Day 0 Sunday, 1 December |
|
17:00 - 18:00 |
Registration |
17:00 - 19:00 |
Welcome Reception |
Day 1 Monday, 2 December |
|
08:00 - 08:45 |
Registration |
08:45 - 09:00 |
Conference Opening |
09:00 - 10:00 |
|
10:00 - 10:30 |
Morning Tea |
10:30 - 12:00 |
Oral Session 1: Classification Chair: Professor Antonio Robles-Kelly, Deakin University |
12:00 - 13:00 |
Lunch |
13:00 - 15:30 |
|
15:00 - 15:30 |
Afternoon Tea |
15:30 - 17:00 |
Chair: Professor Manzur Murshed, Federation University |
Day 2 Tuesday, 3 December |
|
08:15 - 09:00 |
Registration |
09:00 - 10:00 |
|
10:00 - 10:30 |
Morning Tea |
10:30 - 12:00 |
Oral Session 3: Detection and Localization Chair: Dr Mohammed Awrangjeb, Griffith University |
12:00 - 13:00 |
Lunch |
13:00 - 15:00 |
|
14:30 - 15:00 |
Afternoon Tea |
15:00 - 16:30 |
Oral Session 4: Medical Image Analysis Chair: Professor Murk Bottema, Flinders University |
16:30 - 17:30 |
APRS AGM |
18:40 - 22:00 |
|
Day 3 Wednesday, 4 December |
|
08:15 - 09:00 |
Registration |
09:00 - 10:00 |
Towards Embodied Action Understanding |
10:00 - 10:30 |
Morning Tea |
10:30 - 12:00 |
Oral Session 5: Computer Vision Applications I Chair: Dr Dmitry Konovalov, James Cook University |
12:00 - 13:00 |
Lunch |
13:00 14:00 |
|
14:00 - 14:30 |
Oral Session 6 Image and Text Chair: Associate Professor Mark McDonnell, University of South Australia |
14:30 - 15:00 |
Afternoon Tea |
15:00 - 16:30 |
Oral Session 7 - Remote Sensing Chair: Dr Alan Woodley, Queensland University of Technology |
16:30 - 16:45 |
Closing |
Workshops Thursday, 5 December |
|
08:45 - 09:00 |
Opening remarks Professor Ajmal Mian |
09:00 - 12:30 |
|
12:30 - 13:30 |
Lunch |
13:30 16:30 |
Chair: Professor Antonio Robles-Kelly, Deakin University
S1.1. |
Object Graph Networks for Spatial Language Grounding. Phil Hawkins (Queensland University of Technology, Australia); Frederic Maire (Queensland University of Technology, Australia); Simon Denman (Queensland University of Technology, Australia); and Mahsa Baktashmotlagh (University of Queensland, Australia) |
S1.2. |
Part-Based Feature Aggregation Method for Dynamic Scene Recognition. Xiaoming Peng (University of Wollongong, Australia); and Abdesselam Bouzerdoum (University of Wollongong, Australia) |
S1.3. |
Generalized Zero-Shot Learning with Domain Classification in a Joint Semantic and Visual Space. Rafael Felix (The University of Adelaide); Ben Harwood (Monash University); Michele Sasdelli (The University of Adelaide); Gustavo Carneiro (University of Adelaide) |
S1.4. |
Tree Log Identity Matching Using Convolutional Correlation Networks. Mikko Vihlman (Aalto University); Jakke Kulovesi (Aalto University); Arto Visala (Aalto University) |
S1.5. |
A Classification Methodology based on Subspace Graphs Learning. Riccardo La Grassa (University of Insubria, Italy); Ignazio Gallo (University of Insubria, Italy); Alessandro Calefati (University of Insubria, Italy); and Dimitri Ognibene (University of Essex, United Kingdom) |
S1.6. |
Faster R-CNN Based Deep Learning for Seagrass Detection from Underwater Digital Images. Md Moniruzzaman (Edith Cowan University); Syed Islam (Edith Cowan University); Paul Lavery (Edith Cowan University); Mohammed Bennamoun (University of Western Australia) |
Chair: Professor Manzur Murshed, Federation University
S2.1. |
Fast Point Cloud Registration using Semantic Segmentation. Giang Truong (Edith Cowan University); Syed Zulqarnain Gilani (The University of Western Australia); Syed Islam (Edith Cowan University); David Suter (Edith Cowan University) |
S2.2. |
Single View 3D Point Cloud Reconstruction using Novel View Synthesis and Self Supervised Depth Estimation. Adrian Johnston (University of Adelaide); Gustavo Carneiro (University of Adelaide) |
S2.3. |
Perspective-consistent multifocus multiview 3D reconstruction of small objects. Hengjia Li (Australian National University); Chuong Nguyen (CSIRO Data61) |
