Although backpropagation neural networks generally predict better than decision trees do for pattern classiication problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, more often than not, explicit knowledge is needed by human experts. This work drives a symbolic representation for neural networks to make...

Cell replacement therapy and gene transfer to the diseased or injured brain have provided the basis for the development of potentially powerful new therapeutic strategies for a broad spectrum of human neurological diseases including Parkinson disease, Huntington disease, amyotrophic lateral sclerosis (ALS), Alzheimer disease, multiple sclerosis (MS), stroke, spinal cord injury and brain cancer....

In this paper, the evolutionary neural trees (ENT) are applied to forecasing the high-frequency stock returns of Heng-Sheng stock index on December, 1998. To understand what may con-sistute an eeective implementation, six experiments are conducted. These experiments are diierent in data-preprocessing procedures, sample sizes, search intensity and complexity regularization. Our results shows tha...

Convolutional Nerual Networks (CNN) have emerged as powerful tools for learning discriminative image features. In this paper, we propose a framework of 3-D fully CNN models for Glioblastoma segmentation from multi-modality MRI data. By generalizing CNN models to true 3-D convolutions in learning 3-D tumor MRI data, the proposed approach utilizes a unique network architecture to decouple image p...

Multi-character recognition in arbitrary photographs on mobile platform is difficult, in terms of both accuracy and real-time performance. In this paper, we focus on the domain of hand-written multi-digit recognition. Convolutional neural network (CNN) is the state-of-the-art solution for object recognition, and presents a workload that is both compute and data intensive. To reduce the workload...

To extract medical clinical related entity mention from patient clinical records is an essential step in clinical research. Recently, many researchers employ neural architecture to tackle the similar task of clinical concept extraction or drug name recognition from English clinical records, and have got prominent progress. However, most previous systems on Chinese Clinical Named Entity Recognit...

Software project management has always faced challenges that have often had a great impact on the outcome of projects in future. For this, Managers of software projects always seek solutions against challenges. The implementation of unguaranteed approaches or mere personal experiences by managers does not necessarily suffice for solving the problems. Therefore, the management area of software p...