Visualization Method Corresponding to Regression Problems and Its Application to Deep Learning-Based Gaze Estimation Model

2020 ◽  
Vol 24 (5) ◽  
pp. 676-684
Author(s):  
Daigo Kanda ◽  
◽  
Shin Kawai ◽  
Hajime Nobuhara
Keyword(s):  
Deep Learning ◽  
Personal Information ◽  
Smart Devices ◽  
Gaze Estimation ◽  
Visualization Method ◽  
Massachusetts Institute Of Technology ◽  
Estimation Model ◽  
Regression Problem ◽  
The Gaze ◽  
Institute Of Technology

The human gaze contains substantial personal information and can be extensively employed in several applications if its relevant factors can be accurately measured. Further, several fields could be substantially innovated if the gaze could be analyzed using popular and familiar smart devices. Deep learning-based methods are robust, making them crucial for gaze estimation on smart devices. However, because internal functions in deep learning are black boxes, deep learning systems often make estimations for unclear reasons. In this paper, we propose a visualization method corresponding to a regression problem to solve the black box problem of the deep learning-based gaze estimation model. The proposed visualization method can clarify which region of an image contributes to deep learning-based gaze estimation. We visualized the gaze estimation model proposed by a research group at the Massachusetts Institute of Technology. The accuracy of the estimation was low, even when the facial features important for gaze estimation were recognized correctly. The effectiveness of the proposed method was further determined through quantitative evaluation using the area over the MoRF perturbation curve (AOPC).

scholarly journals A New Gaze Estimation Method Based on Homography Transformation Derived from Geometric Relationship

2020 ◽  
Vol 10 (24) ◽  
pp. 9079
Author(s):  
Kaiqing Luo ◽  
Xuan Jia ◽  
Hua Xiao ◽  
Dongmei Liu ◽  
Li Peng ◽  
...  
Keyword(s):  
Estimation Method ◽  
Gaze Estimation ◽  
Estimation Model ◽  
Experimental Accuracy ◽  
Unknown Parameters ◽  
The Gaze ◽  
Marquardt Algorithm ◽  
Mapping Equation ◽  
Estimation System ◽  
Homography Transformation

In recent years, the gaze estimation system, as a new type of human-computer interaction technology, has received extensive attention. The gaze estimation model is one of the main research contents of the system. The quality of the model will directly affect the accuracy of the entire gaze estimation system. To achieve higher accuracy even with simple devices, this paper proposes an improved mapping equation model based on homography transformation. In the process of experiment, the model mainly uses the “Zhang Zhengyou calibration method” to obtain the internal and external parameters of the camera to correct the distortion of the camera, and uses the LM(Levenberg-Marquardt) algorithm to solve the unknown parameters contained in the mapping equation. After all the parameters of the equation are determined, the gaze point is calculated. Different comparative experiments are designed to verify the experimental accuracy and fitting effect of this mapping equation. The results show that the method can achieve high experimental accuracy, and the basic accuracy is kept within 0.6∘. The overall trend shows that the mapping method based on homography transformation has higher experimental accuracy, better fitting effect and stronger stability.

scholarly journals A Deep Learning Approach for Automatic Seizure Detection in Children With Epilepsy

2021 ◽  
Vol 15 ◽  
Author(s):  
Ahmed Abdelhameed ◽  
Magdy Bayoumi
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Seizure Detection ◽  
Detection Methods ◽  
Segment Length ◽  
Brain State ◽  
Learning Approach ◽  
Massachusetts Institute Of Technology ◽  
New Approach ◽  
Institute Of Technology

Over the last few decades, electroencephalogram (EEG) has become one of the most vital tools used by physicians to diagnose several neurological disorders of the human brain and, in particular, to detect seizures. Because of its peculiar nature, the consequent impact of epileptic seizures on the quality of life of patients made the precise diagnosis of epilepsy extremely essential. Therefore, this article proposes a novel deep-learning approach for detecting seizures in pediatric patients based on the classification of raw multichannel EEG signal recordings that are minimally pre-processed. The new approach takes advantage of the automatic feature learning capabilities of a two-dimensional deep convolution autoencoder (2D-DCAE) linked to a neural network-based classifier to form a unified system that is trained in a supervised way to achieve the best classification accuracy between the ictal and interictal brain state signals. For testing and evaluating our approach, two models were designed and assessed using three different EEG data segment lengths and a 10-fold cross-validation scheme. Based on five evaluation metrics, the best performing model was a supervised deep convolutional autoencoder (SDCAE) model that uses a bidirectional long short-term memory (Bi-LSTM) – based classifier, and EEG segment length of 4 s. Using the public dataset collected from the Children’s Hospital Boston (CHB) and the Massachusetts Institute of Technology (MIT), this model has obtained 98.79 ± 0.53% accuracy, 98.72 ± 0.77% sensitivity, 98.86 ± 0.53% specificity, 98.86 ± 0.53% precision, and an F1-score of 98.79 ± 0.53%, respectively. Based on these results, our new approach was able to present one of the most effective seizure detection methods compared to other existing state-of-the-art methods applied to the same dataset.