S2.4. |
High-Throughput Plant Height Estimation from RGB Images Acquired with Aerial Platforms: a 3D Point Cloud based Approach. Xun Li (CSIRO, Australia); Geoff Bull (CSIRO, Australia); Robert Coe (CSIRO, Australia); Sakda Eamkulworapong (CSIRO, Australia); Jamie Scarrow (CSIRO, Australia); Michael Salim (CSIRO, Australia); Michael Schaefer (CSIRO, Australia); and Xavier Sirault (CSIRO, Australia) |
S2.5. |
AB-PointNet for 3D Point Cloud Recognition. Junya Komori (Meijo university); Kazuhiro Hotta (Meijo University) |
S2.6. |
An Automated Method for Individual Wire Extraction from Power Line Corridor using LiDAR Data. Nosheen Munir (Griffith University); Mohammad Awrangjeb (Griffith University, Australia); Bela Stantic (Griffith University) |
Chair: Dr Mohammed Awrangjeb, Griffith University
S3.1. |
Insect-inspired Small Moving Target Enhancement in Infrared Videos. Muhammad Uzair (University of South Australia); Russell Brinkworth (University of South Australia); Anthony Finn (University of South Australia) |
S3.2. |
Visual Localization Under Appearance Change: A Filtering Approach. Dzung Anh Doan (The University of Adelaide, Australia); Yasir Latif (The University of Adelaide, Australia); Tat-Jun Chin (University of Adelaide, Australia); Yu Liu (The University of Adelaide, Australia); Shin-Fang Chng (The University of Adelaide, Australia); Thanh-Toan Do (The University of Liverpool, UK); Ian Reid (The University of Adelaide, Australia ) |
S3.3. |
Automatic Nipple Detection Method for Digital Skin Images with Psoriasis Lesions. Yasmeen M George (University of Melbourne); Mohammad Aldeen (Department of Electrical and Electronic Engineering, University of Melbourne, Australia); Rahil Garnavi (IBM Research Australia) |
S3.4. |
OGaze: Gaze Prediction in Egocentric Videos for Attentional Object Selection. Mohammad Al-Naser (German Research Centre for Artificial Intelligence (DFKI)); Shoaib Ahmed Siddiqui (DFKI); Hiroki Ohashi (Hitachi Ltd); Sheraz Ahmed (DFKI); Nakamura KATSUYUKI (Hitachi); Sato Takuto (Hitachi); Andreas Dengel (DFKI GmbH) |
S3.5. |
Deep-Learning From Mistakes: Automating Cloud Class Refinement for Sky Image Segmentation. S3.5. Gemma Dianne (University of Queensland, Australia); Arnold Wiliem (University of Queensland, Australia); and Brian C. Lovell (University of Queensland, Australia) |
S3.6. |
Enhanced micro target detection through local motion feedback in biologically inspired algorithms. Aaron Melville-Smith (University of South Australia); Anthony Finn (University of South Australia); Russell Brinkworth (University of South Australia) |
Chair: Professor Murk Bottema, Flinders University
S4.1. |
To What Extent Does Downsampling, Compression, and Data Scarcity Impact Renal Image Analysis? Can Peng (the University of Queensland); Kun Zhao (University of Queensland); Arnold Wiliem (the University of Queensland); Teng Zhang (The University of Queensland); Peter Hobson (Sullivan Nicolaides Pathology); Anthony Jennings (Sullivan Nicolaides Pathology); Brian C Lovell (University of Queensland) |
S4.2. |
SRM superpixel merging framework for precise segmentation of cervical nucleus. Ratna Saha (Flinders University); Mariusz Bajger (Flinders University); Gobert Lee (Flinders University) |
S4.3. |
From Chest X-rays to Radiology Reports: A Multimodal Machine Learning Approach. Sonit Singh (Macquarie University); Sarvnaz Karimi (DATA61, CSIRO); Kevin Ho-Shon (Macquarie University); Len Hamey (Computing Department, Macquarie University, NSW 2109) |
S4.4. |
Constructing synthetic chorio-retinal patches using generative adversarial networks. Jason Kugelman (Queensland University of Technology); David Alonso-Caneiro (Queensland University of Technology); Scott Read (Queensland University of Technology); Stephen Vincent (Queensland University of Technology); Fred Chen (Lions Eye Institute); Michael Collins (Queensland University of Technology) |
