Titlebook: International Conference on Innovative Computing and Communications; Proceedings of ICICC Ashish Khanna,Deepak Gupta,Ajay Jaiswal Conferenc

Functional

Intensity of Traffic Due to Road Accidents in US: A Predictive Model,omic and social damage caused. The present research is an attempt to analyse data that might be useful in determining the effect on traffic during an accident. It is hypothesised that accurate traffic congestion intensity forecast will empower travellers to choose different routes, departure times a

Calibrate

全能

圖表證明

aspersion

Heart Disease Prediction Using Machine Learning Techniques: A Quantitative Review,ing of blood vessels and can cause coronary artery infections that in turn lead to weakening of patient’s body. Therefore, there is a need for reliable, accurate, and feasible system that can diagnose the heart disease on time so that the cardiac patient is given an efficient treatment before it lea

有毒

Enhancing CNN with Pre-processing Stage in Illumination-Invariant Automatic Expression Recognition,worked upon recognizing basic emotions like sad, happy, angry, fear, neutral, disgust and surprise through machine learning. Nowadays, deep learning is attracting the researcher in solving the real-word problems. In this research, convolutional neural network (CNN) was implemented with four differen

符合國情

tic-douloureux

myopia

,Predicting Prior Academic Failure of Students’ Using Machine Learning Approach,ing approach. The present research work can be broadly categorized into two modules. Firstly, data pre-processing directed on real-time data of Government Polytechnic College Ambala, Haryana, India. Secondly, desired data collected along with exploratory data analysis and human-interpretable feature

礦石

Deep Classifier for News Text Classification Using Topic Modeling Approach,pproaches have been proposed by researchers in this field of natural language processing (NLP). In most of existing approaches, semantics of the text is not taken in consideration, which in turn is not always realistic. In this paper, proposal of keeping the semantic relationship intact by not remov