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Early-Cycle Internal Impedance Enables ML-Based Battery Cycle Life Predictions Across Manufacturers
Predicting the end-of-life (EOL) of lithium-ion batteries across different manufacturers presents significant challenges due to variations in electrode materials, manufacturing processes, cell formats, and a lack of generally available data.
EaZy Learning: An Adaptive Variant of Ensemble Learning for Fingerprint Liveness Detection
EaZy learning is similar to ensemble learning as it generates an ensemble of base classifiers and integrates them to make a prediction.
AILearn: An Adaptive Incremental Learning Model for Spoof Fingerprint Detection
AILearn is an adaptive incremental learning model which adapts to the features of the ``live'' and ``spoof'' fingerprint images and efficiently recognizes the new spoof fingerprints as well as the known spoof fingerprints when the new data is available.
EILearn: Learning Incrementally Using Previous Knowledge Obtained From an Ensemble of Classifiers
In incremental learning, the general convention is to use only the knowledge acquired in the previous phase but not the previously seen data.
Structuring an unordered text document
Segmenting an unordered text document into different sections is a very useful task in many text processing applications like multiple document summarization, question answering, etc.
Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks
Object detection-the computer vision task dealing with detecting instances of objects of a certain class (e. g., 'car', 'plane', etc.)
