Skin cancer is caused due to unusual development of skin cells and deadly type cancer. Early diagnosis very significant can avoid some categories cancers, such as melanoma focal cell carcinoma. The recognition the classification malignant growth in beginning time expensive challenging. deep learning architectures recurrent networks convolutional neural (ConvNets) are developed past, which proven appropriate for non-handcrafted extraction complex features. To additional expand efficiency...

Despite the growing popularity of mobile web browsing, energy consumed by a phone browser while surfing is poorly understood. We present an infrastructure for measuring precise used to render pages. then measure needed financial, e-commerce, email, blogging, news and social networking sites. Our tools are sufficiently individual elements, such as cascade style sheets (CSS), Javascript, images, plug-in objects. results show that popular sites, downloading parsing Javascript consumes...

Music is a heavenly way of expressing feelings about the world. The language music has vast diversity. For centuries, people have indulged in debates to stratisfy between Western and Indian Classical Music. But through this paper, an understanding can be fabricated while differentiating types one essential characteristics Cultural Heritage. divided into two major parts, i.e. Hindustani Carnatic. Models been sculptured trained classify Carnatic In approaches are used implement classification...

Introduction A cross-sectional survey of 500 nurses was conducted to determine the level understanding EBP principles, frequency application in clinical settings, and barriers implementation. knowledge among is relatively moderate, but inconsistent hindered by many barriers, including time constraints, inadequate training, lack access research resources.

AI estimation is a man-made mental ability procedure for tracking down data chasing after keen decisions. Gigantic Data exceptionally influences consistent divulgences and worth creation. This paper presents methods in Computer based intelligence, fundamental improvements Big data. it huge care considering the likelihood that structures can get from data, see models make decisions with irrelevant human intercession. Learning appraisals various applications we use common. Each time web search...

Speech Recognition Technology can be embedded in various real time applications order to increase the human-computer interaction.From robotics health care and aerospace, from interactive voice response systems mobile telephony telematics, speech recognition technology have enhanced humanmachine interaction.Gender is an important component for application embedding as it reduces computational complexity further processing these applications.The paper involves extraction of one most dominant...

Biometric matching decisions have traditionally been made based solely on a score that represents the similarity of query biometric to enrolled biometric(s) claimed identity. Fusion schemes proposed benefit from availability multiple samples (e.g., same fingerprint) or different biometrics face and fingerprint). These commonly adopted fusion approaches rarely make use large number non-matching available in database form other identities training data. In this paper, we study impact combining...

Most biometric verification techniques make decisions based solely on a score that represents the similarity of query template with reference claimed identity stored in database. When multiple templates are available, fusion scheme can be designed using similarities these templates. Combining several to construct composite and selecting set useful has also been reported addition usual multi-classifier methods when matchers available. These commonly adopted rarely use large number...

One of the main challenges in building an efficient and scalable automatic fingerprint identification system is to identify features which are highly discriminative reproducible across different prints same finger. Most existing matching approaches rely on minutiae geometry. Relatively, little effort has gone into analyzing ridge flow patterns present fingerprint, partly due difficulty extracting robust from images. In this paper, we analyze usefulness curvature information for...

In Test-time Adaptation (TTA), given a source model, the goal is to adapt it make better predictions for test instances from different distribution than source. Crucially, TTA assumes no access data or even any additional labeled/unlabeled samples target finetune model. this work, we consider in more pragmatic setting which refer as SITA (Single Image Adaptation). Here, when making prediction, model has only single instance, rather batch of instances, typically been considered literature....

Graph Neural Networks (GNNs) are a popular technique for modelling graph-structured data and computing node-level representations via aggregation of information from the neighborhood each node. However, this implies an increased risk revealing sensitive information, as node can participate in inference multiple nodes. This that standard privacy-preserving machine learning techniques, such differentially private stochastic gradient descent (DP-SGD) - which designed situations where point...

Abstract A person does not need to go through pages of articles for a given topic understand the gist; mere summary is more than sufficient in many cases. This has rise apps that crunch hundreds generate personalized feed summaries user can through. With and people having access internet, lots information being created shared online. gives us luxury it just click away from consumption. However, all this filtered cleared noise. work aims explore different techniques text summarization...

Novel Class Discovery (NCD) is a learning paradigm, where machine model tasked to semantically group instances from unlabeled data, by utilizing labeled disjoint set of classes. In this work, we first characterize existing NCD approaches into singlestage and two-stage methods based on whether they require access data together while discovering new Next, devise simple yet powerful loss function that enforces separability in the latent space using cues multi-dimensional scaling, which refer as...

Though a lot of research has been done to match fingerprints, most existing approaches rely on locations minutiae features for matching tasks. Relatively, little effort gone into utilizing textural information present in fingerprints as distinguishing characteristic. In this paper, we propose novel gradient-based approach characterize the task biometric matching. particular, proposed uses histograms oriented gradients (HOGs) represent neighborhoods. The neighborhoods are divided several...

The goal of this study is to present a comparative analysis between the three feature extraction techniques: Linear Predictive Coefficients (LPC), Prediction Cepstral (LPCC), and Weighted (WLPCC) for distinguishing speech Intellectually Disabled (ID) children from Typically Developed (TD). Speech samples ID were recorded government-owned special school in India used analysis. Control taken author’s institute. Pre-processing techniques better parameterization. Two classifiers, Artificial...

The machine learning classifiers are found to be the most relevant regarding emotions and gender recognition using speech. In this research, recognized with help of two classifiers: Support Vector Machine Naive Bayes which incorporates four speech features: shimmer, jitter, energy, pitch for classification. take these input sequences correctly classify as well emotion in signal. Results shows, classification accuracy, outperforms classifier by almost 10% 35% recognition. techniques applying...