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MLR-APPL-IP-6: Machine learning for image processing 6

Session Type: Poster
Time: Tuesday, September 21, 15:30 - 17:00
Location: Area E
Session Chair: João Ascenso, Instituto Superior Técnico - University of Lisbon
 
   MLR-APPL-IP-6.1: CLASSIFICATION OF RIGID AND NON-RIGID TRANSFORMATIONS WITH AUTOENCODER REPRESENTATIONS
         Alexis R. Tudor; University of Nevada, Reno
         Gunner Stone; University of Nevada, Reno
         Alireza Tavakkoli; University of Nevada, Reno
         Emily M. Hand; University of Nevada, Reno
 
   MLR-APPL-IP-6.2: MBB: A MULTI-SCALE METHOD FOR DATA BASED ON BIT PLANE SLICING
         Youneng Bao; Harbin Institute of Technology, Shenzhen
         Chao Li; Shenzhen University
         Fanyang Meng; Pengcheng Laboratory
         Yongsheng Liang; Harbin Institute of Technology, Shenzhen
         Wei Liu; Pengcheng Laboratory
         Kaiyu Liu; Harbin Institute of Technology, Shenzhen
 
   MLR-APPL-IP-6.3: KNOWLEDGE TRANSFERRED FINE-TUNING FOR ANTI-ALIASED CONVOLUTIONAL NEURAL NETWORK IN DATA-LIMITED SITUATION
         Satoshi Suzuki; NTT Corporation
         Shoichiro Takeda; NTT Corporation
         Ryuichi Tanida; NTT Corporation
         Hideaki Kimata; NTT Corporation
         Hayaru Shouno; University of Electro-Communications
 
   MLR-APPL-IP-6.4: IMPROVING THE ROBUSTNESS OF CONVOLUTIONAL NEURAL NETWORKS VIA SKETCH ATTENTION
         Tianshu Chu; Shanghai Jiao Tong University
         Zuopeng Yang; Shanghai Jiao Tong University
         Jie Yang; Shanghai Jiao Tong University
         Xiaolin Huang; Shanghai Jiao Tong University
 
   MLR-APPL-IP-6.5: IR-SSL: IMPROVED REGULARIZATION BASED SEMI-SUPERVISED LEARNING FOR LAND COVER CLASSIFICATION
         Habib Ullah; University of Ha'il, Saudi Arabia
         Tawsin Uddin Ahmed; Norwegian University of Science and Technology
         Mohib Ullah; Norwegian University of Science and Technology
         Faouzi Alaya Cheikh; Norwegian University of Science and Technology
 
   MLR-APPL-IP-6.6: LET THEM CHOOSE WHAT THEY WANT: A MULTI-TASK CNN ARCHITECTURE LEVERAGING MID-LEVEL DEEP REPRESENTATIONS FOR FACE ATTRIBUTE CLASSIFICATION
         Zhenduo Chen; Nanjing University of Posts and Telecommunications
         Feng Liu; Nanjing University of Posts and Telecommunications
         Zhenglai Zhao; Jiangsu Bzisland Intelligent Technology Institute
 
   MLR-APPL-IP-6.7: INDIAN MASKED FACES IN THE WILD DATASET
         Shiksha Mishra; Indian Institute of Technology Jodhpur
         Puspita Majumdar; Indraprastha Institute of Information Technology, Delhi
         Richa Singh; Indian Institute of Technology Jodhpur
         Mayank Vatsa; Indian Institute of Technology Jodhpur
 
   MLR-APPL-IP-6.8: LEARNING ASSOCIATIVE REPRESENTATION FOR FACIAL EXPRESSION RECOGNITION
         Yangtao Du; Institute of AI and Robotics, Fudan University
         Dingkang Yang; Institute of AI and Robotics, Fudan University
         Peng Zhai; Institute of AI and Robotics, Fudan University
         Mingchen Li; Institute of AI and Robotics, Fudan University
         Lihua Zhang; Institute of AI and Robotics, Fudan University
 
   MLR-APPL-IP-6.9: A TILT-ANGLE FACE DATASET AND ITS VALIDATION
         Nanxi Wang; Wuhan University
         Zhongyuan Wang; Wuhan University
         Zheng He; Wuhan University
         Baojin Huang; Wuhan University
         Liguo Zhou; Technical University of Munich
         Zhen Han; Wuhan University
 
   MLR-APPL-IP-6.10: PROGRESSIVE FACE SUPER-RESOLUTION WITH NON-PARAMETRIC FACIAL PRIOR ENHANCEMENT
         Jonghyun Kim; Sungkyunkwan University
         Gen Li; Sungkyunkwan University
         Cheolkon Jung; Xidian University
         Joongkyu Kim; Sungkyunkwan University
 
   MLR-APPL-IP-6.12: GEOMETRIC DATA AUGMENTATION BASED ON FEATURE MAP ENSEMBLE
         Takashi Shibata; NTT
         Masayuki Tanaka; Tokyo Institute of Technolgy
         Masatoshi Okutomi; Tokyo Institute of Technolgy