Sorry, you need to enable JavaScript to visit this website.

Image, Video, and Multidimensional Signal Processing

VIRTUAL REVIEW OF LARGE SCALE IMAGE STACK ON 3D DISPLAY


Large scale images allow pathologists to perform reviews, using
computer workstations instead of microscopes. This trend raises
a wide range of issues related to the management of these massive
datasets. In particular, efficient solutions for data storage and processing
have to be developed in order to deliver increasingly reliable
and faster analyses. In addition, the improvement of workflows also
requires the reinforcement of visualization capabilities. In this paper,
we present a new virtual microscopy (VM) approach for interactivetime

Paper Details

Authors:
Jonathan Sarton, Nicolas Courilleau, Anne-Sophie Hérard, Thierry Delzescaux, Yannick Remion, Laurent Lucas
Submitted On:
16 September 2017 - 1:40am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:

Document Files

Poster_ICIP_2017.pdf

(232)

Subscribe

[1] Jonathan Sarton, Nicolas Courilleau, Anne-Sophie Hérard, Thierry Delzescaux, Yannick Remion, Laurent Lucas, "VIRTUAL REVIEW OF LARGE SCALE IMAGE STACK ON 3D DISPLAY", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2177. Accessed: May. 20, 2019.
@article{2177-17,
url = {http://sigport.org/2177},
author = {Jonathan Sarton; Nicolas Courilleau; Anne-Sophie Hérard; Thierry Delzescaux; Yannick Remion; Laurent Lucas },
publisher = {IEEE SigPort},
title = {VIRTUAL REVIEW OF LARGE SCALE IMAGE STACK ON 3D DISPLAY},
year = {2017} }
TY - EJOUR
T1 - VIRTUAL REVIEW OF LARGE SCALE IMAGE STACK ON 3D DISPLAY
AU - Jonathan Sarton; Nicolas Courilleau; Anne-Sophie Hérard; Thierry Delzescaux; Yannick Remion; Laurent Lucas
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2177
ER -
Jonathan Sarton, Nicolas Courilleau, Anne-Sophie Hérard, Thierry Delzescaux, Yannick Remion, Laurent Lucas. (2017). VIRTUAL REVIEW OF LARGE SCALE IMAGE STACK ON 3D DISPLAY. IEEE SigPort. http://sigport.org/2177
Jonathan Sarton, Nicolas Courilleau, Anne-Sophie Hérard, Thierry Delzescaux, Yannick Remion, Laurent Lucas, 2017. VIRTUAL REVIEW OF LARGE SCALE IMAGE STACK ON 3D DISPLAY. Available at: http://sigport.org/2177.
Jonathan Sarton, Nicolas Courilleau, Anne-Sophie Hérard, Thierry Delzescaux, Yannick Remion, Laurent Lucas. (2017). "VIRTUAL REVIEW OF LARGE SCALE IMAGE STACK ON 3D DISPLAY." Web.
1. Jonathan Sarton, Nicolas Courilleau, Anne-Sophie Hérard, Thierry Delzescaux, Yannick Remion, Laurent Lucas. VIRTUAL REVIEW OF LARGE SCALE IMAGE STACK ON 3D DISPLAY [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2177

CORRELATION-BASED DEBLURRING LEVERAGING MULTISPECTRAL CHROMATIC ABERRATION IN COLOR AND NEAR-INFRARED JOINT ACQUISITION

Paper Details

Authors:
Majed El Helou, Zahra Sadeghipoor, Sabine Susstrunk
Submitted On:
15 September 2017 - 9:37am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

ICIP_Presentation_2.pdf

(215)

