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Besichtigung eines Unglücks : Roman
Een overlevende van een treinongeluk in 1939 doet voorkomen alsof ze de vrouw van een omgekomen Italiaan is, terwijl ze in werkelijkheid met een jood verloofd was. NL-ZmNBD.
Book
A Brief Review of Facial Emotion Recognition Based on Visual Information
Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Although FER can be conducted using multiple sensors, this review focuses on studies that exclusively use facial images, because visual expressions are one of the main information channels in interpersonal communication. This paper provides a brief review of researches in the field of FER conducted over the past decades. First, conventional FER approaches are described along with a summary of the representative categories of FER systems and their main algorithms. Deep-learning-based FER approaches using deep networks enabling “end-to-end” learning are then presented. This review also focuses on an up-to-date hybrid deep-learning approach combining a convolutional neural network (CNN) for the spatial features of an individual frame and long short-term memory (LSTM) for temporal features of consecutive frames. In the later part of this paper, a brief review of publicly available evaluation metrics is given, and a comparison with benchmark results, which are a standard for a quantitative comparison of FER researches, is described. This review can serve as a brief guidebook to newcomers in the field of FER, providing basic knowledge and a general understanding of the latest state-of-the-art studies, as well as to experienced researchers looking for productive directions for future work.
Journal Article
Tracks to the trenches : Canadian railway troops in the Great War (1914-1919)
\"Tracks to the Trenches is a photographic history of the role that Canadian soldiers and railroad men played in the construction of rail lines to the Allied front during World War I.\"-- Provided by publisher.
Book
The Extensive Usage of the Facial Image Threshing Machine for Facial Emotion Recognition Performance
Facial emotion recognition (FER) systems play a significant role in identifying driver emotions. Accurate facial emotion recognition of drivers in autonomous vehicles reduces road rage. However, training even the advanced FER model without proper datasets causes poor performance in real-time testing. FER system performance is heavily affected by the quality of datasets than the quality of the algorithms. To improve FER system performance for autonomous vehicles, we propose a facial image threshing (FIT) machine that uses advanced features of pre-trained facial recognition and training from the Xception algorithm. The FIT machine involved removing irrelevant facial images, collecting facial images, correcting misplacing face data, and merging original datasets on a massive scale, in addition to the data-augmentation technique. The final FER results of the proposed method improved the validation accuracy by 16.95% over the conventional approach with the FER 2013 dataset. The confusion matrix evaluation based on the unseen private dataset shows a 5% improvement over the original approach with the FER 2013 dataset to confirm the real-time testing.
Journal Article
Mater 2-10
Centred on three generations of a family of rail workers and a laid-off factory worker staging a high-altitude sit-in, MATER 2-10 vividly depicts the lives of ordinary working Koreans, starting from the Japanese colonial era, continuing through Liberation, and right up to the twenty-first century. It is at once a powerful account that captures a nation's longing for a rail line to reconnect North and South, a magical-realist novel that depicts the lives of modern industrial workers, and a culmination of Hwang's career -- a masterpiece thirty years in the making. A true voice of a generation, Hwang shows again why he is unmatched when it comes to depicting the grief of a divided nation and bringing to life the cultural identity and trials and tribulations of the Korean people.
Book
A Review on Automatic Facial Expression Recognition Systems Assisted by Multimodal Sensor Data
Facial Expression Recognition (FER) can be widely applied to various research areas, such as mental diseases diagnosis and human social/physiological interaction detection. With the emerging advanced technologies in hardware and sensors, FER systems have been developed to support real-world application scenes, instead of laboratory environments. Although the laboratory-controlled FER systems achieve very high accuracy, around 97%, the technical transferring from the laboratory to real-world applications faces a great barrier of very low accuracy, approximately 50%. In this survey, we comprehensively discuss three significant challenges in the unconstrained real-world environments, such as illumination variation, head pose, and subject-dependence, which may not be resolved by only analysing images/videos in the FER system. We focus on those sensors that may provide extra information and help the FER systems to detect emotion in both static images and video sequences. We introduce three categories of sensors that may help improve the accuracy and reliability of an expression recognition system by tackling the challenges mentioned above in pure image/video processing. The first group is detailed-face sensors, which detect a small dynamic change of a face component, such as eye-trackers, which may help differentiate the background noise and the feature of faces. The second is non-visual sensors, such as audio, depth, and EEG sensors, which provide extra information in addition to visual dimension and improve the recognition reliability for example in illumination variation and position shift situation. The last is target-focused sensors, such as infrared thermal sensors, which can facilitate the FER systems to filter useless visual contents and may help resist illumination variation. Also, we discuss the methods of fusing different inputs obtained from multimodal sensors in an emotion system. We comparatively review the most prominent multimodal emotional expression recognition approaches and point out their advantages and limitations. We briefly introduce the benchmark data sets related to FER systems for each category of sensors and extend our survey to the open challenges and issues. Meanwhile, we design a framework of an expression recognition system, which uses multimodal sensor data (provided by the three categories of sensors) to provide complete information about emotions to assist the pure face image/video analysis. We theoretically analyse the feasibility and achievability of our new expression recognition system, especially for the use in the wild environment, and point out the future directions to design an efficient, emotional expression recognition system.
