3 papers
eess.IV2025
Rethinking Medical Anomaly Detection in Brain MRI: An Image Quality Assessment Perspective
Zixuan Pan, Jun Xia, Zheyu Yan +7
Reconstruction-based methods, particularly those leveraging autoencoders, have been widely adopted for anomaly detection task in brain MRI. Unlike most existing works try to improv…
cs.AR2024
A 10.60 W 150 GOPS Mixed-Bit-Width Sparse CNN Accelerator for Life-Threatening Ventricular Arrhythmia Detection
Yifan Qin, Zhenge Jia, Zheyu Yan +9
This paper proposes an ultra-low power, mixed-bit-width sparse convolutional neural network (CNN) accelerator to accelerate ventricular arrhythmia (VA) detection. The chip achieves…
cs.LG2024
Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices
Ruiyang Qin, Dancheng Liu, Chenhui Xu +9
The scaling laws have become the de facto guidelines for designing large language models (LLMs), but they were studied under the assumption of unlimited computing resources for bot…