Subscribe

[1] Majed El Helou, Zahra Sadeghipoor, Sabine Susstrunk, "CORRELATION-BASED DEBLURRING LEVERAGING MULTISPECTRAL CHROMATIC ABERRATION IN COLOR AND NEAR-INFRARED JOINT ACQUISITION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2135. Accessed: May. 20, 2019.
@article{2135-17,
url = {http://sigport.org/2135},
author = {Majed El Helou; Zahra Sadeghipoor; Sabine Susstrunk },
publisher = {IEEE SigPort},
title = {CORRELATION-BASED DEBLURRING LEVERAGING MULTISPECTRAL CHROMATIC ABERRATION IN COLOR AND NEAR-INFRARED JOINT ACQUISITION},
year = {2017} }
TY - EJOUR
T1 - CORRELATION-BASED DEBLURRING LEVERAGING MULTISPECTRAL CHROMATIC ABERRATION IN COLOR AND NEAR-INFRARED JOINT ACQUISITION
AU - Majed El Helou; Zahra Sadeghipoor; Sabine Susstrunk
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2135
ER -
Majed El Helou, Zahra Sadeghipoor, Sabine Susstrunk. (2017). CORRELATION-BASED DEBLURRING LEVERAGING MULTISPECTRAL CHROMATIC ABERRATION IN COLOR AND NEAR-INFRARED JOINT ACQUISITION. IEEE SigPort. http://sigport.org/2135
Majed El Helou, Zahra Sadeghipoor, Sabine Susstrunk, 2017. CORRELATION-BASED DEBLURRING LEVERAGING MULTISPECTRAL CHROMATIC ABERRATION IN COLOR AND NEAR-INFRARED JOINT ACQUISITION. Available at: http://sigport.org/2135.
Majed El Helou, Zahra Sadeghipoor, Sabine Susstrunk. (2017). "CORRELATION-BASED DEBLURRING LEVERAGING MULTISPECTRAL CHROMATIC ABERRATION IN COLOR AND NEAR-INFRARED JOINT ACQUISITION." Web.
1. Majed El Helou, Zahra Sadeghipoor, Sabine Susstrunk. CORRELATION-BASED DEBLURRING LEVERAGING MULTISPECTRAL CHROMATIC ABERRATION IN COLOR AND NEAR-INFRARED JOINT ACQUISITION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2135

Data Driven Coded Aperture Design for Depth Recovery

Paper Details

Authors:
Sreyas Mohan, Kaushik Mitra
Submitted On:
15 September 2017 - 8:12am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Data Driven Coded Aperture Design

(178)

Subscribe

[1] Sreyas Mohan, Kaushik Mitra, "Data Driven Coded Aperture Design for Depth Recovery", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2128. Accessed: May. 20, 2019.
@article{2128-17,
url = {http://sigport.org/2128},
author = {Sreyas Mohan; Kaushik Mitra },
publisher = {IEEE SigPort},
title = {Data Driven Coded Aperture Design for Depth Recovery},
year = {2017} }
TY - EJOUR
T1 - Data Driven Coded Aperture Design for Depth Recovery
AU - Sreyas Mohan; Kaushik Mitra
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2128
ER -
Sreyas Mohan, Kaushik Mitra. (2017). Data Driven Coded Aperture Design for Depth Recovery. IEEE SigPort. http://sigport.org/2128
Sreyas Mohan, Kaushik Mitra, 2017. Data Driven Coded Aperture Design for Depth Recovery. Available at: http://sigport.org/2128.
Sreyas Mohan, Kaushik Mitra. (2017). "Data Driven Coded Aperture Design for Depth Recovery." Web.
1. Sreyas Mohan, Kaushik Mitra. Data Driven Coded Aperture Design for Depth Recovery [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2128

Anomaly Detection in Thermal Images Using Deep Neural Networks

Paper Details

Authors:
Cai Lile, Li Yiqun
Submitted On:
15 September 2017 - 1:53am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

icip_poster.pdf

(873)

Subscribe

[1] Cai Lile, Li Yiqun, "Anomaly Detection in Thermal Images Using Deep Neural Networks", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2085. Accessed: May. 20, 2019.
@article{2085-17,
url = {http://sigport.org/2085},
author = {Cai Lile; Li Yiqun },
publisher = {IEEE SigPort},
title = {Anomaly Detection in Thermal Images Using Deep Neural Networks},
year = {2017} }
TY - EJOUR
T1 - Anomaly Detection in Thermal Images Using Deep Neural Networks
AU - Cai Lile; Li Yiqun
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2085
ER -
Cai Lile, Li Yiqun. (2017). Anomaly Detection in Thermal Images Using Deep Neural Networks. IEEE SigPort. http://sigport.org/2085
Cai Lile, Li Yiqun, 2017. Anomaly Detection in Thermal Images Using Deep Neural Networks. Available at: http://sigport.org/2085.
Cai Lile, Li Yiqun. (2017). "Anomaly Detection in Thermal Images Using Deep Neural Networks." Web.
1. Cai Lile, Li Yiqun. Anomaly Detection in Thermal Images Using Deep Neural Networks [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2085

ICIP 2017 Poster Paper 3060


Top-down attention plays an important role in guidance of human attention in real-world scenarios, but less efforts in computational modeling of visual attention has been put on it. Inspired by the mechanisms of top-down attention in human visual perception, we propose a multi-layer linear model of top-down attention to modulate bottom-up saliency maps actively. The first layer is a linear regression model which combines the bottom-up saliency maps on various visual features and objects.