Journal Article
The Paris express : a novel
Based on an 1895 disaster that went down in history when it was captured in a series of surreal, extraordinary photographs, The Paris Express is a propulsive novel set on a train packed with a fascinating cast of characters who hail from as close as Brittany and as far as Russia, Ireland, Algeria, Pennsylvania, and Cambodia. Members of parliament hurry back to Paris to vote; a medical student suspects a girl may be dying; a secretary tries to convince her boss of the potential of moving pictures; two of the train's crew build a life away from their wives; a young anarchist makes a terrifying plan, and much more.
BOOK
eXnet: An Efficient Approach for Emotion Recognition in the Wild
Facial expression recognition has been well studied for its great importance in the areas of human–computer interaction and social sciences. With the evolution of deep learning, there have been significant advances in this area that also surpass human-level accuracy. Although these methods have achieved good accuracy, they are still suffering from two constraints (high computational power and memory), which are incredibly critical for small hardware-constrained devices. To alleviate this issue, we propose a new Convolutional Neural Network (CNN) architecture eXnet (Expression Net) based on parallel feature extraction which surpasses current methods in accuracy and contains a much smaller number of parameters (eXnet: 4.57 million, VGG19: 14.72 million), making it more efficient and lightweight for real-time systems. Several modern data augmentation techniques are applied for generalization of eXnet; these techniques improve the accuracy of the network by overcoming the problem of overfitting while containing the same size. We provide an extensive evaluation of our network against key methods on Facial Expression Recognition 2013 (FER-2013), Extended Cohn-Kanade Dataset (CK+), and Real-world Affective Faces Database (RAF-DB) benchmark datasets. We also perform ablation evaluation to show the importance of different components of our architecture. To evaluate the efficiency of eXnet on embedded systems, we deploy it on Raspberry Pi 4B. All these evaluations show the superiority of eXnet for emotion recognition in the wild in terms of accuracy, the number of parameters, and size on disk.
Journal Article
Canadian railroad trilogy
Portrays the building of the Canadian Pacific Railway in a series of dreamlike paintings accompanied by the lyrics of Lightfoot's 1967 song commemorating Canada's centennial year.
Book
Efficient synthesis of some 1,3-oxazine derivatives in the presence of solid acid nano catalyst based on ferrierite and study on their activity against breast cancer through molecular docking calculation
In this research, the magnetic solid acid nanocatalyst based on ferrierite has been prepared and used as catalyst for the green synthesis of some [1,3]-oxazine derivatives in water at room temperature. The synthesized compounds were obtained in high to excellent yields after short reaction times and the structure of synthesized products were investigated by spectroscopic methods such as: FT-IR,
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H NMR and
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C NMR. The prepared magnetic solid acid catalyst was characterized using XRD, FT-IR, FE-SEM, EDX, elemental mapping, TGA and VSM analysis methods. Magnetic catalyst has easy separation ability, which leads to better and easier recycling. The preparation and synthesis of [1,3]-oxazine derivatives were carried out at room temperature in the presence of M-FER/TEPA/SO
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H. Easy workup, green solvent (water) and also short reaction times with high to excellent yield of products, are some of advantageous of presented method. Docking calculations on the structure of the synthesized compounds proved their medicinal properties against breast cancer cells.
Journal Article