Artificial Intelligence and Mobile Services – AIMS 2018

A Two-Stage Bi-LSTM Model for Chinese Company Name Recognition.- Multi-modal Multi-scale Speech Expression Evaluation in Computer-Assisted Language Learning.- From Global to Local: Local Popularity Prediction Using Context-embedded LSTM Recurrent Network.- Matching Low-Quality photo to DSLR-Quality with Deep Convolutional Networks.- Learning Frame-Level Recurrent Neural Networks Representations for Query-by-Example Spoken Term Detection on Mobile Devices.- Plant Identification based on Image Set Analysis.- Economic Index Forecasting via Multi-Scale Recursive Dynamic Factor Analysis.- Sub-Goal Oriented A* Search.- Towards Efficient Mobile Augmented Reality in Indoor Environments.- MAD-API: Detection, Correction and Explanation of API Misuses in Distributed Android Applications.- Relaxed Event-triggered Control of Networked Control Systems under Denial of Service Attacks.- Sentiment Analysis Based on Hybrid Bi-Attention mechanism in Mobile Application.- Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment.- AICDS: An infant crying detection system based on lightweight convolutional neural network.- Exploring Trends of Lung Cancer Research Based on Word Representation.- Effective Facial Obstructions Removal With Enhanced Cycle-Consistent Generative Adversarial Networks.- Applied Analysis of Social Network Data in Personal Credit Evaluation.- Deep Neural Network Based Frame Reconstruction For Optimized Video Coding.- Detection and tracking of moving objects system for indoor mobile robots with a low-cost laser scanner.- Using IT/IS Applications to Empower Physically Challenged Individuals to Enjoy a High Quality of Life.<br> <br>