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Despite the recent success of deep-learning based semantic segmentation, deploying a pre-trained road scene segmenter to a city whose images are not presented in the training set would not achieve satisfactory performance due to dataset biases. Instead of collecting a large number of annotated images of each city of interest to train or refine the segmenter, we propose an unsupervised learning approach...
As an artificial intelligent technique, artificial neural networks (ANNs) have been applied successfully in a wide range of fields due to its effective learning ability. In this paper, we conduct an empirical application on fragrance bottle form design due to its wide variety of appearances. For getting a better structure of the ANN model to develop the consumer-oriented expert system, we conduct...
We have proposed a spatial-cue based binaural noise reduction algorithm for hearing aids. However, in that algorithm, decision parameters are empirically selected. In this paper, we extend the work and propose a supervised classification algorithm for binaural speech enhancement/separation and dereverberation using a modified ideal binary mask (mIBM) as the training target and simple neural networks...
The proportion of aged population nowadays almost rises acutely in each countries, which resulted from the increasing life expectancy and falling fertility rates. The impairment of mobility is a major health concern for the elderly. While the more decline of daily activities, more dangerous the elderly would be. The design of an image-based surveillance system for tracking elderly's activities in...
Marine simulator has been widely applied to the seafarer training and examination. But, there have been still no standardized criteria on evaluation of the operation level of the trainees, which can influence the training quality and the effectiveness of the evaluation results. Therefore, it is extremely necessary to establish an automatic assessment system for operations on marine simulator. Besides,...
In this work, we develop an appearance-based gaze tracking system allowing user to move their head freely. The main difficulty of the appearance-based gaze tracking method is that the eye appearance is sensitive to head orientation. To overcome the difficulty, we propose a 3-D gaze tracking method combining head pose tracking and appearance-based gaze estimation. We use a random forest approach to...
Data is only as good as the similarity metric used to compare it. The all important notion of similarity allows us to leverage knowledge derived from prior observations to predict characteristics of new samples. In this paper we consider the problem of compiling a consistent and accurate view of similarity given its multiple incomplete and noisy approximations. We propose a new technique called Multiple...
This paper presents a predictive space aggregated regression based boosting algorithm, and its application in classifying the Continuous Wave(CW) Flow Doppler image data set with the diseases of stenosis and regurgitation in mitral and aortic valves. The proposed algorithm involves finding a way to simultaneously combine all the weak learners based on a well-justified assumption as in the previous...
This paper addresses the problem of human activity recognition based on wearable sensors. In resent years researches on human daily activity recognition have enabled impressive result on substantial amount of labeled training samples. However, unlabeled samples are readily available but labeled ones are often difficult and slow to obtain. In order to reduce the level of supervision, this paper analyzes...
This paper presents a novel classification via aggregated regression algorithm - dubbed CAVIAR - and its application to the OASIS MRI brain image database. The CAVIAR algorithm simultaneously combines a set of weak learners based on the assumption that the weight combination for the final strong hypothesis in CAVIAR depends on both the weak learners and the training data. A regularization scheme using...
With the purpose of designing a general learning framework for detecting human parts, we formulate this task as a classification problem over non-aligned training examples of multiple classes. We propose a new multi-class multi-instance boosting method, named MCMIBoost, for effective human parts detection in static images. MCMIBoost has two benefits. First, training examples are represented as a set...
If sedimentation of constructions exceeds the prescribed limits, it would give rise to huge losses for community and people, so it is significant to establish the effective and practical deformation forecasting model for the safe operation and economic development. With the unique non-linear, non-convexity, non-locality, non-steadiness, adaptability and powerful ability of calculation and information...
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