Showing 1-25 of 8,659 resultsfor "Index Terms":Teacher Network
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South African teachers are under pressure due to rising expectations of their content knowledge and digital skills without guaranteed infrastructural or institutional support in using ICTs. The purpose of this study is to find out to what extent ICTs are being used by teachers in rural South African schools and also what support systems, if any, these teachers have. The theoretical lens is that of...Show More
Unsupervised adaptation of student DNNS learned from teacher RNNS for improved ASR performance
2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)
Year: 2017 | Conference Paper |
Cited by: Papers (1)
In automatic speech recognition (ASR), adaptation techniques are used to minimize the mismatch between training and testing conditions. Many successful techniques have been proposed for deep neural network (DNN) acoustic model (AM) adaptation. Recently, recurrent neural networks (RNNs) have outperformed DNNs in ASR tasks. However, the adaptation of RNN AMs is challenging and in some cases when com...Show More
Construction and Empirical Study of Regional Teacher Research and Training Mechanism Based on Network Teaching and Research Platform
2023 3rd International Conference on Educational Technology (ICET)
Year: 2023 | Conference Paper |
With the emergence of intelligent teaching environment, network research and study will become the main position of teachers' research and study. This paper first depends on the Education of Guangdong Province Resources Public Service Platform construction of network teaching environment, from the perspective of subject study in the education information-based teaching practice of community projec...Show More
Evaluation of Rural Teachers’ Informatization Ability Based on Neural Network
2022 6th Asian Conference on Artificial Intelligence Technology (ACAIT)
Year: 2022 | Conference Paper |
Aiming at the objective demand of rural teachers’ informatization ability evaluation, a rural teachers’ informatization ability evaluation model based on BP neural network is proposed. Among them, the design ability and software index are taken as the input of BP neural network, and the evaluation results of rural informatization ability are output through the training of BP neural network. The re...Show More
Designing Determining Teacher Engagement Based on The Indonesian Teacher Engagement Index Using Artificial Neural Network
Sasmoko;Jurike Moniaga;Yasinta Indrianti;Yogi Udjaja;Christina Natasha
2019 International Conference on Information and Communications Technology (ICOIACT)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
This research proposes the use of a classifier built using the artificial neural network (ANN) technique for determining teacher engagement based on the Indonesian Teacher Engagement Index (ITEI). ANN classifier will be built in the form of a website. This study uses the concept of artificial intelligence and Artificial neural networks. This research produces Website Workflow and The Classifier Pr...Show More
Teacher-student Network As An Attention Module With Memory for Defect Localization
2022 China Automation Congress (CAC)
Year: 2022 | Conference Paper |
The goal of defect detection is to detect and locate defects on product surface. Since the complexity of defect types in actual industrial production and it is difficult to obtain a large number of samples for supervised training. Current defect detection methods are thought to be mainly unsupervised training methods. However, the current unsupervised methods all learn the normal sample feature re...Show More
Optimized Computation Combining Classification and Detection Networks with Distillation
2021 International Joint Conference on Neural Networks (IJCNN)
Year: 2021 | Conference Paper |
A Convolutional neural network (CNN) has emerged as a widely used approach to computer vision tasks, including object classification and detection tasks. The high requirement for the model to be more computationally efficient on lower information and communication technology (ICT) resource, e.g., mobile terminals can benefit from model distillation. However, most existing distillation methods suff...Show More
A Neural Network based Approach for Predicting Indonesian Teacher Engagement Index (ITEI)
Sucianna Ghadati Rabiha;Emny Harna Yossy;Yasinta Indrianti;Samoko
2019 International Conference of Artificial Intelligence and Information Technology (ICAIIT)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
The Indonesian Teacher Engagement Index (ITEI) is an instrument designed to help teachers detect themselves through self-diagnostics. In this study we use the Neural Network approach to predict Index values and assess parameters in the Neural Network. The analysis of this study is based on several variables including the input layer of the proposed ANN model as many as 28 parameters obtained from ...Show More
Improved Neural Network Compression using Generative Adversarial Networks
