Search Results for author:
Found 10 papers, 3 papers with code
The Internet of Responsibilities-Connecting Human Responsibilities using Big Data and Blockchain
Accountability in the workplace is critically important and remains a challenging problem, especially with respect to workplace safety management.
Attention Mechanism based Cognition-level Scene Understanding
Given a question-image input, the Visual Commonsense Reasoning (VCR) model can predict an answer with the corresponding rationale, which requires inference ability from the real world.
A Generic Knowledge Based Medical Diagnosis Expert System
The proposed disease diagnosis system also uses a graphical user interface (GUI) to facilitate users to interact with the expert system.
Interpretable Visual Understanding with Cognitive Attention Network
While image understanding on recognition-level has achieved remarkable advancements, reliable visual scene understanding requires comprehensive image understanding on recognition-level but also cognition-level, which calls for exploiting the multi-source information as well as learning different levels of understanding and extensive commonsense knowledge.
Cognitive Visual Commonsense Reasoning Using Dynamic Working Memory
Moreover, the proposed model provides intuitive interpretation into visual commonsense reasoning.
LSTM Based Sentiment Analysis for Cryptocurrency Prediction
Recent studies in big data analytics and natural language processing develop automatic techniques in analyzing sentiment in the social media information.
Responsibility Management through Responsibility Networks
The safety management is critically important in the workplace.
Using Machine Learning to Automate Mammogram Images Analysis
Early detection of breast cancer in X-ray mammography is believed to have effectively reduced the mortality rate.
A Data-driven Human Responsibility Management System
An ideal safe workplace is described as a place where staffs fulfill responsibilities in a well-organized order, potential hazardous events are being monitored in real-time, as well as the number of accidents and relevant damages are minimized.
Exploring Dynamic Context for Multi-path Trajectory Prediction
In our framework, first, the spatial context between agents is explored by using self-attention architectures.
