This paper surveys some of the most important recent works related to micro-expression analysis. It includes discussions on algorithms for spotting and recognizing micro-expressions, their performances, databases, and...
详细信息
A progressive neurodegenerative ailment called Parkinson's disease (PD) is marked by the death of dopamine-producing cells in the substantia nigra area of the brain. The exact etiology of PD remains elusive, but i...
详细信息
Medical Image Analysis (MIA) is integral to healthcare, demanding advanced computational techniques for precise diagnostics and treatment planning. The demand for accurate and interpretable models is imperative in the...
详细信息
Medical Image Analysis (MIA) is integral to healthcare, demanding advanced computational techniques for precise diagnostics and treatment planning. The demand for accurate and interpretable models is imperative in the ever-evolving healthcare landscape. This paper explores the potential of Self-Supervised Learning (SSL), transfer learning and domain adaptation methods in MIA. The study comprehensively reviews SSL-based computational techniques in the context of medical imaging, highlighting their merits and limitations. In an empirical investigation, this study examines the lack of interpretable and explainable component selection in existing SSL approaches for MIA. Unlike prior studies that randomly select SSL components based on their performance on natural images, this paper focuses on identifying components based on the quality of learned representations through various clustering evaluation metrics. Various SSL techniques and backbone combinations were rigorously assessed on diverse medical image datasets. The results of this experiment provided insights into the performance and behavior of SSL methods, paving the way for an explainable and interpretable component selection mechanism for artificial intelligence models in medical imaging. The empirical study reveals the superior performance of BYOL (Bootstrap Your Own Latent) with resnet as the backbone, as indicated by various clustering evaluation metrics such as Silhouette Coefficient (0.6), Davies-Bouldin Index (0.67), and Calinski-Harabasz Index (36.9). The study also emphasizes the benefits of transferring weights from a model trained on a similar dataset instead of a dataset from a different domain. Results indicate that the proposed mechanism expedited convergence, achieving 98.66% training accuracy and 92.48% testing accuracy in 23 epochs, requiring almost half the number of epochs for similar results with ImageNet weights. This research contributes to advancing the understanding of SSL in MIA, providin
In serverless computing, the service provider takes full responsibility for function management. However, serverless computing has many challenges regarding data security and function scheduling. To address these chal...
详细信息
Handwritten signature identification is the process of determining an individual’s true identity by analyzing their signature. This is an important task in various applications such as financial transactions, legal d...
详细信息
Deep neural networks excel at image identification and computer vision applications such as visual product search, facial recognition, medical image analysis, object detection, semantic segmentation,instance segmentat...
详细信息
Deep neural networks excel at image identification and computer vision applications such as visual product search, facial recognition, medical image analysis, object detection, semantic segmentation,instance segmentation, and many others. In image and video recognition applications, convolutional neural networks(CNNs) are widely employed. These networks provide better performance but at a higher cost of computation. With the advent of big data, the growing scale of datasets has made processing and model training a time-consuming operation, resulting in longer training times. Moreover, these large scale datasets contain redundant data points that have minimum impact on the final outcome of the model. To address these issues, an accelerated CNN system is proposed for speeding up training by eliminating the noncritical data points during training alongwith a model compression method. Furthermore, the identification of the critical input data is performed by aggregating the data points at two levels of granularity which are used for evaluating the impact on the model *** experiments are conducted using the proposed method on CIFAR-10 dataset on ResNet models giving a 40% reduction in number of FLOPs with a degradation of just 0.11% accuracy.
E-beam lithography is a powerful tool for generating nanostructures and fabricating nanodevices with fine features approaching a few nanometers in ***,alternative approaches to conventional spin coating and developmen...
详细信息
E-beam lithography is a powerful tool for generating nanostructures and fabricating nanodevices with fine features approaching a few nanometers in ***,alternative approaches to conventional spin coating and development processes are required to optimize the lithography procedure on irregular *** this review,we summarize the state of the art in nanofabrication on irregular substrates using e-beam *** overcome these challenges,unconventional methods have been *** instance,polymeric and nonpolymeric materials can be sprayed or evaporated to form uniform layers of electron-sensitive materials on irregular ***,chemical bonds can be applied to help form polymer brushes or self-assembled monolayers on these *** addition,thermal oxides can serve as resists,as the etching rate in solution changes after e-beam ***,e-beam lithography tools can be combined with cryostages,evaporation systems,and metal deposition chambers for sample development and lift-off while maintaining low *** nanopyramids can be fabricated on an AFM tip by utilizing ice as a positive ***,Ti/Au caps can be patterned around a carbon ***,3D nanostructures can be formed on irregular surfaces by exposing layers of anisole on organic ice surfaces with a focused *** advances in e-beam lithography on irregular substrates,including uniform film coating,instrumentation improvement,and new pattern transferring method development,substantially extend its capabilities in the fabrication and application of nanoscale structures.
End-to-end text spotting is a vital computer vision task that aims to integrate scene text detection and recognition into a unified *** methods heavily rely on region-of-interest(Rol)operations to extract local featur...
详细信息
End-to-end text spotting is a vital computer vision task that aims to integrate scene text detection and recognition into a unified *** methods heavily rely on region-of-interest(Rol)operations to extract local features and complex post-processing steps to produce final *** address these limitations,we propose TextFormer,a query-based end-to-end text spotter with a transformer ***,using query embedding per text instance,TextFormer builds upon an image encoder and a text decoder to learn a joint semantic understanding for multitask *** allows for mutual training and optimization of classification,segmentation and recognition branches,resulting in deeper feature sharing without sacrificing flexibility or ***,we design an adaptive global aggregation(AGG)module to transfer global features into sequential features for reading arbitrarilyshaped texts,which overcomes the suboptimization problem of Rol ***,potential corpus information is utilized from weak annotations to full labels through mixed supervision,further improving text detection and end-to-end text spotting *** experiments on various bilingual(i.e.,English and Chinese)benchmarks demonstrate the superiority of our *** on the TDA-ReCTS dataset,TextFormer surpasses the state-of-the-art method in terms of 1-NED by 13.2%.
Now a days, cloud computing services are being used exponentially which in turn increases in multi-tenant distributed service(MTDS). Targeted attacks in MTDS propagated through side channel, shared memories, network a...
详细信息
Biomedical health monitoring systems are evolving rapidly and using non-invasive and cost effective sensors. These systems can monitor physiological parameters of the body to monitor health conditions and provide feed...
详细信息
暂无评论