2024 Horizons of Information Technology and Engineering (HITE)
Year: 2024 | Conference Paper |
Deep neural networks are typically computationally expensive, thus, there is a strong motivation to develop less intensive models while maintaining performance. Distilling knowledge from a teacher network to a lightweight student network is a critical application of neural network compression where the student network can learn meaningful feature space and perform comparably to the teacher network...Show More
Design of a Distributed Fusion Network Based on Knowledge Distillation
2024 7th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)
Year: 2024 | Conference Paper |
Given the outstanding performance of knowledge distillation networks in optimizing traditional deep neural networks, this paper proposes a distributed fusion network based on knowledge distillation. It leverages knowledge distillation techniques to partition the different branches of the distributed fusion network into teacher and student networks. Specifically, the branch modules responsible for ...Show More
Distilled Neural Network for Clothes Type Identification
Teerapon Chongpiphattanasiri;Pramod Wickramatilake;Jednipat Moonrinta;Mongkol Ekpanyapong;Matthew N. Dailey
Diverse applications such as criminal forensics and retail customer market segmentation would benefit from the ability to track individuals across multiple cameras. Clothing information is one of the keys to this capability when other identifying information such as the face cannot be reliably extracted. To quickly search for a criminal suspect or re-identify individuals across time and space, fil...Show More
Anomaly Detection based on Teacher-Student Network in the field of Security Document Production
2022 International Conference on Artificial Intelligence, Information Processing and Cloud Computing (AIIPCC)
Year: 2022 | Conference Paper |
Our paper proposes an unsupervised learning framework for knowledge distillation based on teacher-student networks for anomaly detection and classification in secure document images. The teacher network uses Wide-ResNet-50 as the backbone network and is pre-trained on large datasets of secure document images and ImageNet. We use a multi-scale feature pyramid matching strategy, so that the student ...Show More
Physical Education Teaching Evaluation Model Based on Levy Flight Mother Optimization Algorithm
2024 International Conference on Data Science and Network Security (ICDSNS)
Year: 2024 | Conference Paper |
The effectiveness of Physical Education (PE) teaching based on Deep Learning (DL) aims to maximum college students by addressing current deficiencies in college teachers' teaching abilities. However, PE teachers often lack experience and struggle with handling the high computational load, which affects accuracy. This paper proposes using the Levy Flight Mother Optimization Algorithm (LFMOA) method...Show More
Visualization of Teacher Social Capital in a Computer-Supported Engineering Education Teacher Professional Development Program
2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)
Year: 2016 | Conference Paper |
This study uses social network analysis to analyze teacher social capital in a NSF-funded, DRK-12 cyber-enabled engineering education teacher professional development program. The social capital leveraged among the teachers can be visually represented by attributes such as schools, grades, cohorts, and subgroups. Each teacher's social capital is calculated to complement the analysis.Show More
The Application of BP Neural Network Algorithm in the Performance Evaluation of College Teachers
2023 Third International Conference on Digital Data Processing (DDP)
Year: 2023 | Conference Paper |
With the promotion of the strategy of rejuvenating the country through science and education, the national government and colleges and universities have continuously promoted the emphasis and investment in the work performance of scientific research personnel, and the performance evaluation of university teachers has gradually become a social development trend. This paper mainly analyzes each univ...Show More
Segmenting Neuronal Structure in 3D Optical Microscope Images via Knowledge Distillation with Teacher-Student Network
Heng Wang;Donghao Zhang;Yang Song;Siqi Liu;Yue Wang;Dagan Feng;Hanchuan Peng;Weidong Cai
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)
Year: 2019 | Conference Paper |
Cited by: Papers (23)
Three-dimensional (3D) volumetric neural image segmentation is crucial to reconstructing accurate neuron structures. However, due to the structural complexity of neurons and the diverse imaging qualities of the microscopes, it is challenging to achieve both accuracy and efficiency. In this paper, we propose a teacher-student learning framework for fast neuron segmentation. The segmentation inferen...Show More
Stochasticity and Skip Connection Improve Knowledge Transfer
2020 28th European Signal Processing Conference (EUSIPCO)
Year: 2021 | Conference Paper |
Cited by: Papers (6)
