Adaptive Multimodal Fusion For Facial Action Units Recognition

Multimodal facial action units (AU) recognition aims to build models that are capable of processing, correlating, and integrating information from multiple modalities (i.e., 2D images from a visual sensor, 3D geometry from 3D imaging, and thermal images from an infrared sensor). Although the multimodal data can provide rich information, there are two challenges that have to be addressed when learning from multimodal data: 1) the model must capture the complex cross-modal interactions in order to utilize the additional and mutual information effectively; 2) the model must be robust enough in the circumstance of unexpected data corruptions during testing, in case of a certain modality missing or being noisy. In this paper, we propose a novel Adaptive Multimodal Fusion method (AMF) for AU detection, which learns to select the most relevant feature representations from different modalities by a re-sampling procedure conditioned on a feature scoring module. The feature scoring module is designed to allow for evaluating the quality of features learned from multiple modalities. As a result, AMF is able to adaptively select more discriminative features, thus increasing the robustness to missing or corrupted modalities. In addition, to alleviate the over-fitting problem and make the model generalize better on the testing data, a cut-switch multimodal data augmentation method is designed, by which a random block is cut and switched across multiple modalities. We have conducted a thorough investigation on two public multimodal AU datasets, BP4D and BP4D+, and the results demonstrate the effectiveness of the proposed method. Ablation studies on various circumstances also show that our method remains robust to missing or noisy modalities during tests

A systematic review and meta-analysis of clinical trials on saffron (Crocus sativus) effectiveness and safety on erectile dysfunction and semen parameters

Objective: We performed this systematic review and meta-analysis study to determine saffron (Crocus sativus) effectiveness and safety in male infertility problems. Materials and Methods: The databases PubMed, Scopus, Cochrane, Google Scholar, SID, IranMedex and Magiran until July 2016 and reference section of relevant articles, were searched to find both English and Persian clinical trials on male infertility issues that used saffron as medical treatment. Also, the quality of these trials was evaluated by Oxford Center for Evidence Based Medicine checklist. A total of six trials was ultimately included. All statistical analyses were done by Comprehensive Meta-analysis (CMA) Version 2. Results: Only in one study conducted on sperm parameters, the mean percentage of sperm with normal morphology (