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Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training
For EEG classification many models have been developed with layer types and architectures we typically do not see in time series classification.
Towards Comparable Active Learning
Active Learning has received significant attention in the field of machine learning for its potential in selecting the most informative samples for labeling, thereby reducing data annotation costs.
Towards Comparable Knowledge Distillation in Semantic Image Segmentation
Knowledge Distillation (KD) is one proposed solution to large model sizes and slow inference speed in semantic segmentation.
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development
ML can be seen as a set of tools that contribute to the automation of the whole experimental cycle, including model building and practical planning, thus allowing human experts to focus on the more demanding and overarching cognitive tasks.
Reinforcement Learning Approach to Active Learning for Image Classification
The ever-growing penetration of machine learning algorithms in new application areas requires solutions for the need for data in those new domains.