Paper Details

Authors:
Keng-Teck Ma, Liyuan Li, Peilun Dai, Joo-Hwee Lim, Chenyao Shen, Qi Zhao
Submitted On:
15 September 2017 - 1:33am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICIP2017_P3060.pdf

(179)

Subscribe

[1] Keng-Teck Ma, Liyuan Li, Peilun Dai, Joo-Hwee Lim, Chenyao Shen, Qi Zhao, "ICIP 2017 Poster Paper 3060", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2083. Accessed: May. 20, 2019.
@article{2083-17,
url = {http://sigport.org/2083},
author = {Keng-Teck Ma; Liyuan Li; Peilun Dai; Joo-Hwee Lim; Chenyao Shen; Qi Zhao },
publisher = {IEEE SigPort},
title = {ICIP 2017 Poster Paper 3060},
year = {2017} }
TY - EJOUR
T1 - ICIP 2017 Poster Paper 3060
AU - Keng-Teck Ma; Liyuan Li; Peilun Dai; Joo-Hwee Lim; Chenyao Shen; Qi Zhao
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2083
ER -
Keng-Teck Ma, Liyuan Li, Peilun Dai, Joo-Hwee Lim, Chenyao Shen, Qi Zhao. (2017). ICIP 2017 Poster Paper 3060. IEEE SigPort. http://sigport.org/2083
Keng-Teck Ma, Liyuan Li, Peilun Dai, Joo-Hwee Lim, Chenyao Shen, Qi Zhao, 2017. ICIP 2017 Poster Paper 3060. Available at: http://sigport.org/2083.
Keng-Teck Ma, Liyuan Li, Peilun Dai, Joo-Hwee Lim, Chenyao Shen, Qi Zhao. (2017). "ICIP 2017 Poster Paper 3060." Web.
1. Keng-Teck Ma, Liyuan Li, Peilun Dai, Joo-Hwee Lim, Chenyao Shen, Qi Zhao. ICIP 2017 Poster Paper 3060 [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2083

Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization


As image tampering becomes ever more sophisticated and commonplace, the need for image forensics algorithms that can accurately and quickly detect forgeries grows. In this paper, we revisit the ideas of image querying and retrieval to provide clues to better localize forgeries. We propose a method to perform large-scale image forensics on the order of one million images using the help of an image search algorithm and database to gather contextual clues as to where tampering may have taken place.

Paper Details

Authors:
Joel Brogan, Paolo Bestagini, Aparna Bharati, Allan Pinto, Daniel Moreira, Kevin Bowyer, Patrick Flynn, Anderson Rocha, Walter Scheirer
Submitted On:
14 September 2017 - 10:48pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICIP2017_poster.pdf

(177)

Subscribe

[1] Joel Brogan, Paolo Bestagini, Aparna Bharati, Allan Pinto, Daniel Moreira, Kevin Bowyer, Patrick Flynn, Anderson Rocha, Walter Scheirer, "Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2074. Accessed: May. 20, 2019.
@article{2074-17,
url = {http://sigport.org/2074},
author = {Joel Brogan; Paolo Bestagini; Aparna Bharati; Allan Pinto; Daniel Moreira; Kevin Bowyer; Patrick Flynn; Anderson Rocha; Walter Scheirer },
publisher = {IEEE SigPort},
title = {Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization},
year = {2017} }
TY - EJOUR
T1 - Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization
AU - Joel Brogan; Paolo Bestagini; Aparna Bharati; Allan Pinto; Daniel Moreira; Kevin Bowyer; Patrick Flynn; Anderson Rocha; Walter Scheirer
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2074
ER -
Joel Brogan, Paolo Bestagini, Aparna Bharati, Allan Pinto, Daniel Moreira, Kevin Bowyer, Patrick Flynn, Anderson Rocha, Walter Scheirer. (2017). Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization. IEEE SigPort. http://sigport.org/2074
Joel Brogan, Paolo Bestagini, Aparna Bharati, Allan Pinto, Daniel Moreira, Kevin Bowyer, Patrick Flynn, Anderson Rocha, Walter Scheirer, 2017. Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization. Available at: http://sigport.org/2074.
Joel Brogan, Paolo Bestagini, Aparna Bharati, Allan Pinto, Daniel Moreira, Kevin Bowyer, Patrick Flynn, Anderson Rocha, Walter Scheirer. (2017). "Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization." Web.
1. Joel Brogan, Paolo Bestagini, Aparna Bharati, Allan Pinto, Daniel Moreira, Kevin Bowyer, Patrick Flynn, Anderson Rocha, Walter Scheirer. Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2074

