Early Action Prediction by Soft Regression

Real-Time RGB-D Activity Prediction by Soft Regression

Fig. 4: Soft labels learned for the activities in the SYSU 3DHOI set. Fig. 5: More evaluations on the SYSU 3DHOI set. . Table 1: RGB vs. RGB-D Prediction on the SYSU 3DHOI set. Our LAFF feature is constructed from the frame-level feature(HOG and relative locations), with temporal structure considered. Accumulative Feature computation with temporal interval : LAFF construction: For a sequence of...

Software reliability prediction by soft computing techniques

In this paper, ensemble models are developed to accurately forecast software reliability. Various statistical (multiple linear regression and multivariate adaptive regression splines) and intelligent techniques (backpropagation trained neural network, dynamic evolving neuro–fuzzy inference system and TreeNet) constitute the ensembles presented. Three linear ensembles and one non-linear ensemble...

Path Loss Prediction by Robust Regression Methods

Prediction of Antibiotics Residues in Raw Milk by Using Binary Logistic Regression Model

medical compounds, especially antibiotics, in which remains in milk and dairy products on the one hand causes health problems such as allergic reactions and Development of bacterial resistance to antibiotics are a serious threat to the health of consumers , and on the other hand, industrial troubles such as failure to produce fermented products can cause the milk back to the rancher. The purpos...

A Comparative Study of the Prediction Stock Crash Risk by using Meta- Heuristic & Regression

One of the most important methods of opacity accounting information by management is to accelerate the identification of good news versus delaying the identification of bad news on profits, but there is always a final level of accumulation of bad news in the company, and by reaching that its final level, these bad news will be released, which will lead to a Stock Price Crash Risk. In fact, stoc...