synthetic and in vivo data. The proposed method reaches alignment errors of approximately 0.43 mm for pairs of sequences acquired during the same intervention phase and 0.77 mm for pairs of sequences acquired at successive intervention stages. |
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| Notes |
MILAB |
Approved |
no |
| Call Number |
Admin @ si @ ABC2013 |
Serial |
2313 |
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| Author |
Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva |
| Title |
Automatic Non-Rigid Temporal Alignment of IVUS Sequences |
Type |
Conference Article |
| Year |
2012 |
Publication |
15th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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| Volume |
1 |
Issue |
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Pages |
642-650 |
| Keywords |
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| Abstract |
Clinical studies on atherosclerosis regression/progression performed by Intravascular Ultrasound analysis require the alignment of pullbacks of the same patient before and after clinical interventions. In this paper, a methodology for the automatic alignment of IVUS sequences based on the Dynamic Time Warping technique is proposed. The method is adapted to the specific IVUS alignment task by applying the non-rigid alignment technique to multidimensional morphological signals, and by introducing a sliding window approach together with a regularization term. To show the effectiveness of our method, an extensive validation is performed both on synthetic data and in-vivo IVUS sequences. The proposed method is robust to stent deployment and post dilation surgery and reaches an alignment error of approximately 0.7 mm for in-vivo data, which is comparable to the inter-observer variability. |
| Address |
Nice, France |
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Springer-Verlag Berlin, Heidelberg |
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978-3-642-33414-6 |
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MICCAI |
| Notes |
MILAB |
Approved |
no |
| Call Number |
Admin @ si @ ABC2012 |
Serial |
2168 |
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| Author |
Joan Arnedo-Moreno; D. Bañeres; Xavier Baro; S. Caballe; S. Guerrero; L. Porta; J. Prieto |
| Title |
Va-ID: A trust-based virtual assessment system |
Type |
Conference Article |
| Year |
2014 |
Publication |
6th International Conference on Intelligent Networking and Collaborative Systems |
Abbreviated Journal |
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Issue |
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Pages |
328 - 335 |
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| Abstract |
Even though online education is a very important pillar of lifelong education, institutions are still reluctant to wager for a fully online educational model. At the end, they keep relying on on-site assessment systems, mainly because fully virtual alternatives do not have the deserved social recognition or credibility. Thus, the design of virtual assessment systems that are able to provide effective proof of student authenticity and authorship and the integrity of the activities in a scalable and cost efficient manner would be very helpful. This paper presents ValID, a virtual assessment approach based on a continuous trust level evaluation between students and the institution. The current trust level serves as the main mechanism to dynamically decide which kind of controls a given student should be subjected to, across different courses in a degree. The main goal is providing a fair trade-off between security, scalability and cost, while maintaining the perceived quality of the educational model. |
| Address |
Salerna; Italy; September 2014 |
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ISBN |
978-1-4799-6386-7 |
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INCOS |
| Notes |
OR; HuPBA;MV |
Approved |
no |
| Call Number |
Admin @ si @ ABB2014 |
Serial |
2620 |
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| Author |
Reza Azad; Afshin Bozorgpour; Maryam Asadi-Aghbolaghi; Dorit Merhof; Sergio Escalera |
| Title |
Deep Frequency Re-Calibration U-Net for Medical Image Segmentation |
Type |
Conference Article |
| Year |
2021 |
Publication |
IEEE/CVF International Conference on Computer Vision Workshops |
Abbreviated Journal |
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Issue |
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Pages |
3274-3283 |
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| Abstract |
We present a novel solution to the garment animation problem through deep learning. Our contribution allows animating any template outfit with arbitrary topology and geometric complexity. Recent works develop models for garment edition, resizing and animation at the same time by leveraging the support body model (encoding garments as body homotopies). This leads to complex engineering solutions that suffer from scalability, applicability and compatibility. By limiting our scope to garment animation only, we are able to propose a simple model that can animate any outfit, independently of its topology, vertex order or connectivity. Our proposed architecture maps outfits to animated 3D models into the standard format for 3D animation (blend weights and blend shapes matrices), automatically providing of compatibility with any graphics engine. We also propose a methodology to complement supervised learning with an unsupervised physically based learning that implicitly solves collisions and enhances cloth quality. |
| Address |
VIRTUAL; October 2021 |
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ICCVW |
| Notes |
HUPBA; no proj |
Approved |
no |
| Call Number |
Admin @ si @ ABA2021 |
Serial |
3645 |
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| Author |
Cristhian A. Aguilera-Carrasco; C. Aguilera; Angel Sappa |
| Title |
Melamine Faced Panels Defect Classification beyond the Visible Spectrum |
Type |
Journal Article |
| Year |
2018 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
18 |
Issue |
11 |
Pages |
1-10 |
| Keywords |
industrial application; infrared; machine learning |
| Abstract |
