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Six-Channel Image Representation for Cross-Domain Object Detection.

, , and . ICIG (1), volume 12888 of Lecture Notes in Computer Science, page 171-184. Springer, (2021)

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Object Detection with Convolutional Neural Networks., , , , and . CoRR, (2019)Why Layer-Wise Learning is Hard to Scale-up and a Possible Solution via Accelerated Downsampling., , , and . ICTAI, page 238-243. IEEE, (2020)Object Detection and Classification based on Hierarchical Semantic Features and Deep Neural Networks.. University of Kansas, Lawrence, USA, (2021)base-search.net (ftunivkansas:oai:kuscholarworks.ku.edu:1808/34305).MDFN: Multi-Scale Deep Feature Learning Network for Object Detection., , , and . CoRR, (2019)MDCN: Multi-Scale, Deep Inception Convolutional Neural Networks for Efficient Object Detection., , , and . ICPR, page 2510-2515. IEEE Computer Society, (2018)Six-Channel Image Representation for Cross-Domain Object Detection., , and . ICIG (1), volume 12888 of Lecture Notes in Computer Science, page 171-184. Springer, (2021)Multi-Resolution Fusion and Multi-scale Input Priors Based Crowd Counting., , and . ICPR, page 5790-5797. IEEE, (2020)Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters., , , and . WACV, page 1044-1048. IEEE, (2020)Traffic flow forecasting research based on Bayesian normalized Elman neural network., and . SP/SPE, page 426-430. IEEE, (2015)VisDrone-DET2018: The Vision Meets Drone Object Detection in Image Challenge Results., , , , , , , , , and 95 other author(s). ECCV Workshops (5), volume 11133 of Lecture Notes in Computer Science, page 437-468. Springer, (2018)