TP1.PD.4
Self-supervised Learning for Context-independent DfD Network using Multi-view Rank Supervision
Nao Mishima, Akihito Seki, Toshiba coop., Japan; Shinsaku Hiura, University of Hyogo, Japan
Session:
TP1.PD: Computational Imaging Systems Poster
Track:
Computational Imaging Systems
Location:
Poster Area D
Presentation Time:
Tue, 10 Oct, 14:30 - 16:00 Malaysia Time (UTC +8)
Session Chair:
Shogo Muramatsu, Niigata University
Session TP1.PD
TP1.PD.1: SWINAT-UNET: A NEW BACKBONE FOR PRECIPITATION NOWCASTING
Wei Fang, Meihan Qi, Nanjing University of Information Science & Technology, China
TP1.PD.2: REAL-TIME SUPERMARKET PRODUCT RECOGNITION ON MOBILE DEVICES USING SCALABLE PIPELINES
Julian Strohmayer, Martin Kampel, TU Wien, Austria
TP1.PD.3: A NOVEL PSEUDO-LABEL GENERATION METHOD FOR SEMI-SUPERIVISED SAR TARGET RECOGNITION BASED ON DEEP LEARNING
Xinzheng Zhang, Yuqing Luo, School of Microelectronics and Communication Engineering, Chongqing University, China; Liping Hu, Science and Technology on Electromagnetic Scattering Laboratory, Beijing Institute of Environmental Features, China
TP1.PD.4: Self-supervised Learning for Context-independent DfD Network using Multi-view Rank Supervision
Nao Mishima, Akihito Seki, Toshiba coop., Japan; Shinsaku Hiura, University of Hyogo, Japan
TP1.PD.5: STYLE TRANSFER BETWEEN MICROSCOPY AND MAGNETIC RESONANCE IMAGING VIA GENERATIVE ADVERSARIAL NETWORK IN SMALL SAMPLE SIZE SETTINGS
Monika Pytlarz, Adrian Onicas, Alessandro Crimi, Sano – Centre for Computational Personalised Medicine, Poland
TP1.PD.6: LITE-HRNET PLUS: FAST AND ACCURATE FACIAL LANDMARK DETECTION
Sota Kato, Kazuhiro Hotta, Meijo University, Japan; Yuhki Hatakeyama, Yoshinori Konishi, SenseTime Japan, Japan
TP1.PD.7: PREDICTION OF DEEP ICE LAYER THICKNESS USING ADAPTIVE RECURRENT GRAPH NEURAL NETWORKS
Benjamin Zalatan, Maryam Rahnemoonfar, Lehigh University, United States of America
TP1.PD.8: RESIDENTIAL EXTRACTION BASED ON WEAKLY-SUPERVISED SIMILARITY-AWARE MULTI-SOURCE ALIGNMENT STRATEGY WITH LIMITED SAR DATA
Sijia Ma, Libao Zhang, Beijing Normal University, China
TP1.PD.9: CNN-BASED ESTIMATION OF WATER DEPTH FROM MULTISPECTRAL DRONE IMAGERY FOR MOSQUITO CONTROL
Qianyao Shen, KTH Royal Institute of Technology, Sweden; K T Yasas Mahima, Kasun De Zoysa, University of Colombo, Sri Lanka; Luca Mottola, Thiemo Voigt, RISE Research Institutes of Sweden & Uppsala University, Sweden; Markus Flierl, KTH Royal Institute of Technology, Sweden
TP1.PD.10: WHAT MODALITY MATTERS? EXPLOITING HIGHLY RELEVANT FEATURES FOR VIDEO ADVERTISEMENT INSERTION
Onn Keat Chong, Hui-Ngo Goh, Multimedia University, Malaysia; John See, Heriot-Watt University, Malaysia
TP1.PD.11: EARLY DIAGNOSIS OF PROSTATE CANCER USING PARAMETRIC ESTIMATION OF IVIM FROM DW-MRI
Hossam Magdy Balaha, University of Louisville, United States of America; Sarah M. Ayyad, Mansoura University, Egypt; Ahmed Alksas, University of Louisville, United States of America; Ali Elsorougy, Mohamed Ali Badawy, Mansoura University, Egypt; Mohamed Shehata, University of Louisville, United States of America; Mohamed Abou El-Ghar, Mansoura University, Egypt; Mohammed Ghazal, Abu Dhabi University, United Arab Emirates; Ali Mahmoud, University of Louisville, United States of America; Sohail Contractor, Department of Radiology, University of Louisville, United States of America; Ayman El-Baz, University of Louisville, United States of America
TP1.PD.12: DEEP LEARNING BASED WORKFLOW FOR ACCELERATED INDUSTRIAL X-RAY COMPUTED TOMOGRAPHY
Obaidullah Rahman, Singanallur Venkatakrishnan, Luke Scime, Oak Ridge National Laboratory, United States of America; Paul Brackman, Curtis Frederick, ZEISS Industrial Metrology, LLC, United States of America; Ryan Dehoff, Vincent Paquit, Amir Koushyar Ziabari, Oak Ridge National Laboratory, United States of America
Contacts