In this work, we explore the use of images from different spectral bands to classify defects in melamine faced panels, which could appear through the production process. Through experimental evaluation, we evaluate the use of images from the visible (VS), near-infrared (NIR), and long wavelength infrared (LWIR), to classify the defects using a feature descriptor learning approach together with a support vector machine classifier. Two descriptors were evaluated, Extended Local Binary Patterns (E-LBP) and SURF using a Bag of Words (BoW) representation. The evaluation was carried on with an image set obtained during this work, which contained five different defect categories that currently occurs in the industry. Results show that using images from beyond the visual spectrum helps to improve classification performance in contrast with a single visible spectrum solution. |
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| Notes |
MSIAU; 600.122 |
Approved |
no |
| Call Number |
Admin @ si @ AAS2018 |
Serial |
3191 |
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| Author |
Cristhian A. Aguilera-Carrasco; Cristhian Aguilera; Cristobal A. Navarro; Angel Sappa |
| Title |
Fast CNN Stereo Depth Estimation through Embedded GPU Devices |
Type |
Journal Article |
| Year |
2020 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
20 |
Issue |
11 |
Pages |
3249 |
| Keywords |
stereo matching; deep learning; embedded GPU |
| Abstract |
Current CNN-based stereo depth estimation models can barely run under real-time constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art evaluations usually do not consider model optimization techniques, being that it is unknown what is the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models on three different embedded GPU devices, with and without optimization methods, presenting performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically augmenting the runtime speed of current models. In our experiments, we achieve real-time inference speed, in the range of 5–32 ms, for 1216 × 368 input stereo images on the Jetson TX2, Jetson Xavier, and Jetson Nano embedded devices. |
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MSIAU; 600.122 |
Approved |
no |
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Admin @ si @ AAN2020 |
Serial |
3428 |
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| Author |
Reza Azad; Maryam Asadi-Aghbolaghi; Shohreh Kasaei; Sergio Escalera |
| Title |
Dynamic 3D Hand Gesture Recognition by Learning Weighted Depth Motion Maps |
Type |
Journal Article |
| Year |
2019 |
Publication |
IEEE Transactions on Circuits and Systems for Video Technology |
Abbreviated Journal |
TCSVT |
| Volume |
29 |
Issue |
6 |
Pages |
1729-1740 |
| Keywords |
Hand gesture recognition; Multilevel temporal sampling; Weighted depth motion map; Spatio-temporal description; VLAD encoding |
| Abstract |
Hand gesture recognition from sequences of depth maps is a challenging computer vision task because of the low inter-class and high intra-class variability, different execution rates of each gesture, and the high articulated nature of human hand. In this paper, a multilevel temporal sampling (MTS) method is first proposed that is based on the motion energy of key-frames of depth sequences. As a result, long, middle, and short sequences are generated that contain the relevant gesture information. The MTS results in increasing the intra-class similarity while raising the inter-class dissimilarities. The weighted depth motion map (WDMM) is then proposed to extract the spatio-temporal information from generated summarized sequences by an accumulated weighted absolute difference of consecutive frames. The histogram of gradient (HOG) and local binary pattern (LBP) are exploited to extract features from WDMM. The obtained results define the current state-of-the-art on three public benchmark datasets of: MSR Gesture 3D, SKIG, and MSR Action 3D, for 3D hand gesture recognition. We also achieve competitive results on NTU action dataset. |
| Address |
June 2019, |
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HUPBA; no proj |
Approved |
no |
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Admin @ si @ AAK2018 |
Serial |
3213 |
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| Author |
Reza Azad; Maryam Asadi-Aghbolaghi; Mahmood Fathy; Sergio Escalera |
| Title |
Attention Deeplabv3+: Multi-level Context Attention Mechanism for Skin Lesion Segmentation |
Type |
Conference Article |
| Year |
2020 |
Publication |
Bioimage computation workshop |
Abbreviated Journal |
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| Address |
Virtual; August 2020 |
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ECCVW |
| Notes |
HUPBA |
Approved |
no |
| Call Number |
Admin @ si @ AAF2020 |
Serial |
3520 |
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| Author |
Reza Azad; Maryam Asadi Aghbolaghi; Mahmood Fathy; Sergio Escalera |
| Title |
Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions |
Type |
Conference Article |
| Year |
2019 |
Publication |
Visual Recognition for Medical Images workshop |
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Issue |
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Pages |
406-415 |
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| Abstract |
In recent years, deep learning-based networks have achieved state-of-the-art performance in medical image segmentation. Among the existing networks, U-Net has been successfully applied on medical image segmentation. In this paper, we propose an extension of U-Net, Bi-directional ConvLSTM U-Net with Densely connected convolutions (BCDU-Net), for medical image segmentation, in which we take full advantages of U-Net, bi-directional ConvLSTM (BConvLSTM) and the mechanism of dense convolutions. Instead of a simple concatenation in the skip connection of U-Net, we employ BConvLSTM to combine the feature maps extracted from the corresponding encoding path and the previous decoding up-convolutional layer in a non-linear way. To strengthen feature propagation and encourage feature reuse, we use densely connected convolutions in the last convolutional layer of the encoding path. Finally, we can accelerate the convergence speed of the proposed network by employing batch normalization (BN). The proposed model is evaluated on three datasets of: retinal blood vessel segmentation, skin lesion segmentation, and lung nodule segmentation, achieving state-of-the-art performance. |
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Seul; Korea; October 2019 |
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ICCVW |
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HUPBA; no proj |
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no |
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Admin @ si @ AAF2019 |
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3324 |
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