Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can precisely recognize the human central issues, really work on the exactness of human posture assessment, and can adjust to the intricate scenes with thick individuals and impediment. Finally, the difficulties and possible future trends are described, and the development of the field is presented.
Contemporary art has been widely affected by technology, and ceramics production is no exception. As an ancient art that originates from clay and other humble materials found in the ground, ceramics is considered one of the most adaptable art forms. Once it is realised how flexible ceramics as a material is, it can be easily altered into endless forms and shapes. Therefore, it is vital for ceramics practitioners to find a relationship between this wonderful material and the media of contemporary art, culture and modelling software or technology in general so that they can take their deformable art pieces to a whole new level. Such a relationship is worth investigating. Thus, for the purposes of this research, several ceramic pieces were
... Show MoreThe aim of the research is to identify to what extent to which Malcolm Baldrige standards of total quality are applied in the after-sales services of a private sector company for electrical appliances, from the point of view of administrative leaders, in it. To achieve this aim a questionnaire has been used to measure the degree of application of Malcolm’s seven criteria for total quality, namely: (leadership, strategic planning, focus on the customer, measurement and analysis and knowledge management, focus in human resource and operation management and results of the company’s management), the research found that the company achieved a good level of the standard from the de
... Show Moreاستخدام سلاسل ماركوف في التعرف على تعقبات الحامض النووي DNA
A simple UV spectrophotometric differential derivatization method was performed for the simultaneous quantification of three aromatic amino acids of tryptophan, the polar tyrosine and phenylalanine TRP, TYR and PHE respectively. The avoidance of the time and reagents consuming steps of sample preparation or analyze separation from its bulk of interferences made the approach environmentally benign, sustainable and green. The linear calibration curves of differential second derivative were built at the optimum wavelength for each analyze (218.9, 236.1 and 222.5 nm) for PHE, TRP and TYR respectively. Quantification for each analyze was in the concentration range of (1.0– 45, 0.1–20.0 and 1.0– 50.0 μg/ml) at replicates of (n=3) with a re
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no
... Show MoreDeep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing
... Show MoreDeep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreRecommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o
... Show MoreUltraviolet spectrophotometric studies for antibiotic (amino glycoside) derivatives including, Neomycin, Streptomycin, Gentamycin and Kanamycin with special reagents, which are benzoyl chloride; benzene sulfonyl chloride, toluenesulfonyl chloride and phthalic anhydride were made. Amino glycosides derivatives were followed through measurements of the ultraviolet absorbance (A) from which the absorptivity (ε) of the complexes was deduced and molar absorbances using Ultraviolet for products and calculate the number of reagents molecule that combine to amino glycosides.