The ambitious target of net-zero emission by 2050 has been aggressively driving the renewable energy sector in many countries. Leading race sources is solar energy, fastest growing source at present. industry witnessed more growth last decade than it past 40 years, owing to its technological advancements, plummeting costs, and lucrative incentives. United States one largest producers power world a pioneer adoption, with major projects across different technologies, mainly photovoltaic,...

Since the COVID-19 pandemic, several research studies have proposed Deep Learning (DL)-based automated detection, reporting high cross-validation accuracy when classifying patients from normal or other common Pneumonia. Although reported outcomes are very in most cases, these results were obtained without an independent test set a separate data source(s). DL models likely to overfit training distribution sets not utilized prone learn dataset-specific artifacts rather than actual disease...

The novel Coronavirus Disease 2019 (COVID-19) is a global pandemic disease spreading rapidly around the world. A robust and automatic early recognition of COVID-19, via auxiliary computer-aided diagnostic tools, essential for cure control. chest radiography images, such as Computed Tomography (CT) X-ray, deep Convolutional Neural Networks (CNNs), can be significant useful material designing tools. However, an automated tool challenging massive number manually annotated datasets are not...

Accurate and robust whole heart substructure segmentation is crucial in developing clinical applications, such as computer-aided diagnosis surgery. However, the of different substructures challenging because inadequate edge or boundary information, complexity background texture, diversity substructures' sizes shapes. This article proposes a framework for multi-class employing non-rigid registration-based probabilistic atlas incorporating Bayesian framework. We also propose registration...

Epileptic seizure is one of the common neurological disorder now a day. But this curable if it can be detected in early stage. So, research become necessity prediction epileptic seizure. A complete and reliable system classify patients states This explores supervised machine learning deep model for classification from Seizure dataset UCI repository. The has 11,500 instances; every information contains 178 attributes. XGBoost used Machine approach ANN Deep approach. proposed algorithm...

Mammography is the most widely used gold standard for screening breast cancer, where mass classification a prominent step. Classification of in is, however, an arduous problem as they usually have large variations terms shape, size, boundary, and texture. In this study, process automated with use transfer learning Deep Convolutional Neural Networks (DCNN) to extract features, bagged decision tree feature selection, finally Support Vector Machine (SVM) classifier classifying non-mass tissue....

Face liveness detection is a big challenge for the researcher. recognition based security system suffer from spoofing attack, because of lacking proper face system. In this paper, we proposed new approach to prevent attack with two stage approach, one motion and another deep learning based. The network train on ROSE-Youtu Liveness Detection Database. whole model test real time videos webcam. This combine gives better performance than other approaches in Our an accuracy 95.44% error rate...

ABSTRACT A large number of studies in the past months have proposed deep learning-based Artificial Intelligence (AI) tools for automated detection COVID-19 using publicly available datasets Chest X-rays (CXRs) or CT scans training and evaluation. Most these report high accuracy when classifying patients from normal other commonly occurring pneumonia cases. However, results are often obtained on cross-validation without an independent test set coming a separate dataset biases such as two...

Stress is the non-specific response of human brain which changes according to demand day life. In this paper stress and relaxation identified from activation alpha ( α) beta β) EEG bands depending on their power spectral density (PSD). occurs due sustained mental task in a test (Bengali, English, Math) environment work has been performed Reading, Writing Mathematical problem-solving stages. When β/α ratio 1.5 or more it indicates stress. The estimated taking PSD at different time interval...

Music is a popular source of entertainment and way relief from stress. But with the elapse time duration it may changes mood human being. In this paper, age based being will be analyzed music stimulated potentials on power spectral density (PSD). different languages Bengali, English Tamil are taken as chosen stimuli. Rock, POP Metal songs which categorized PSD considered genre. Three groups selected subjects EEG signals while listening genres. Wavelet transformation performed to denoise...

Automated skin lesion analysis for simultaneous detection and recognition is still challenging inter-class homogeneity intra-class heterogeneity, leading to low generic capability of a Single Convolutional Neural Network (CNN) with limited datasets. This article proposes an end-to-end deep CNN-based framework the lesions, named Dermo-DOCTOR, consisting two encoders. The feature maps from encoders are fused channel-wise, called Fused Feature Map (FFM). FFM utilized decoding in sub-network,...

For the emerging significance of mental stress, various research directives have been established over time to better understand causes stress and how deal with it. In recent years, rise video gameplay is unprecedented, further triggered by lockdown imposed due COVID-19 pandemic. This paper presents an end-to-end analysis for gaming stimuli using EEG. The PSD value Alpha Beta bands computed calculate Beta-to-Alpha ratio (BAR). this article, BAR used denote stress. Subjects are chosen based...

Accurate and robust whole heart substructure segmentation is crucial in developing clinical applications, such as computer-aided diagnosis surgery. However, of different substructures challenging because inadequate edge or boundary information, the complexity background texture, diversity substructures' sizes shapes. This article proposes a framework for multi-class employing non-rigid registration-based probabilistic atlas incorporating Bayesian framework. We also propose registration...