Automated breast cancer detection in digital mammograms: A moth flame optimization based ELM approach
Early detection of breast cancer based on a digital mammogram is an important research
domain in the field of medical image analysis. An improved CAD model is proposed in this …
domain in the field of medical image analysis. An improved CAD model is proposed in this …
Fast discrete curvelet transform and modified PSO based improved evolutionary extreme learning machine for breast cancer detection
A significant research area in medical imaging analysis is digital mammography breast
cancer detection in the early stage. For breast mass classification into the benign or …
cancer detection in the early stage. For breast mass classification into the benign or …
A diabetes monitoring system and health-medical service composition model in cloud environment
Diabetes is a common chronic illness or absence of sugar in the blood. The early detection
of this disease decreases the serious risk factor. Nowadays, Machine Learning based cloud …
of this disease decreases the serious risk factor. Nowadays, Machine Learning based cloud …
An empirical evaluation of extreme learning machine uncertainty quantification for automated breast cancer detection
Early detection and diagnosis are the key factors in decreasing the breast cancer mortality
rate in medical image analysis. A randomized learning technique called extreme learning …
rate in medical image analysis. A randomized learning technique called extreme learning …
[HTML][HTML] Exploration of Advancements in Handwritten Document Recognition Techniques
Handwritten document recognition and classification are among the many computers related
issues being studied for digitizing handwritten data. A handwritten document comprises text …
issues being studied for digitizing handwritten data. A handwritten document comprises text …
MantaRayWmark: An image adaptive multiple embedding strength optimization based watermarking using Manta Ray Foraging and bi-directional ELM
Digital watermarking schemes based on a single value of embedding strength do not take
into account the local characteristics of the host signal for watermark embedding …
into account the local characteristics of the host signal for watermark embedding …
An effective and improved CNN-ELM classifier for handwritten digits recognition and classification
Optical character recognition is gaining immense importance in the domain of deep
learning. With each passing day, handwritten digits (0–9) data are increasing rapidly, and …
learning. With each passing day, handwritten digits (0–9) data are increasing rapidly, and …
Analysis of Cursive Text Recognition Systems: A Systematic Literature Review
Regional and cultural diversities around the world have given birth to a large number of
writing systems and scripts, which consist of varying character sets. Develo** an optimal …
writing systems and scripts, which consist of varying character sets. Develo** an optimal …
Sliding window based off-line handwritten text recognition using edit distance
A significant issue in the domain of optical character recognition is handwritten text
recognition. Here, two novel feature extraction techniques are proposed using a fixed-size …
recognition. Here, two novel feature extraction techniques are proposed using a fixed-size …
H‐WordNet: a holistic convolutional neural network approach for handwritten word recognition
Segmentation of handwritten words into isolated characters and their recognition are
challenging due to the presence of high variability and cursiveness in Indian scripts. The …
challenging due to the presence of high variability and cursiveness in Indian scripts. The …