Description
Book Synopsis.- Technical Papers.
.- NER Explainability Framework: Utilizing LIME to Enhance Clarity and Robustness in Named Entity Recognition.
.- Neural Nets.
.- Revealing limitations of ResNet models for deep evaluation in chess.
.- Quasi Biologically Plausible Category Learning.
.- On the Development of a Pixel-wise Plastic Waste Identification System for Multispectral Remote Sensing Applications.
.- Streamlining Attention for Text Classification: Sequence Length Reduction with Pooling Attention.
.- LSTM for Modelling and Predictive Control of Multivariable Processes.
.- Structured Radial Basis Function Network: Modelling Diversity for Multiple Hypotheses Prediction.
.- Deep Learning.
.- Bitcoin Forecasting using Deep Learning and Time Series Ensemble Techniques.
.- TRAPL: Transformer-based Patch Learning
