Identification of each animal in a collective becomes possible even when individuals are never all visible simultaneously, enabling faster and more accurate analysis of collective behavior.
Abstract: As a prominent research topic, multi-view multi-label classification (MvMlC) aims to assign multiple labels to samples by integrating information from various perspectives. However, in ...
GrainMIL: Automated Grain Damage Classification from Weak Labels via Deep Multiple Instance Learning
Abstract: Visual analysis is essential for ensuring the quality and safety of cereal grains. However, the traditional manual process is subjective and inconsistent which motivates the need for ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results