How does it work? Instead of learning about a topic in class, students use digital information and occasionalmicrolearning techniques, for example, watching short videos on a specific topic at home. The content of this homework is then explored and discussed in more detail in the classroom. In...
The potential of deep learning-based techniques to address imaging bottlenecks in the field of low-field MRI was demonstrated by Koonjoo et al.42 They use an end-to-end deep convolutional neural network approach to boost SNR in low-field MR images acquired from highly noise-corrupted data. We...
This literature review attempts to compile and compare the most recent advancements in Machine Learning-based techniques for the detection and classification of bots on five primary social media platforms namely Facebook, Instagram, LinkedIn, Twitter, and Weibo. We bring forth a concise overview of a...
In this paper, we introduce a solution called Lightning Cat which is based on deep learning techniques. We train three deep learning models for detecting vulnerabilities in smart contract: Optimized-CodeBERT, Optimized-LSTM, and Optimized-CNN. Experimental results show that, in the Lightning Cat we...
Q-Learning: This technique belongs to value-based reinforcement learning techniques that combine the Monte Carlo method and the TD method. Its ultimate goal is to learn a table (Q-Table). Works including [25], [55] adopt this technique. To integrate it into the FogBus2 framework, we imple...
Corner point detection for the reading region is achieved by reconstructing the detection head and incorporating the corner detection loss function, its localization accuracy is further improved by embedding attention mechanism modules, dynamic loss functions, and offline enhancement techniques. Geometric ...
Tips and Techniques for Incorporating Team-Based Learning (TBL) Methods into a College ClassroomTeam-based learningcritical thinkinggroup dynamicsstudent engagementlearning satisfactionTeam-based learning (TBL) methods provide instructors with an avenue to create student engagement and enhance learning ...
To obtain a high performance of person identification and authentication, deep-learning techniques are presented to learn and model the gait biometrics from the walking data. Specifically, a hybrid deep neural network is proposed for robust gait feature representation, where features in the space ...
For learning-based fusion, several supervised, unsupervised, reinforcement learning, and deep learning techniques are illustrated in multi-sensor integrated positioning/navigation systems. Design consideration of these integrated systems is discussed in detail from several aspects and their application scenarios...
Deep learning techniques Convolutional neural network for classification We implemented a set of CNNs to perform the classification task for each cell image. These CNNs were constructed with the “Xception” module, which is an upgraded version of the “Google Inception” module. The difference betw...