81 citations · 122 across the 7 of their papers we have counts for
7 papers
TastepepAI, An artificial intelligence platform for taste peptide de novo design
Jianda Yue, Tingting Li, Jian Ouyang +8
Taste peptides have emerged as promising natural flavoring agents attributed to their unique organoleptic properties, high safety profile, and potential health benefits. However, t…
DS-MVSNet: Unsupervised Multi-view Stereo via Depth Synthesis
Jingliang Li, Zhengda Lu, Yiqun Wang +2
In recent years, supervised or unsupervised learning-based MVS methods achieved excellent performance compared with traditional methods. However, these methods only use the probabi…
SWA Object Detection
Haoyang Zhang, Ying Wang, Feras Dayoub +1
Do you want to improve 1.0 AP for your object detector without any inference cost and any change to your detector? Let us tell you such a recipe. It is surprisingly simple: train y…
VarifocalNet: An IoU-aware Dense Object Detector
Haoyang Zhang, Ying Wang, Feras Dayoub +1
Accurately ranking the vast number of candidate detections is crucial for dense object detectors to achieve high performance. Prior work uses the classification score or a combinat…
You Only Search Once: A Fast Automation Framework for Single-Stage DNN/Accelerator Co-design
Weiwei Chen, Ying Wang, Shuang Yang +2
DNN/Accelerator co-design has shown great potential in improving QoR and performance. Typical approaches separate the design flow into two-stage: (1) designing an application-speci…
Bayesian Bits: Unifying Quantization and Pruning
Mart van Baalen, Christos Louizos, Markus Nagel +4
We introduce Bayesian Bits, a practical method for joint mixed precision quantization and pruning through gradient based optimization. Bayesian Bits employs a novel decomposition o…
Structured Sparse Method for Hyperspectral Unmixing
Feiyun Zhu, Ying Wang, Shiming Xiang +2
Hyperspectral Unmixing (HU) has received increasing attention in the past decades due to its ability of unveiling information latent in hyperspectral data. Unfortunately, most exis…