S4.5. |
Radiography Contrast Enhancement: Smoothed LHE Filter a Practical Solution for Digital X-rays with Mach band. Prasoon Ambalathankandy (Hokkaido University, Japan); Yafei Ou (Hokkaido University, Japan); Jyotsna Kochiyil (Independent Radiologist, United States); Shinya Takamaeda (Hokkaido University, Japan); Masato Motomura (Tokyo Institute of Technology, Japan); Tetsuya Asai (Hokkaido University, Japan); and Masayuki Ikebe (Hokkaido University, Japan) |
S4.6. |
Assessment and Elimination of Inflammatory Cell: A Machine Learning Approach in Digital Cytology. Jing Ke (Shanghai Jiao Tong University, China); Junwei Deng (University of Michigan, United States); Yizhou Lu (Shanghai Jiao Tong University, China); Dadong Wang (Data61, CSIRO, Australia); Yang Song (University of New South Wales, Australia); and Huijuan Zhang (Shanghai Jiao Tong University, China) |
Chair: Dr Dmitry Konovalov, James Cook University
S5.1. |
Modelling and Flame Segmentation for Real-Time Monitoring of Rotary Kilns. John Ridley (Curtin University); Duc Son Pham (Curtin University); Mihai Lazarescu (Curtin University) |
S5.2. |
Multi-pooling attention learning for melanoma recognition. Ruolin Liang (South China University of Technology, China); Qiuxia Wu (South China University of Technology, China); and Xiaowei Yang (South China University of Technology, China) |
S5.3. |
Mine-like Object Sensing in Sonar Imagery with a Compact Deep Learning Architecture for Scarce Data. Son Lam Phung (University of Wollongong, Australia); Thi Nhat Anh Nguyen (University of Wollongong, Australia); Hoang Thanh Le (University of Wollongong, Australia); Philip Chapple (Defence Science Technology Group, Australia); Christian Ritz (University of Wollongong, Australia); Abdesselam Bouzerdoum (University of Wollongong, Australia); and Le Chung Tran (University of Wollongong, Australia) |
S5.4. |
Using style-transfer to understand material classification for robotic sorting of recycled beverage containers. Mark D. McDonnell (University of South Australia); Bahar Moezzi (University of South Australia); Russell Brinkworth (University of South Australia) |
S5.5. |
EncapNet-3D and U-EncapNet for Cell Segmentation. Takumi Sato (Meijo University); Kazuhiro Hotta (Meijo University) |
S5.6. |
Explaining Machine Learning based Classifications of in-vivo Gastral Images. Avleen Malhi (Aalto University); Timotheus Kampik (Umeε University); Husanbir Singh Pannu (Thapar University); Manik Madhikermi (Aalto University); Kary Frδmling (Aalto University) |
Chair: Associate Professor Mark McDonnell, University of South Australia
S6.1. |
Historical Document Text Binarization using Atrous Convolution and Multi-scale Feature Decoder. Hanif Rasyidi (Australian National University); Salman Khan (Australian National University (ANU)) |
S6.2. |
Picture What you Read. Ignazio Gallo (University of Insubria, Italy); Shah Nawaz (University of Insubria, Italy); Alessandro Calefati (University of Insubria, Italy); Riccardo La Grassa (University of Insubria, Italy); and Nicola Landro (University of Insubria, Italy) |
Chair: Dr Alan Woodley, Queensland University of Technology
S7.1. |
Robust Image Watermarking Framework Powered by Convolutional Encoder-Decoder Network. Thien Huynh-The (Kumoh National Institute of Technology, South Korea); Cam-Hao Hua (Kyung Hee University, South Korea); Tu Nguyen (Nazarbayev University, Kazakhstan); and Dong-Seong Kim (Kumoh National Institute of Technology, South Korea) |
S7.2. |
Runway detection and localization in aerial images using deep learning. Muhammad Shahzad (National University of Sciences and Technology, Pakistan); Javeria Akbar (National University of Sciences and Technology, Pakistan); Muhammad Imran Malik (National University of Sciences and Technology, Pakistan); Adnan Ul-Hasan (Deep Learning Laboratory, National Center of Artificial Intelligence, Pakistan); and Faisal Shafait (National University of Sciences and Technology, Pakistan) |
