Results 41 to 50 of about 21,150,821 (215)
On the continued Erlang loss function [PDF]
, 1986 We prove two fundamental results in teletraffic theory. The first is the frequently conjectured convexity of the analytic continuation B(x, a) of the classical Erlang loss function as a function of x, x 0. The second is the uniqueness of the solution of
Doorn, Erik A. van, Jagers, A.A.
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Generalization of Cross-Entropy Loss Function for Image Classification
Mohyla Mathematical Journal, 2021 Classification task is one of the most common tasks in machine learning. This supervised learning problem consists in assigning each input to one of a finite number of discrete categories.
V. Andreieva, N. Shvai
semanticscholar +1 more source
Tomato Leaf Disease Identification Method Based on Improved YOLOX
Agronomy, 2023 In tomato leaf disease identification tasks, the high cost and consumption of deep learning-based recognition methods affect their deployment and application on embedded devices.
Wenbo Liu, Yongsen Zhai, Yu Xia
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Are Analysts' Loss Functions Asymmetric? [PDF]
Journal of Forecasting, 2006 ABSTRACTDespite displaying a statistically significant optimism bias, analysts' earnings forecasts are an important input to investors’ valuation models. Understanding the possible reasons for any bias is important if information is to be extracted from earnings forecasts and used optimally by investors. Extant research into the shape of analysts' loss
Clatworthy, Mark A. +2 more
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Application of Weighted Cross-Entropy Loss Function in Intrusion Detection
Journal of Computer and Communications, 2021 The deep learning model is overfitted and the accuracy of the test set is reduced when the deep learning model is trained in the network intrusion detection parameters, due to the traditional loss function convergence problem.
Ziyun Zhou, Hong Huang, Binhao Fang
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Deep Learning Techniques for Vehicle Detection and Classification from Images/Videos: A Survey
Sensors, 2023 Detecting and classifying vehicles as objects from images and videos is challenging in appearance-based representation, yet plays a significant role in the substantial real-time applications of Intelligent Transportation Systems (ITSs).
Michael Abebe Berwo +7 more
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Indium selenide: An insight into electronic band structure and surface excitations [PDF]
, 2017 We have investigated the electronic response of single crystals of indium selenide by means of angle-resolved photoemission spectroscopy, electron energy loss spectroscopy and density functional theory.
Agnoli, Stefano +12 more
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Retail commodity detection method based on location learnable visual center mechanism
物联网学报, 2023 To address the problem of low detection accuracy caused by the difficulty in effectively capturing significant and diversified feature information for packaging deformation and overlap products, a location learnable visual center (LLVC) mechanism was ...
Xiaohua LYU, Mingchen WEI, Libo LIU
doaj
, 2018 We describe a new framework for fitting jump models to a sequence of data. The key idea is to alternate between minimizing a loss function to fit multiple model parameters, and minimizing a discrete loss function to determine which set of model ...
Bemporad, A. +3 more
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Loss Functions for Loss Estimation
The Annals of Statistics, 1988 Let X be a random variable with distribution \(P_{\theta}\), where \(\theta\in \Theta\), and d(X) a decision for \(\theta\) with loss W(\(\theta\),d(X)). A class of loss functions combining the decision error W(\(\theta\),d(X)) and the error in estimating W(\(\theta\),d(X)) by h(X) is introduced. Under these loss functions the Bayes procedure \((d_ B(X)
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