scholarly journals Modeling of moral decisions with deep learning

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Christopher Wiedeman ◽  
Ge Wang ◽  
Uwe Kruger
Keyword(s):  
Deep Learning ◽  
Deep Neural Networks ◽  
Autonomous Vehicle ◽  
Massachusetts Institute Of Technology ◽  
Test Results ◽  
Moral Decision Making ◽  
Machine Experiment ◽  
Moral Decisions ◽  
Human Ethics ◽  
Institute Of Technology

AbstractOne example of an artificial intelligence ethical dilemma is the autonomous vehicle situation presented by Massachusetts Institute of Technology researchers in the Moral Machine Experiment. To solve such dilemmas, the MIT researchers used a classic statistical method known as the hierarchical Bayesian (HB) model. This paper builds upon previous work for modeling moral decision making, applies a deep learning method to learn human ethics in this context, and compares it to the HB approach. These methods were tested to predict moral decisions of simulated populations of Moral Machine participants. Overall, test results indicate that deep neural networks can be effective in learning the group morality of a population through observation, and outperform the Bayesian model in the cases of model mismatches.

scholarly journals A Lightweight Deep Learning Model for Fast Electrocardiographic Beats Classification With a Wearable Cardiac Monitor: Development and Validation Study

10.2196/17037 ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. e17037 ◽  
Author(s):  
Eunjoo Jeon ◽  
Kyusam Oh ◽  
Soonhwan Kwon ◽  
HyeongGwan Son ◽  
Yongkeun Yun ◽  
...  
Keyword(s):  
Deep Learning ◽  
Graphics Processing Units ◽  
Model Complexity ◽  
Massachusetts Institute Of Technology ◽  
Baseline Model ◽  
Accurate Analysis ◽  
Central Processing ◽  
Beat Classification ◽  
Institute Of Technology ◽  
Graphics Processing

Background Electrocardiographic (ECG) monitors have been widely used for diagnosing cardiac arrhythmias for decades. However, accurate analysis of ECG signals is difficult and time-consuming work because large amounts of beats need to be inspected. In order to enhance ECG beat classification, machine learning and deep learning methods have been studied. However, existing studies have limitations in model rigidity, model complexity, and inference speed. Objective To classify ECG beats effectively and efficiently, we propose a baseline model with recurrent neural networks (RNNs). Furthermore, we also propose a lightweight model with fused RNN for speeding up the prediction time on central processing units (CPUs). Methods We used 48 ECGs from the MIT-BIH (Massachusetts Institute of Technology-Beth Israel Hospital) Arrhythmia Database, and 76 ECGs were collected with S-Patch devices developed by Samsung SDS. We developed both baseline and lightweight models on the MXNet framework. We trained both models on graphics processing units and measured both models’ inference times on CPUs. Results Our models achieved overall beat classification accuracies of 99.72% for the baseline model with RNN and 99.80% for the lightweight model with fused RNN. Moreover, our lightweight model reduced the inference time on CPUs without any loss of accuracy. The inference time for the lightweight model for 24-hour ECGs was 3 minutes, which is 5 times faster than the baseline model. Conclusions Both our baseline and lightweight models achieved cardiologist-level accuracies. Furthermore, our lightweight model is competitive on CPU-based wearable hardware.

Applying the Anderson-Darling Test to Suicide Clusters

Crisis ◽  
2013 ◽  
Vol 34 (6) ◽  
pp. 434-437 ◽  
Author(s):  
Donald W. MacKenzie
Keyword(s):  
Poisson Process ◽  
Goodness Of Fit ◽  
Small Samples ◽  
Massachusetts Institute Of Technology ◽  
Homogeneous Poisson Process ◽  
Cornell University ◽  
The Difference ◽  
Suicide Clusters ◽  
Institute Of Technology ◽  
Anderson Darling

