Titlebook: Soft Computing and Its Engineering Applications; 4th International Co Kanubhai K. Patel,K. C. Santosh,Ashish Ghosh Conference proceedings 2

Junction

Explainable AI for Predictive Analytics on Employee AttritionInterpretable Model-Agnostic Explanations to analyze the key factors behind employees leaving the organizations. The current work managed to accurately create a prediction model with a score of 96% and detect three key features behind employee’s decision of staying or leaving any organization.

Wernickes-area

Graph Convolutional Neural Networks for Nuclei Segmentation from Histopathology Imagesi segmentation. The proposed model achieved an accuracy, Dice coefficient, Intersection over Union (IoU), precision and recall scores of 90.75%, 83.74%, 83.2%, 75.40% and 79.93% respectively on a UCSB bio-segmentation benchmark breast histopathology dataset.

lethargy

Performance Analysis of Cache Memory in CPUgram is run on four computer systems with different specifications to check the performance and understand the cache levels. The problem size, i.e. the execution of the benchmark program is defined to get iterations and plotting comparison curves for time and throughput analysis for test cases of co

coagulate

Extraction of Single Chemical Structure from Handwritten Complex Chemical Structure with Junction Potion of an image has been achieved with morphological thinning. The proposed approach accepts the scanned image of HCCS as an input, and it produced the images of isolated chemical structures as an output.

Engaging

Automatic Mapping of Deciduous and Evergreen Forest by Using Machine Learning and Satellite Imagery0 m spatial resolution) namely Near-infrared (NIR), visible light band (Blue, Green and Red) are stacked for classification. In this study, overall classification accuracy attained by RF and k-NN is 81.52% (kappa value of 0.759) and 80.84% (kappa value of 0.751) respectively. Results indicates that