5 accepted papers
Deep learning has achieved success across many domains when sufficient training samples are available. However, the commonly used mini-batch stochastic gradient descent (SGD) training paradigm treats each sample equally, resulting in massive computational waste on samples that are easily identifiabl…
Personalized keyword spotting (KWS) with few enrollment utterances remains an important problem over years. KWS remains a challenging task due to the following factors, including the scarcity of enrollment samples, speech variation in the open-set scenarios, and distributional gap between source and…
Keyword Spotting (KWS) is crucial for hands-free voice-activated systems, requiring a balance between accuracy and complexity, especially in noisy environments. While Speech Enhancement (SE) can improve KWS accuracy, existing methods often lack the ability to effectively utilize the rich features pr…
In many situations such as city delivery and wild inspection, quadrotors are often required to follow a predefined reference trajectory. However, these reference trajectories cannot be perfectly safe, resulting in conflicts between tracking the reference precisely, flying safely, and finishing the m…
In recent years, multirotors have become more and more widely used, such as in aerial photography and delivery. Ensuring a safe landing in emergencies is the most basic requirement, and it is important to make full use of all the sensors of the multirotor. To improve the safety of UAV landing in unk…