TP-V2.V9.3

MULTI-SCALE DEFORMABLE TRANSFORMER ENCODER BASED SINGLE-STAGE PEDESTRIAN DETECTION

Jing Yuan, Tania Stathaki, Imperial College London, United Kingdom of Great Britain and Northern Ireland; Panagiotis Barmpoutis, University College London, United Kingdom of Great Britain and Northern Ireland
Session:
Detection and Regression
Virtual Poster
Track:
Applications of Machine Learning
Location:
Gather.Town 9
Presentation Time:
Tue, 4 Oct, 22:00 - 23:00 China Standard Time (UTC +8)
Tue, 4 Oct, 16:00 - 17:00 Central European Time (UTC +2)
Tue, 4 Oct, 14:00 - 15:00 UTC
Tue, 4 Oct, 10:00 - 11:00 Eastern Time (UTC -4)
Session Co-Chairs:
Andrea Cavallaro, Queen Mary University of London and Jean-Christophe Pesquet, CentraleSupélec and Rebecca Willett, University of Chicago
Presentation
Discussion
Resources
No resources available.
Session TP-V2.V9
TP-V2.V9.1: A PROPER ORTHOGONAL DECOMPOSITION APPROACH FOR PARAMETERS REDUCTION OF SINGLE SHOT DETECTOR NETWORKS
Laura Meneghetti, Nicola Demo, Gianluigi Rozza, SISSA, Italy
TP-V2.V9.2: IMPROVED HARD EXAMPLE MINING APPROACH FOR SINGLE SHOT OBJECT DETECTORS
Aybora Koksal, Onder Tuzcuoglu, Kutalmis Gokalp Ince, A. Aydin Alatan, Middle East Technical University, Turkey; Yoldas Ataseven, ASELSAN Inc., Turkey
TP-V2.V9.3: MULTI-SCALE DEFORMABLE TRANSFORMER ENCODER BASED SINGLE-STAGE PEDESTRIAN DETECTION
Jing Yuan, Tania Stathaki, Imperial College London, United Kingdom of Great Britain and Northern Ireland; Panagiotis Barmpoutis, University College London, United Kingdom of Great Britain and Northern Ireland
TP-V2.V9.4: Class-wise FM-NMS for Knowledge Distillation of Object Detection
Lyuzhuang Liu, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi, Chubu University, Japan
TP-V2.V9.5: PREDICTING PATH LOSS DISTRIBUTIONS OF A WIRELESS COMMUNICATION SYSTEM FOR MULTIPLE BASE STATION ALTITUDES FROM SATELLITE IMAGES
Ibrahim Shoer, Koc University, Turkey; Bahadir Gunturk, Hasan Ates, Istanbul medipol university, Turkey; Tuncer Baykas, Kadir Has University, Turkey
TP-V2.V9.6: IMAGE-BASED AIR QUALITY FORECASTING THROUGH MULTI-LEVEL ATTENTION
Tony Zhang, Robert P. Dick, University of Michigan, United States of America
TP-V2.V9.7: SEQDNET: IMPROVING MISSING VALUE BY SEQUENTIAL DEPTH NETWORK
Hao Hsu, Hung-Ting Su, Jia-Fong Yeh, Chi-Ming Chung, Winston H. Hsu, National Taiwan University, Taiwan
TP-V2.V9.8: ACCELERATING A MORPHOLOGY-PRESERVING ADSORPTION MODEL BY DEEP LEARNING
Adam Hammoumi, Elsa Jolimaitre, Thibaud Chevalier, IFP Energies nouvelles, France; Maxime Moreaud, IFP Energies nouvelles/MINES ParisTech, France; Michaela Klotz, Alexey Novikov, Saint-Gobain Research Provence, France
TP-V2.V9.9: Monitoring of Varroa Infestation rate in Beehives: A Simple AI Approach
Lukas Picek, University of West Bohemia in Pilsen,, Czechia; Adam Novozamsky, Radmila C. Frydrychova, Barbara Zitova, The Czech Academy of Sciences, Czechia; Pavel Mach, ProBee, Czechia