Dahua Li's research while affiliated with Tianjin University of Technology and other places
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Publications (9)
italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Emotion analysis has been employed in many fields such as human-computer interaction, rehabilitation, and neuroscience. But most emotion analysis methods mainly focus on healthy controls or depression patients. This paper aims to classify the emotional...
Recent research on emotion recognition suggests that deep network-based adversarial learning has an ability to solve the cross-subject problem of emotion recognition. This study constructed a hearing-impaired electroencephalography (EEG) emotion dataset containing three emotions (positive, neutral, and negative) in 15 subjects. The emotional domain...
Emotion recognition based on electroencephalogram (EEG) signals has been one of the most active research topics of affective computing. In previous studies of emotion recognition, the selection of stimulus sources was usually focused on single stimuli, such as visual or auditory. In this work, we propose a novel emotional stimulation scheme that sy...
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In recent years, many researchers have explored different methods to obtain discriminative features for electroencephalogram-based (EEG-based) emotion recognition, but a few studies have been investigated on deaf subjects. In this study, we have established a deaf EEG emotion data set, which contains three kinds of emotion (positive, neutral, and n...
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With the development of science and technology, inspection robots have attracted more and more attention, and research on the automatic reading of pointer instruments through inspection robots has become particularly valuable. Aiming at the problems of uneven illumination, complex dial background and damping fluid interference of the collected inst...
Feature fusion is widely used in various neural network-based visual recognition tasks, such as object detection, to enhance the quality of feature representation. It is common practice for both the one-stage object detectors and the two-stage object detectors to implement feature fusion in feature pyramid networks (FPN) to enhance the capacity to...
Citations
... For example, the difference of the feature distribution between source and target domains is narrowed by the deep domain confusion model for cross subject recognition [176]. Recent algorithms like Deep CORAL [177], Deep Adaptation Networks [178], Deep Subdomain Associate Adaptation Network (DSAAN) [179] and Emotional Domain Adversarial Neural Network (EDANN) [180] are recommended to reduce domain differences. Despite the advances in DA models, few algorithms were applied to medical data [175]. ...
... While the second are more frequently related to passive methods, like mono-vision [21], stereovision [22], multi-camera [23]. One already known method that uses both principles of active and passive methods is based on structured light [24]. From this fundaments, specialized methods emerge, each of them develop or applying techniques such as signal, image and data processing through algorithms, filtering, enhancement, sharpening, restoration, segmentation, object detection, compression, manipulation, augmentation, registration, clustering and outliers removal, to mention some. ...
... These facts open up the door for EEG as a potential low cost and portable alternative to neuroimaging techniques as far as brain mapping [16]. EEG is currently used in many applications, including medical [17], emotion recognition [18], computer-brain interface (CBI) [19], and neuromarketing [20]. Conceivably, an EEG system may be used either alone or in combination with neuroimaging tests to provide a high level of accuracy in detecting TBI. ...
... Due to the loss of a key channel during the process of emotion communication, the individuals with hearing impairment can only compensate for changes in the outside world through senses such as vision and touch. Therefore, the individuals with hearing impairment are more sensitive to emotional perception, and may have differences in recognition of emotion from healthy controls [18] - [20]. ...
... However, the second method, in general, yields better results with less computational power [9][10][11]. Moreover, the image subtraction method has also been used to segment the region of the pointer [12,13]. This method is often performed before the straight-line fitting method to increase the robustness of the pointer detection by eliminating the background interference. ...
... Object detection is one of the most challenging tasks in computer vision, and has witnessed great progress in recent years [19][20][21][22][23]. Existing CNN-based object detectors can be roughly divided into anchor-based and anchor-free detectors. ...
