Chen Jason Zhang

TL;DR: Wang et al. as discussed by the authors built a large dataset of community-acquired pneumonia consisting of 35389 cases (distinguished from nosocomial pneumonia) based on actual medical records and trained a prediction model with the chest X-ray images in their dataset, capable of precisely detecting pneumonia.

TL;DR: ROLLER is presented, which takes a different construction-based approach to generate kernels, using rTile, a new tile abstraction that encapsulates tensor shapes that align with the key features of the underlying accelerator, thus achieving efficient execution by limiting the shape choices.

TL;DR: The Visual Object Tracking challenge VOT2022 as mentioned in this paper was composed of seven sub-challenges focusing on different tracking domains: (i) VOT-STs2022 challenge focused on short-term tracking in RGB by segmentation, (ii) VOTE-STb2022 challenging was focused on real-time short-time tracking by bounding boxes, (iii) VODE-RTb2021 challenge was concerned with segmentation of RGB and depth-only images, and (iv) as mentioned in this paper focused on long-term longterm tracking by coping with target disappearance and reappearance.

TL;DR: This work further extends the existing wideband systems to enable full-band (48kHz) speech enhancement while simultaneously ensuring automatic speech recognition compatibility and optionally, personalized speech enhancement by employing a multi-stage and multi-loss training architecture that incorporates the recently proposed two-step structure.