S7.3. |
Abundance-guided Superpixels and Recurrent Neural Network for Hyperspectral Image Classification. Fahim Alam (Griffith University, Australia); Jun Zhou (Griffith University, Australia); Alan Liew (Griffith University, Australia) |
S7.4. |
Temporal 3D fully connected network for water-hazard detection. Juntao Li (Australian National University, Australia); Chuong Nguyen (CSIRO, Australia); and Shaodi You (CSIRO, Australia) |
S7.5. |
Improved Detection for WAMI using Background Contextual Information. Elena M Vella (The University of Melbourne); Anee Azim (Lockheed Martin); Han Gaetjens (Lockheed Martin); Boris Repasky (Lockheed Martin); Timothy Payne (Lockheed Martin) |
S7.6. |
Change Detection Over the State of Queensland Using High Resolution Planet Satellite Mosaics. Connor McLaughlin (Queensland University of Technology, Australia); Holly Hutson (Queensland University of Technology, Australia); Lance De Vine (Queensland University of Technology, Australia); Alan Woodley (Queensland University of Technology, Australia); Shlomo Geva (Queensland University of Technology, Australia); Timothy Chappell (Queensland University of Technology, Australia); Wayne Kelly (Queensland University of Technology, Australia); Wageeh Boles (Queensland University of Technology Australia); and Dimitri Perrin (Queensland University of Technology, Australia) |
P1.1.
Image
Alignment Using Norm Conserved GAT Correlation |
P1.2.
Wave scale,
speed and direction from airborne video of maritime scene |
P1.3.
Indian
Sign Language Gesture Recognition using Image Processing and Deep Learning |
P1.4.
Reading
Meter Numbers in the Wild |
P1.5.
Automated
Building Footprint and 3D Building Model Generation from Lidar Point Cloud
Data |
P1.6.
Deep
Latent Space Learning for Cross-modal Mapping of Audio and Visual Signals |
P1.7.
Using
Image Processing to Automatically Measure Pearl Oyster Size for Selective
Breeding |
P1.8.
Real-Time
Human Gaze Estimation |
P1.9.
Deep
Learning for Autonomous Driving |
P1.10. LiteSeg: A Novel Lightweight
ConvNet for Semantic Segmentation |
P1.11. Feature Engineering meets Deep Learning: A Case Study on
Table Detection in Documents |
P1.12. Facial gender classification- Analysis using
convolutional neural networks |
P1.13. STCEC: A Remote Sensing Dataset for Identifying Spatial
Temporal Change in Homogeneous and Heterogeneous Environments |
P1.14. Semantic Segmentation under Severe Imaging Conditions |
P1.15. Incorporating the
Barzilai-Borwein Adaptive Step Size into Sugradient Methods for Deep Network
Training |
P1.16. Ensemble of Training Models for
Road and Building Segmentation. |
P1.17. Efficient Block Pruning based on
kernel and feature stabilization. |
P1.18. Bi-SAN-CAP: Bi-Directional
Self-Attention for Image Captioning. |
P1.19. Scalable video classification
using bag of visual words on Spark. |
P1.20. Class Activation Map generation
by Multiple Level Class Grouping and Orthogonal Constraint. |
P1.21. Deep Fusion Net for Coral
Classification in Fluorescence and Reflectance Images. |
P1.22. Logical Layout Analysis using
Deep Learning. |
P2.1.
Data
Efficient Classification of Birdcall Through Convolutional Neural Networks
Transfer Learning.
Dina Efremova, Funbox Inc., Russian
Federation; Mangalam Sankupellay, James Cook University, Australia; and Dmitry
Konovalov, James Cook University, Australia
P2.2.
Deep
Corrosion Assessment for Electrical Transmission Towers.
Teng Zhang, The University of Queensland, Australia;
Liangchen Liu, The University of Queensland, Australia; Arnold Wiliem, The
University of Queensland, Australia; Stephen Connor, Powerlink Queensland,
Australia; Zelkjo Ilich, Powerlink Queensland, Australia; Eddie Van Der Draai,
Powerlink Queensland, Australia; and Brian Lovell, University of Queensland,
Australia)
P2.3.
