Abstract Trends of kidney cancer cases worldwide are expected to increase persistently and this inspires the modification traditional diagnosis system respond future challenges. Renal Cell Carcinoma (RCC) is most common responsible for 80–85% all renal tumors. This study proposed a robust computationally efficient fully automated Grading Network (RCCGNet) from histopathology images. The RCCGNet contains shared channel residual (SCR) block which allows network learn feature maps associated...

In this paper, an efficient technique for image compression and quality retrieval using matrix completion is presented. The proposed based on low-rank singular value truncation thresholding. Here, decomposed decomposition (SVD) to obtain a low rank of data, which approximated in compressed form. Later on, thresholding algorithm exploited retrieve visual the image. presented method easily applicable various characteristics different efficiency. A detailed analysis has been show efficiency...

In this study, an inter‐ and intra‐beat correlation‐based compression technique for electrocardiogram (ECG) signal is proposed using singular coefficient truncation, based on value decomposition (SVD) adaptive scanning wavelet difference reduction technique. method, correlated beat segments are arranged in N × M array, processed with Initially, array decomposed into triplets SVD which most significant energy concentrated first few values. The insignificant coefficients truncated retained...

This study presents an improved technique for compression of electrocardiogram (ECG) signals, based on beat correlation signal and principle component (PC) analysis, ECG signal. For this purpose, two‐dimensional matrix temporal inter‐and intra‐beat is constructed, further achieved using PC extraction. Beat helps to generate very few PCs that increase the efficiency. A detailed analysis has been presented ten signals having different rhythms, wave morphologies abnormalities Massachusetts...

In this paper, an improved method for electrocardiogram (ECG) signal compression using Set Partitioning in Hierarchical Trees (SPIHT) algorithm is proposed. ECG signals are compressed based on different transform such as discrete cosine and wavelet with modified SPIHT. The SPIHT yields good controlled quantity of degradation requires computational time compared to earlier published algorithms. proposed suitable the telemedicine or e-health system due minimum time.

Photoplethysmogram signals are becoming increasingly important for the detection of abnormalities in patients. Peak plays a significant role diagnosis and monitoring using PPG signals. Although copious number methods available peak detection, none them consider an online processing signal. In this paper we propose algorithm that tries to mimic human cognitive model three-layered feedforward neural network trained sequential learning algorithm. The processed sequentially without...

In this paper, an ECG signal compression technique is presented based on Slantlet transform with different thresholding functions. The method exploited the uniform quantization (UQ) methods criteria slantlet coefficients of signal. This returned better reconstruction from compressed data as compare to wavelet and discrete cosine due energy compaction efficiency. A detail analysis has been for retrieval efficiency along evaluation criteria. tested obtained MIT-BIH arrhythmia database....

Human activity recognition (HAR) and Extreme Learning Machines (ELM) are emerging fields of research. HAR investigates the behavioural attributes humans integrates that to an electronic system. An ELM is a fast learning algorithm, overcomes fundamental issue slow training-error convergence other algorithms such as back propagation algorithm suffer. In this paper, we present blend two by classifying using Artificial Neural Networks (ANN) trained Sequential Algorithm (SELA). The efficacious...

In this paper, medical image compression technique is presented based on adaptive Scan Wavelet Difference Reduction (ASWDR). It helps to save the storage space and transmission bandwidth of tele-healthcare system. The scheme has evaluated for different ultrasound cases. ASWDR exploited with wavelet filters obtained efficiency as per distinctive sparse characteristics. However, performance fidelity assessments well human vision perception reconstruction. As seen results, up 45:1 99%...

In recent years, technologies related to Facial Recognition have undergone a remarkable upgradation in the domain of commerce as well security. This paper presents an automated real-time attendance management system (AMS) using face recognition technique reduce human dependency and thereby saving time. A modified local binary pattern histogram (MLBPH) algorithm based on calculation pixel neighborhood gray median for extracting significant features face. More specifically, facial landmarks...

An Electrocardiogram (ECG) signal compression becomes more area of interest due to increases demand tel-e-healthcare system. In this manuscript, dual tree discrete wavelet decomposition (DT-DWT) based ECG is exploited using zero run-length coding techniques. The main advancement proposed technique, its sensitivity generating sparse data set that helps enhance performance Performance method evaluated through ratio and percentage root-mean square difference quality the cross correlation...

Automated recognition system for handwritten Hindi words in legal documents is an essential requirement India. In order to achieve good accuracy, precise segmentation necessary. Segmentation algorithms language mostly uses zone identification as a pre-segmentation stage. the present work, we propose character method that identifies different zones of word image and utilizes fuzzy function estimating headline pixels further outer contour along with estimated segment upper lower modifiers,...

An Electrocardiogram (ECG) signal compression technique is proposed using compressed sensing/sampling based on Block sparse Bayesian learning (BSBL) algorithm. Advantage of method over the conventional stat-of-art techniques energy efficient, highly compressive and minimum reconstruction error. Here, BSBL has utilized especially for ECG to enhance performance data handling/communication system telemedicine. Simulated results have achieved 75% with very good quality reconstruction. Therefore,...

Peak detection is a facile wing of signal processing. Conventional peak algorithms detect peaks when the entire made available to them. In contrast, we propose method that based on recognizing fundamental shapes signal, and overall intuitive in nature. Towards this, use feedforward neural network trained using online sequential learning algorithm which provides better convergence performance relative back propagation algorithm. Moreover, training avoids complex pre-processing tasks feature...