U-Phylogeny: Undirected Provenance Graph Construction in the Wild


Deriving relationships between images and tracing back their history of modifications are at the core of Multimedia Phylogeny solutions, which aim to combat misinformation through doctored visual media. Nonetheless, most recent image phylogeny solutions cannot properly address cases of forged composite images with multiple donors, an area known as multiple parenting phylogeny (MPP). This paper presents a preliminary undirected graph construction solution for MPP, without any strict assumptions.

Paper Details

Authors:
Aparna Bharati, Daniel Moreira, Allan Pinto, Joel Brogan, Kevin Bowyer, Patrick Flynn, Walter Scheirer, Anderson Rocha
Submitted On:
14 September 2017 - 10:24pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICIP17_UPhy_Presentation.pptx

(159)

Subscribe

[1] Aparna Bharati, Daniel Moreira, Allan Pinto, Joel Brogan, Kevin Bowyer, Patrick Flynn, Walter Scheirer, Anderson Rocha, "U-Phylogeny: Undirected Provenance Graph Construction in the Wild", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2069. Accessed: May. 20, 2019.
@article{2069-17,
url = {http://sigport.org/2069},
author = {Aparna Bharati; Daniel Moreira; Allan Pinto; Joel Brogan; Kevin Bowyer; Patrick Flynn; Walter Scheirer; Anderson Rocha },
publisher = {IEEE SigPort},
title = {U-Phylogeny: Undirected Provenance Graph Construction in the Wild},
year = {2017} }
TY - EJOUR
T1 - U-Phylogeny: Undirected Provenance Graph Construction in the Wild
AU - Aparna Bharati; Daniel Moreira; Allan Pinto; Joel Brogan; Kevin Bowyer; Patrick Flynn; Walter Scheirer; Anderson Rocha
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2069
ER -
Aparna Bharati, Daniel Moreira, Allan Pinto, Joel Brogan, Kevin Bowyer, Patrick Flynn, Walter Scheirer, Anderson Rocha. (2017). U-Phylogeny: Undirected Provenance Graph Construction in the Wild. IEEE SigPort. http://sigport.org/2069
Aparna Bharati, Daniel Moreira, Allan Pinto, Joel Brogan, Kevin Bowyer, Patrick Flynn, Walter Scheirer, Anderson Rocha, 2017. U-Phylogeny: Undirected Provenance Graph Construction in the Wild. Available at: http://sigport.org/2069.
Aparna Bharati, Daniel Moreira, Allan Pinto, Joel Brogan, Kevin Bowyer, Patrick Flynn, Walter Scheirer, Anderson Rocha. (2017). "U-Phylogeny: Undirected Provenance Graph Construction in the Wild." Web.
1. Aparna Bharati, Daniel Moreira, Allan Pinto, Joel Brogan, Kevin Bowyer, Patrick Flynn, Walter Scheirer, Anderson Rocha. U-Phylogeny: Undirected Provenance Graph Construction in the Wild [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2069

FEATURE SAMPLING STRATEGIES FOR ACTION RECOGNITION

Paper Details

Authors:
Submitted On:
14 September 2017 - 10:21pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

icip2017-poster-feature-v2.pdf

(153)

Subscribe

[1] , "FEATURE SAMPLING STRATEGIES FOR ACTION RECOGNITION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2068. Accessed: May. 20, 2019.
@article{2068-17,
url = {http://sigport.org/2068},
author = { },
publisher = {IEEE SigPort},
title = {FEATURE SAMPLING STRATEGIES FOR ACTION RECOGNITION},
year = {2017} }
TY - EJOUR
T1 - FEATURE SAMPLING STRATEGIES FOR ACTION RECOGNITION
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2068
ER -
. (2017). FEATURE SAMPLING STRATEGIES FOR ACTION RECOGNITION. IEEE SigPort. http://sigport.org/2068
, 2017. FEATURE SAMPLING STRATEGIES FOR ACTION RECOGNITION. Available at: http://sigport.org/2068.
. (2017). "FEATURE SAMPLING STRATEGIES FOR ACTION RECOGNITION." Web.
1. . FEATURE SAMPLING STRATEGIES FOR ACTION RECOGNITION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2068