Automatic
Weight Estimation of Harvested Fish from Images.
Dmitry Konovalov, James Cook University,
Australia; Alzayat Saleh, James Cook University, Australia; Dina Efremova,
Funbox Inc, Russian Federation; Jose Domingos, James Cook University,
Australia; and Dean Jerry, James Cook University, Australia
P2.4.
Measurement
of Traffic Volume by Time Series Images Created from Horizontal Edge Segments.
Kazunori Onoguchi (Hirosaki University,
Japan)
P2.5.
Flood
Detection in Social Media Images Using Visual Features and Metadata.
Rabiul Islam Jony, Queensland University
of Technology, Australia;Alan Woodley, Queensland University of Technology,
Australia; and Dimitri Perrin, Queensland University of Technology, Australia
P2.6.
Blind
Motion Deblurring for Satellite Image using Convolutional Neural Network.
Hyun-ho Kim, Korea Aerospace Research
Institute, Republic of Korea; Doochun Seo, Korea Aerospace Research Institute,
Republic of Korea; Jaeheon Jung, Korea Aerospace Research Institute, Republic
of Korea; Donghwan Cha, Korea Aerospace Research Institute, Republic of Korea;
and Donghan Lee, Korea Aerospace Research Institute, Republic of Korea
P2.7.
Evaluation
of the impact of image spatial resolution in designing a context-based fully
convolution neural networks for flood mapping.
Chandrama Sarker, Queensland University of
Technology, Australia; Luis Mejias, Queensland University of Technology,
Australia; Frederic Maire, Queensland University of Technology, Australia; and
Alan Woodley, Queensland University of Technology, Australia
P2.8.
Hyperspectral
Image Analysis for Writer Identification using Deep Learning.
Ammad Ul Islam, Institute of Space
Technology, Pakistan; Muhammad Jaleed Khan, Institute of Space Technology,
Pakistan; Khurram Khurshid, Institute of Space Technology, Pakistan; and Faisal
Shafait, National University of Sciences and Technology, Pakistan
P2.9.
Automatic
generation of lymphoma post-treatment PETs using conditional-GANs.
Gabriel Silva, Instituto
Superior de Engenharia de Coimbra, Portugal; Ines Domingues, IPO Porto Research
Center (CI-IPOP), Portugal; Hugo Duarte, Portuguese Institute of Oncology of
Porto (IPO-Porto), Portugal; and Joao A. M. Santos, Portuguese Institute of
Oncology of Porto (IPO-Porto), Portugal
P2.10.
Corporate
IT-support Help-desk Process Hybrid-Automation Solution with Machine Learning
Approach.
Kuruparan Shanmugalingam, Millennium I.T
E.S.P (Pvt) Ltd, Sri Lanka; Nisal Chandrasekara, Millennium I.T E.S.P (Pvt)
Ltd, Sri Lanka; Calvin Hindle, Millennium I.T E.S.P (Pvt) Ltd, Sri Lanka; Gihan
Fernando, Millennium I.T E.S.P (Pvt) Ltd, Sri Lanka; and Chanaka Gunawardhana,
Millennium I.T E.S.P (Pvt) Ltd, Sri Lanka
P2.11.
Social
network analysis of an acoustic environment: the use of visualised data to
characterise natural habitats.
Junling Wang, James Cook University,
Australia; Mangalam Sankupellay, James Cook University, Australia; Dmitry
Konovalov, James Cook University, Australia; Michael Towsey, Queensland
University of Technology, Australia; and Paul Roe, Queensland University of
Technology, Australia
P2.12.
Improved
Image Analysis Methodology for Detecting Changes in Evidence Positioning at
Crime Scenes.
Mark Petty, Federation
University Australia, Australia;Shyh Wei Teng, Federation University Australia,
Australia; and Manzur Murshed, Federation University Australia, Australia
P2.13.
Detection
of Central Retinal Vein Occlusion Using Guided Salient Features.
Nirupama Rajapaksha, University of
Moratuwa, Sri Lanka;Lochandaka Ranathunga, University of Moratuwa, Sri Lanka;
and K.M.P.K. Bandara, Teaching Hospital, Ragama, Sri Lanka
P2.14.
