The performance efficiency is measured simply by providing each model with fixed number of input images and comparing correct number of outputs for each model. Finally, a comparison between different machine learning and deep learning-based models is made based upon the accuracy score for each model...
convolutional neural networks, hyperspectral transmittance image, internal mechanical damage detection, fruit quality detection, machine learning... Z Wang,M Hu,G Zhai - 《Sensors》 被引量: 3发表: 2018年 A dual-stage deep learning model based on a sparse autoencoder and layered deep classifier fo...
The main aim of this study is to have deeper analysis on the effect of region and orientation on the performance of Machine Learning and Deep Learning respectively using Malaysian Ringgit banknotes (RM 1, RM 5, RM 10, RM 20, RM 50 and RM 100). In this project, two experiments conducted...
As such, there are many different types of learning that you may encounter as a practitioner in the field of machine learning: from whole fields of study to specific techniques. In this post, you will discover a gentle introduction to the different types of learning that you may encounter in...
Neural networks (deep learning) are a stochastic machine learning algorithm. The random initial weights allow the model to try learning from a different starting point in the search space each algorithm run and allow the learning algorithm to “break symmetry” during learning. The random shuffle ...
Swift for TensorFlow Swift for TensorFlow is a next-generation platform for machine learning that incorporates differentiable programming. In this notebook a go over its basics and also how to create a simple NN and CNN. Platform GCN Ever asked yourself how to use convolution networks for non...
Serious research has been conducted on data-driven models to analyze the cumulative production performance of the SAGD process, and one of the most common machine learning methods utilized is the Artificial Neural Network (ANN). It is important to test other machine learning methods like Extreme ...
In this study, we use optical data from the Rapid Eye satellite and topographic factors to analyze the potential of machine learning methods, i.e., artificial neural network (ANN), support vector machines (SVM) and random forest (RF), and different deep-learning convolution neural networks (...
The results of these methods are sensitive to different factors, such as the quality of input data, choice of algorithm, sampling strategies, and data splitting ratios. In this study, five different Machine Learning (ML) algorithms are used for LSM for the Wayanad district in Kerala, India, ...
Deep_Learning看ch04的two_layer_net還有dataset。參考連結點此 Yurei's Demo Code Keras Demo Code fran's review_TwoLayerNN_demo. Feel free to contact me with any questions and further details. Week 17: Introduction to Inner Product Space and Hash Table Yurei&Fran (10/1) Inner Product ...