3 papers
cs.SD2022
I2CR: Improving Noise Robustness on Keyword Spotting Using Inter-Intra Contrastive Regularization
Dianwen Ng, Jia Qi Yip, Tanmay Surana +6
Noise robustness in keyword spotting remains a challenge as many models fail to overcome the heavy influence of noises, causing the deterioration of the quality of feature embeddin…
cs.LG2018
A Cost-Sensitive Deep Belief Network for Imbalanced Classification
Chong Zhang, Kay Chen Tan, Haizhou Li +1
Imbalanced data with a skewed class distribution are common in many real-world applications. Deep Belief Network (DBN) is a machine learning technique that is effective in classifi…
eess.SP2018
A Multi-State Diagnosis and Prognosis Framework with Feature Learning for Tool Condition Monitoring
Chong Zhang, Geok Soon Hong, Jun-Hong Zhou +5
In this paper, a multi-state diagnosis and prognosis (MDP) framework is proposed for tool condition monitoring via a deep belief network based multi-state approach (DBNMS). For fau…