Paper Title: Individual Tiger Identification using Transfer Learning   Authors: Shailendra Singh Kathait, Co-Founder and Chief Data Scientist, Valiance Analytics Pvt. Ltd., Noida, Uttar Pradesh Vaibhav Singh, Data Scientist, Valiance Analytics Pvt. Ltd., Noida, Uttar Pradesh Ashish Kumar, Principal Data Scientist, Valiance Analytics Pvt. Ltd.,Noida, Uttar Pradesh   Summary: The research paper “Individual Tiger Identification …

Paper Title: Deep Learning-based Model for Wildlife Species Classification Authors: Shailendra Singh Kathait, Ashish Kumar, Piyush Dhuliya and Ikshu Chauhan Summary: Motion-activated cameras have become ubiquitous in ecological parks and wildlife sanctuaries, capturing images upon sensor-triggered motion, including infrared visuals that were once impractical. Despite this technological leap, extracting pertinent wildlife information from the vast …

Paper Title: Custom Deep Neural Network For Message Scoring Authors: Shailendra Singh Kathait, Ashish Kumar and Ikshu Chauhan Summary: This paper offers customized message scoring creation of Technical Literature of Drugs using Text Analytics and Deep Learning. A customized Deep Learning driven model has beendeveloped that feeds scientific data (texts) about medicine(s) (written by medical …

This whitepaper proposes a holistic approach for Machine Learning driven defect detection and categorisation in Manufacturing industry!

In this paper, an unsupervised approach for the automated tagging of articles in the Chinese language has been implemented. Unlike the English characters, Chinese characters do not make use of separators.

This paper enlightens the way companies can design Intelligent System to understand their customers’ sentiments better to improve their experience, which will help the businesses change their market position.

This paper proposes an equipment reliability model designed by applying data extraction algorithm on equipment maintenance records residing in SAP application.

This paper highlights a comparison between different time series forecasting algorithms for forecasting noisy time series data. Neural networks based time series forecasting proved to be more accurate & robust.

Hybridised intelligent systems are more adaptable to solving real-world complex problems. In this paper, an attempt has been made to show how a hybrid system involving fuzzy regression analysis and Bayesian Gaussian reasoning can be designed.

This paper enlightens the way unsupervised learning can be used to extract key-phrases for automated tagging of text, with significant accuracy.