Published in Artificial intelligence review
In the current era of the digital world, the hash of any digital means considered as a footprint or fingerprint of any digital term but from the ancient era, human fingerprint considered as the most trustworthy criteria for identification and it also cannot be changed with time even up to the death of an individual. In the court of law, fingerprint...
Published in Artificial intelligence review
With the spiraling pandemic of the Coronavirus Disease 2019 (COVID-19), it has becoming inherently important to disseminate accurate and timely information about the disease. Due to the ubiquity of Internet connectivity and smart devices, social sensing is emerging as a dynamic AI-driven sensing paradigm to extract real-time observations from onlin...
Published in Artificial Intelligence Review
Artificial neural networks (ANNs) have achieved significant success in tackling classical and modern machine learning problems. As learning problems grow in scale and complexity, and expand into multi-disciplinary territory, a more modular approach for scaling ANNs will be needed. Modular neural networks (MNNs) are neural networks that embody the c...
Published in Artificial Intelligence Review
Gearbox is an important part of mechanical equipment. If a fault cannot be timely detected, it will cause significant economic losses. In order to solve the problem of early fault diagnosis quickly and accurately, this paper proposes a feature extraction method by the decomposition of feature value to the waveform of signal, and inputs the extracte...
Published in Artificial Intelligence Review
Deep convolutional network is commonly stacked by vast number of nonlinear convolutional layers. Deep fused network can improve the training process of deep convolutional network due to its capability of learning multi-scale representations and of optimizing information flow. However, the depth in a deep fused network does not contribute to the ove...
Published in Artificial Intelligence Review
Electroencephalogram (EEG) signals can be used to identify the human brain in different disease conditions. Nonetheless, it is difficult to detect the subtle and vital differences in EEG simply by visual inspection because of the non-stationary nature of EEG signals. Specifically, in order to find the epileptogenic focus for medical treatment in th...
Published in Artificial Intelligence Review
Hand gestures are spatio-temporal patterns which can be characterized by collections of spatio-temporal features. Recognition of hand gestures is to find the re-occurrences of such spatio-temporal patterns through pattern matching. However, dynamic hand gestures have many obstacles for accurate recognition, including poor lighting conditions, camer...
Published in Artificial Intelligence Review
Forecasting is a very important and difficult task for various economic activities. Despite the great evolution of time series modeling, forecasters are still in the hunt for better strategies to improve mathematical models and come up with more accurate predictions. In this respect, several new models, mixing autoregressive processes to artificial...
Published in Artificial Intelligence Review
Many feature weighting methods have been proposed to evaluate feature saliencies in recent years. Neural-network (NN) feature weighting, as a supervised method, is founded upon the mapping from input features to output decisions, and implemented by evaluating the sensitivity of network outputs to its inputs. Through training on sample data, NN impl...
Published in Artificial Intelligence Review
Named entity recognition (NER) is an important natural language processing (NLP) task with many applications. We tackle the problem of Arabic NER using deep learning based on Arabic word embeddings that capture syntactic and semantic relationships between words. Deep learning has been shown to perform significantly better than other approaches for ...