Background: Suicide clusters at Cornell University and the Massachusetts Institute of Technology (MIT) prompted popular and expert speculation of suicide contagion. However, some clustering is to be expected in any random process. Aim: This work tested whether suicide clusters at these two universities differed significantly from those expected under a homogeneous Poisson process, in which suicides occur randomly and independently of one another. Method: Suicide dates were collected for MIT and Cornell for 1990–2012. The Anderson-Darling statistic was used to test the goodness-of-fit of the intervals between suicides to distribution expected under the Poisson process. Results: Suicides at MIT were consistent with the homogeneous Poisson process, while those at Cornell showed clustering inconsistent with such a process (p = .05). Conclusions: The Anderson-Darling test provides a statistically powerful means to identify suicide clustering in small samples. Practitioners can use this method to test for clustering in relevant communities. The difference in clustering behavior between the two institutions suggests that more institutions should be studied to determine the prevalence of suicide clustering in universities and its causes.

Editorial: Advancing the Debate on Architecture, Planning, and Built Environment Research

2015 ◽  
Vol 9 (2) ◽  
Author(s):  
Ashraf M. Salama
Keyword(s):  
Learning Styles ◽  
Cultural Values ◽  
Urban Studies ◽  
Wide Spectrum ◽  
Journal Ranking ◽  
Massachusetts Institute Of Technology ◽  
Open Access Journals ◽  
Practice Based Research ◽  
Institute Of Technology ◽  
Number Of Citations

With an acceptance rate that does not exceed 25% of the total papers and articles submitted to the journal, IJAR – International Journal of Architectural Research is moving forward to position itself among the leading journals in architecture and urban studies worldwide. As this is the case since the beginning of volume 5, issue 1, March 2011, one must note that the journal has been covered by several data and index bases since its inception including Avery Index to Architectural Periodicals, EBSCO-Current Abstracts-Art and Architecture, INTUTE, Directory of Open Access Journals, Pro-Quest, Scopus-Elsevier and many university library databases across the globe. This is coupled with IJAR being an integral part of the archives and a featured collection of ArchNet and the Aga Khan Documentation Centre at MIT: Massachusetts Institute of Technology, Cambridge, MA.In 2014, IJAR was included in Quartile 2 / Q2 list of Journals both in ‘Architecture’ and ‘Urban Studies.’ As of May 2015, IJAR is ranked 23 out of 83 journals in ‘Architecture’ and 59 out of 119 in ‘Urban Studies.’ Rankings are based on the SJR (SCImago Journal Ranking); an Elsevier- SCOPUS indicator that measures the scientific influence of the average article in a journal. SJR is a measure of scientific influence of scholarly journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from. See here for more information (http://www.scimagojr.com/index.php) and (http://www.journalmetrics.com/sjr.php). While the journal is now on top of many of the distinguished journals in Elsevier- SCOPUS database, we will keep aspiring to sustain our position and move forward to Q1 group list and eventually in the top 10 journal list in the field. However, this requires sustained efforts and conscious endeavours that give attention to quality submissions through a rigorous review process. This edition of IJAR: volume 9, issue 2, July 2015 includes debates on a wide spectrum of issues, explorations and investigations in various settings. The issue encompasses sixteen papers addressing cities, settlements, and projects in Europe, South East Asia, and the Middle East. Papers involve international collaborations evidenced by joint contributions and come from scholars in universities, academic institutions, and practices in Belgium; Egypt; Greece; Italy; Jordan; Malaysia; Palestine; Qatar; Saudi Arabia; Serbia; Spain; Turkey; and the United Kingdom. In this editorial I briefly outline the key issues presented in these papers, which include topics relevant to social housing, multigenerational dwelling, practice-based research, sustainable design and biomimetic models, learning environments and learning styles, realism and the post modern condition, development and planning, urban identity, contemporary landscapes, and cultural values and traditions.

XX Rudi Dombusch, Keys to Prosperity. Free Markets, Sound Money, and bit of Luck The MIT Press 2000 Londres

2009 ◽  
Vol 33 (130) ◽  
Author(s):  
GERARDO REYES GUZMÁN
Keyword(s):  
Massachusetts Institute ◽  
Massachusetts Institute Of Technology ◽  
Free Markets ◽  
Institute Of Technology

Rudiger Dornbusch, destacado economista del Massachusetts Institute of Technology (MIT), analiza en esta trascendental obra tópicos como inflación, deuda, tipos de cambio, política externa y mercados emergentes. El marco conceptual descansa en la corriente de la escuela de Chicago, la cual parte del principio de que el mercado es el mecanismo que garantiza la creación del progreso en contraste con el Estado, que en su afán por encontrar soluciones perfectas, fracasa regularmente en sus cometidos.

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