LOOSECUT: INTERACTIVE IMAGE SEGMENTATION WITH LOOSELY BOUNDED BOXES

Paper Details

Authors:
Submitted On:
14 September 2017 - 10:16pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

icip2017-poster-loosecut-v2.pdf

(205)

Subscribe

[1] , "LOOSECUT: INTERACTIVE IMAGE SEGMENTATION WITH LOOSELY BOUNDED BOXES", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2066. Accessed: May. 20, 2019.
@article{2066-17,
url = {http://sigport.org/2066},
author = { },
publisher = {IEEE SigPort},
title = {LOOSECUT: INTERACTIVE IMAGE SEGMENTATION WITH LOOSELY BOUNDED BOXES},
year = {2017} }
TY - EJOUR
T1 - LOOSECUT: INTERACTIVE IMAGE SEGMENTATION WITH LOOSELY BOUNDED BOXES
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2066
ER -
. (2017). LOOSECUT: INTERACTIVE IMAGE SEGMENTATION WITH LOOSELY BOUNDED BOXES. IEEE SigPort. http://sigport.org/2066
, 2017. LOOSECUT: INTERACTIVE IMAGE SEGMENTATION WITH LOOSELY BOUNDED BOXES. Available at: http://sigport.org/2066.
. (2017). "LOOSECUT: INTERACTIVE IMAGE SEGMENTATION WITH LOOSELY BOUNDED BOXES." Web.
1. . LOOSECUT: INTERACTIVE IMAGE SEGMENTATION WITH LOOSELY BOUNDED BOXES [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2066

TAD16K: An Enhanced Benchmark for Autonomous Driving


Although promising results have been achieved in the areas of object detection and classification, few works have provided an end-to-end solution to the perception problems in the autonomous driving field. In this paper, we make two contributions. Firstly, we fully enhanced our previously released TT100K benchmark and provide 16,817 elaborately labeled Tencent Street View panoramas.

Paper Details

Authors:
Yuming Li, Jue Wang, Tengfei Xing, Tianlu Liu, Chengjun Li, Kuifeng Su
Submitted On:
14 September 2017 - 6:10am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICIP2017_poster.pdf

(222)

Subscribe

[1] Yuming Li, Jue Wang, Tengfei Xing, Tianlu Liu, Chengjun Li, Kuifeng Su, "TAD16K: An Enhanced Benchmark for Autonomous Driving", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2007. Accessed: May. 20, 2019.
@article{2007-17,
url = {http://sigport.org/2007},
author = {Yuming Li; Jue Wang; Tengfei Xing; Tianlu Liu; Chengjun Li; Kuifeng Su },
publisher = {IEEE SigPort},
title = {TAD16K: An Enhanced Benchmark for Autonomous Driving},
year = {2017} }
TY - EJOUR
T1 - TAD16K: An Enhanced Benchmark for Autonomous Driving
AU - Yuming Li; Jue Wang; Tengfei Xing; Tianlu Liu; Chengjun Li; Kuifeng Su
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2007
ER -
Yuming Li, Jue Wang, Tengfei Xing, Tianlu Liu, Chengjun Li, Kuifeng Su. (2017). TAD16K: An Enhanced Benchmark for Autonomous Driving. IEEE SigPort. http://sigport.org/2007
Yuming Li, Jue Wang, Tengfei Xing, Tianlu Liu, Chengjun Li, Kuifeng Su, 2017. TAD16K: An Enhanced Benchmark for Autonomous Driving. Available at: http://sigport.org/2007.
Yuming Li, Jue Wang, Tengfei Xing, Tianlu Liu, Chengjun Li, Kuifeng Su. (2017). "TAD16K: An Enhanced Benchmark for Autonomous Driving." Web.
1. Yuming Li, Jue Wang, Tengfei Xing, Tianlu Liu, Chengjun Li, Kuifeng Su. TAD16K: An Enhanced Benchmark for Autonomous Driving [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2007

Pages