Haar
Pattern Based Binary Feature Descriptor for Retinal Image Registration.
Sajib Saha, Commonwealth
Scientific and Industrial Research Organisation, Australia; and Yogesan
Kanagasingam, Commonwealth Scientific and Industrial Research Organisation,
Australia
P2.15.
FFD: Figure
and Formula Detection from Document Images.
Junaid Younas, Technical University
Kaiserslautern, Germany; Syed Tahseen Raza Rizvi, Technical University
Kaiserslautern, Germany; Muhammad Imran Malik, National University of Science Technology,
Pakistan;Faisal Shafait, National University of Science Technology, Pakistan; Paul
Lukowicz, Technical University Kaiserslautern, Germany; and Sheraz Ahmed, DFKI,
Germany
P2.16.
Benchmarking
Object Detection Networks for Image based Reference Detection in Document
Images.
Syed Tahseen Raza Rizvi, German Research
Center for Artificial Intelligence, Germany; Adriano Lucieri, German Research
Center for Artificial Intelligence, Germany; Andreas Dengel, German Research
Center for Artificial Intelligence, Germany; and Sheraz Ahmed, German Research
Center for Artificial Intelligence, Germany
P2.17.
Registration
Based Data Augmentation for Multiple Sclerosis Lesion Segmentation.
Ava Assadi Abolvardi, Macquarie
University, Australia; Len Hamey, Macquarie University, Australia; and Kevin
Ho-Shon, Macquarie University, Australia
P2.18.
Improving
Follicular Lymphoma Identification using the class of interest for Transfer
Learning.
Upeka Somaratne, Murdoch University,
Australia; Kok Wong, Murdoch University, Australia; Jeremy Parry, PathWest
Laboratory Medicine WA, Australia; Ferdous Sohel, Murdoch University,
Australia; Xuequn Wang, Murdoch University, Australia; and Hamid Laga, Murdoch
University, Australia
P2.19.
Multimodal
brain tumour segmentation using densely connected 3D convolutional neural
network.
Mina Ghaffari, Macquarie University,
Australia; Arcot Sowmya, University of New South Wales, Australia; Len Hamey,
Macquarie University, Australia; and Ruth Oliver, Macquarie University,
Australia
P2.20.
Rain Streak
Removal from Video Sequence Using Spatiotemporal Appearance.
Muhammad Rafiqul Islam, Charles Sturt
University, Australia; and Manoranjan Paul, Charles Sturt University, Australia
P2.21.
Facial-Expression
Recognition from Video Using Enhanced Convolutional LSTM.
Ryo Miyoshi, Chukyo University, Japan;
Noriko Nagata, Kwansei Gakuin University, Japan; and Manabu Hashimoto, Chukyo
University, Japan
P2.22. Adult or Child: Recognizing through
touch gestures on smartphones.
Osama Rasheed, COMSATS
University, Pakistan; Aimal Rextin, COMSATS University, Pakistan; and Mehwish
Nasim, Data61 CSIRO, Australia
Time |
Topic |
Speakers |
8:45am 9:00am |
Openning Remarks |
Ajmal Mian |
9:00am 10:00am |
TBA (Visual Text Correction, Video Fill-in-the-Blank, Natural Language Queries from Videos) |
Prof. Mubarak Shah (University of Central Florida) |
10:00am 10:30am |
Morning Tea Break |
|
10:30am 11:15am |
Deep Reasoning in Vision and Language |
Dr. Qi Wu (Uni. of Adelaide) |
11:15am - 12:00pm |
Knowledge Graph Driven Video Analysis for Social Good |
Dr. Xiaojun Chang (Monash) |
12:00pm 12:30pm |
Caption Quality Evaluation - the State of the Art |
Naeha Sharif |
12:30pm 1:30pm |
Working LUNCH |
Discussions with UWA PhD Students on Natural Language Generation |
1:30pm 2:45pm |
Attacking Deep Models |
Camilo A. P. Cardeno / Naveed Akhtar |
2:45pm - 3:15pm |
Going beyond attacks with perturbations |
Mohammad A. A. K. Jalwana / Naveed Akhtar |
3:15pm 3:45pm |
Afternoon Tea Break |
- |
3:45pm 4:30pm |
Adversarial defenses |
Camilo A. P. Cardeno / Naveed Akhtar |