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Morphological Skip-Gram: Using morphological knowledge to improve word representation
In this work, we propose a new method for training word embeddings, and its goal is to replace the FastText bag of character n-grams for a bag of word morphemes through the morphological analysis of the word.
Learning to associate detections for real-time multiple object tracking
With the recent advances in the object detection research field, tracking-by-detection has become the leading paradigm adopted by multi-object tracking algorithms.
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