Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
A review of generalizable transfer learning in automatic emotion recognition
Automatic emotion recognition is the process of identifying human emotion from signals
such as facial expression, speech, and text. Collecting and labeling such signals is often …
such as facial expression, speech, and text. Collecting and labeling such signals is often …
Latent backdoor attacks on deep neural networks
Recent work proposed the concept of backdoor attacks on deep neural networks (DNNs),
where misclassification rules are hidden inside normal models, only to be triggered by very …
where misclassification rules are hidden inside normal models, only to be triggered by very …
Speech model pre-training for end-to-end spoken language understanding
Whereas conventional spoken language understanding (SLU) systems map speech to text,
and then text to intent, end-to-end SLU systems map speech directly to intent through a …
and then text to intent, end-to-end SLU systems map speech directly to intent through a …
Transfer learning for low-resource neural machine translation
The encoder-decoder framework for neural machine translation (NMT) has been shown
effective in large data scenarios, but is much less effective for low-resource languages. We …
effective in large data scenarios, but is much less effective for low-resource languages. We …
Deep learning and transfer learning models of energy consumption forecasting for a building with poor information data
Precise prediction of energy consumption in buildings could significantly optimize strategies
for operating building equipment and release the energy savings potential of buildings. With …
for operating building equipment and release the energy savings potential of buildings. With …
Cross corpus multi-lingual speech emotion recognition using ensemble learning
Receiving an accurate emotional response from robots has been a challenging task for
researchers for the past few years. With the advancements in technology, robots like service …
researchers for the past few years. With the advancements in technology, robots like service …
Deep learning-based late fusion of multimodal information for emotion classification of music video
YR Pandeya, J Lee - Multimedia Tools and Applications, 2021 - Springer
Affective computing is an emerging area of research that aims to enable intelligent systems
to recognize, feel, infer and interpret human emotions. The widely spread online and off-line …
to recognize, feel, infer and interpret human emotions. The widely spread online and off-line …
How transferable are neural networks in nlp applications?
Transfer learning is aimed to make use of valuable knowledge in a source domain to help
model performance in a target domain. It is particularly important to neural networks, which …
model performance in a target domain. It is particularly important to neural networks, which …
Towards making the most of bert in neural machine translation
GPT-2 and BERT demonstrate the effectiveness of using pre-trained language models (LMs)
on various natural language processing tasks. However, LM fine-tuning often suffers from …
on various natural language processing tasks. However, LM fine-tuning often suffers from …