Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Kang, Byungkon"'
Driver motion recognition is a principal factor in ensuring the safety of driving systems. This paper presents a novel system for learning and predicting driver motions and an event-based high-resolution (1280x720) dataset, N-DriverMotion, newly coll
Externí odkaz:
http://arxiv.org/abs/2408.13379
It has become common practice now to use random initialization schemes, rather than the pre-trained embeddings, when training transformer based models from scratch. Indeed, we find that pre-trained word embeddings from GloVe, and some sub-word embedd
Externí odkaz:
http://arxiv.org/abs/2407.12514
With the increasing complexity of machine learning models, managing computational resources like memory and processing power has become a critical concern. Mixed precision techniques, which leverage different numerical precisions during model trainin
Externí odkaz:
http://arxiv.org/abs/2305.10947
Lowering the precision of neural networks from the prevalent 32-bit precision has long been considered harmful to performance, despite the gain in space and time. Many works propose various techniques to implement half-precision neural networks, but
Externí odkaz:
http://arxiv.org/abs/2301.12809
The MINSU(Mobile Inventory and Scanning Unit) algorithm uses the computational vision analysis method to record the residual quantity/fullness of the cabinet. To do so, it goes through a five-step method: object detection, foreground subtraction, K-m
Externí odkaz:
http://arxiv.org/abs/2204.06681
Recent progress in deep learning-based models has improved photo-realistic (or perceptual) single-image super-resolution significantly. However, despite their powerful performance, many methods are difficult to apply to real-world applications becaus
Externí odkaz:
http://arxiv.org/abs/1903.02240
Image distortion classification and detection is an important task in many applications. For example when compressing images, if we know the exact location of the distortion, then it is possible to re-compress images by adjusting the local compressio
Externí odkaz:
http://arxiv.org/abs/1805.10881
In recent years, deep learning methods have been successfully applied to single-image super-resolution tasks. Despite their great performances, deep learning methods cannot be easily applied to real-world applications due to the requirement of heavy
Externí odkaz:
http://arxiv.org/abs/1803.08664
Publikováno v:
In Pattern Recognition July 2022 127
Akademický článek
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