In recent years, neural image compression emerges as a rapidly developing topic in computer vision, where the state-of-the-art approaches now exhibit superior compression performance than their conventional counterparts.
The audio-video based emotion recognition aims to classify a given video into basic emotions.
We demonstrate that f-SpecAugment is more effective than the utterance level SpecAugment for deep CNN based hybrid models.
We believe the proposed method will benefit astronomy and cosmology, where a large number of unlabeled multi-band images are available, but acquiring image labels is costly.
Although there is no consensus on a definition, human emotional states usually can be apperceived by auditory and visual systems.
no code implementations • 17 Oct 2018 • Zhenghang Zhong, Zhe Tang, Xiangxing Li, Tiancheng Yuan, Yang Yang, Meng Wei, Yuanyuan Zhang, Renzhi Sheng, Naomi Grant, Chongfeng Ling, Xintao Huan, Kyeong Soo Kim, Sanghyuk Lee
In this paper, we present a new location fingerprinting database comprised of Wi-Fi received signal strength (RSS) and geomagnetic field intensity measured with multiple devices at a multi-floor building in Xi'an Jiatong-Liverpool University, Suzhou, China.
In this paper, we present a novel attention based fully convolutional network for speech emotion recognition.
In two harmonized efficacy studies to prevent HIV infection through multiple infusions of the monoclonal antibody VRC01, a key objective is to evaluate whether the serum concentration of VRC01, which changes cyclically over time along with the infusion schedule, is associated with the rate of HIV infection.