This is therefore a fine-tuned model for this particular dataset and problem. Figure 8b/d and Table 3 give the results of this model on all classes separately. To get an overall estimate of model performance, we have taken a weighted average of the F1-score per class with the number of...
But, with the use of powerful graphics processing units and ongoing advances in computer vision, it is now possible to efficiently and accurately detect and identify objects, including insects, from images. Applying state-of-the-art deep learning methods to the problem of species-level bee ...
Following long years of research and technological advancements in the field, the ANN has become the core methodology that drives almost every application of Artificial Intelligence (Shahin, 2016) with the help of backpropagation technique. Backpropagation is a gradient descent based optimization method...
On the other hand, based on the linear convergence property of the conjugate gradient method, a restart factor is introduced in this paper. For an inverse problem containing n unknown parameters, the algorithm restarts from the steepest descent method after every n + 1 iterations to identify ...
This definition of BA addresses the problem that different clocks (for example, based on different feature spaces or using different mathematical/machine learning methods) often do not agree with each other, sometimes producing vastly different BA estimates for the same individual. This might occur ...
Another problem with using raw data is that the IMUs provide this information with different scaling, so if you change from an IMU manufactured by one supplier to one manufactured by a different supplier, the calibration model changes because the parameters obtained from the classifier depend on ...
This paper proposed a variant based on the gray wolf optimization algorithm (GWO) with chaotic disturbance, candidate migration, and attacking mechanisms, naming it the enhanced gray wolf optimizer (EGWO), to solve the problem of premature convergence and local stagnation. The performance of the E...
bytes per second from even one-minute sniffing of network traffic is sufficient to predict the video with high accuracy. The accuracy is increased to 90% accuracy in the non-VPN, 66% accuracy in the VPN, and 77% in the mixed VPN and non-VPN traffic, for models with two-minute sniffing...
loop region can serve as a “gatekeeper” in the substrate channel. Leucovorin, Carboprost, Protirelin, Flavin Mononucleotide, and Lovastatin Acid all have Gibbs binding free energies with pS273R that were less than −20 Kcal/mol according to the MM/PBSA analyses. In contrast to pS273R ...
After preprocessing the data, they are needed to build a model with the potential to accurately predict further observations. If the built model completely fits the training data, it is probably not reliable after deployment in the real world. This problem is called overfit and needs to be ...