Deep neural networks have achieved state-of-the-art performance in various fields. However, DNNs need to be scaled down to fit real-word applications where memory and computation resources are limited. As a means to compress the network yet still maintain the performance of the network, knowledge distillation has brought a lot of attention. This technique is based on the idea to train a student ne...Show More
Transferring Information Between Neural Networks
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2018 | Conference Paper |
Cited by: Papers (2)
This paper investigates techniques to transfer information between deep neural networks. We demonstrate that a student network, which has access to information computed by a teacher network on the training data, learns faster, can be less deep and requires less labeled examples to achieve a given performance level. For that we force the student to mimic the teacher by adding a penalty term to the ...Show More
Lightweight Neural Networks From PCA & LDA Based Distilled Dense Neural Networks
Mohamed El Amine Seddik;Hassane Essafi;Abdallah Benzine;Mohamed Tamaazousti
2020 IEEE International Conference on Image Processing (ICIP)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
This paper presents two methods for building lightweight neural networks with similar accuracy than heavyweight ones with the advantage to be less greedy in memory and computing resources. So it can be implemented in edge and IoT devices. The presented distillation methods are respectively based on Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). The two methods basically...Show More
Ensemble2N et: Learning from Ensemble Teacher Networks via Knowledge Transfer
2021 IEEE Symposium Series on Computational Intelligence (SSCI)
Year: 2021 | Conference Paper |
In machine learning, deep neural networks (DNNs) are becoming mainstream because they can learn higher-level features and thus form deep representations. However, DNNs require a lot of memory and training time. Improving the efficiency and effectiveness of D NN training has been an increasingly important focus of research in recent years. In this paper, we propose a training method, Ensemble2Net, ...Show More
Design of Teacher Portrait System Based on Knowledge Graph
2024 IEEE 2nd International Conference on Image Processing and Computer Applications (ICIPCA)
Year: 2024 | Conference Paper |
This paper takes the junior high school education administration system, human resource management system, student system and official website as the research object. Then the knowledge graph is used to study the multi-attribute teacher image. The system has intuitive material integration function, powerful interactive creation function, rich variable, function and program control function. The pr...Show More
Highlight Every Step: Knowledge Distillation via Collaborative Teaching
IEEE Transactions on Cybernetics
Cited by: Papers (40)
High storage and computational costs obstruct deep neural networks to be deployed on resource-constrained devices. Knowledge distillation (KD) aims to train a compact student network by transferring knowledge from a larger pretrained teacher model. However, most existing methods on KD ignore the valuable information among the training process associated with training results. In this article, we p...Show More
Research on Teachers’ Behavior in the Class Recognition on Based on Text Classification Technology
2020 IEEE 10th International Conference on Electronics Information and Emergency Communication (ICEIEC)
Year: 2020 | Conference Paper |
Teachers’ behavior in the classroom is the key factor that affects the quality of teaching and students’ learning. In order to improve the accuracy of teachers’ behavior in the classroom recognition, this study uses multiple in-depth learning models to identify teachers’ behavior in the classroom. Before the experiment, the teacher’s behaviors are marked and classified. The teacher’s speech is div...Show More
Construction of a Web-Based Remote Training Platform for Rural Preschool Teachers in China
2023 International Conference on Educational Knowledge and Informatization (EKI)
Year: 2023 | Conference Paper |
In the face of the varying levels of professional competence among rural preschool teachers, this study aims to enhance their professional abilities by constructing a web-based remote training platform. Employing software engineering methods, the study designed and developed functional modules such as video on-demand, discussion forums, and resource downloads. A survey was conducted on 100 rural p...Show More
Lifelong Teacher-Student Network Learning
A unique cognitive capability of humans consists in their ability to acquire new knowledge and skills from a sequence of experiences. Meanwhile, artificial intelligence systems are good at learning only the last given task without being able to remember the databases learnt in the past. We propose a novel lifelong learning methodology by employing a Teacher-Student network framework. While the Stu...Show More
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