Chetan Chaudhari - Academia.edu (original) (raw)
Uploads
Papers by Chetan Chaudhari
EAI endorsed transactions on pervasive health and technology, Apr 2, 2024
INTRODUCTION: Annual influenza epidemics and rare pandemics represent a significant global health... more INTRODUCTION: Annual influenza epidemics and rare pandemics represent a significant global health risk. Since the upper respiratory tract is the primary target of influenza, a diagnosis of influenza illness might be made using deep learning applied to pictures of the pharynx. Using pharyngeal imaging data and clinical information, the researcher created a deep-learning model for influenza diagnosis. People who sought medical attention for flu-like symptoms were the subjects included. METHODOLOGY: The study created a diagnostic and predicting Artificial Intelligence (AI) method using deep learning techniques to forecast clinical data and pharyngeal pictures for PCR confirmation of influenza. The accuracy of the AI method as a diagnostic tool was measured during the validation process. The extra research evaluated the AI model's diagnosis accuracy to that of three human doctors and explained the methodology using high-impact heat maps. In the training stage, a cohort of 8,000 patients was recruited from 70 hospitals. Subsequently, a subset of 700 patients, including 300 individuals with PCR-confirmed influenza, was selected from 15 hospitals during the validation stage. RESULTS: The AI model exhibited an operating receiver curve with an area of 1.01, surpassing the performance of three doctors by achieving a sensitivity of 80% and a specificity of 80%. The significance of heat maps lies in their ability to provide valuable insights. In AI models, particular attention is often directed towards analyzing follicles on the posterior pharynx wall. Researchers introduced a novel artificial intelligence model that can assist medical professionals in swiftly diagnosing influenza based on pharyngeal images.
Face recognition is a biometric approach t at employs automated methods to verify or recogni ze t... more Face recognition is a biometric approach t at employs automated methods to verify or recogni ze the identity of a living person based on his/her ph ysiological characteristics. In general, a biometri c identification system makes use of either physiolog ical characteristics (such as a fingerprint, iris p attern, or face) or behavior patterns (such as hand-writing, v oice, or key-stroke pattern) to identify a person. Because of human inherent protectiveness of his/her eyes, s ome people are reluctant to use eye identification systems. Face recognition has the benefit of being a passive , non-intrusive system to verify personal identity in a “natural” and friendly way.
Image processing using surface defect detection techniques in image detection, form of signal pro... more Image processing using surface defect detection techniques in image detection, form of signal processing for which the input is an image, such as a photograph or video frame. Examination of ceramic tile is finished in conditions like noise, high temperature, and wetness. There are many stages through that we are able to maintain quality of a tile. These stages include examination of color variation during a tile, chip offs during a tile, surface defects during a tile. This paper provides analysis of techniques that are helpful to search out surface defects like crack, blob, hole, variation in color, defect in corners, and pattern pair in tile that has pattern thereon. Glass defects are a significant reason for poor quality and of embarrassment for makers. It’s a tedious method to manually examine terribly giant size glasses. The manual examination method is slow, long and vulnerable to human error. Automatic examination systems victimization image process will overcome several of th...
International Journal of Recent Technology and Engineering, 2020
A roll of fabric with defects can have a depreciation of 45 to 65% with respect to the original p... more A roll of fabric with defects can have a depreciation of 45 to 65% with respect to the original price. While some commercial solutions exist, automatic fabric defect detection remains an active field of development and research. The goal is to extract the characteristics of the texture of the fabric to detect defects contained using image processing techniques. To date, there is no standard method which ensures the detection of texture defects in fabrics with high precision. In the following work, the use of Singular Value Decomposition (SVD), Local Binary Pattern (LBP) and GrayLevel Co-Occurrence Matrix (GLCM) features of images for the identification of defects in textiles is presented, where the application of techniques for pre-processing is presented, and for the analysis of texture LBP and the GLCM in order to extract features and segmentation is done using SVD approach. This model makes it possible to obtain compact and precise detection of the faulty texture structures. Our ...
EAI endorsed transactions on pervasive health and technology, Apr 2, 2024
INTRODUCTION: Annual influenza epidemics and rare pandemics represent a significant global health... more INTRODUCTION: Annual influenza epidemics and rare pandemics represent a significant global health risk. Since the upper respiratory tract is the primary target of influenza, a diagnosis of influenza illness might be made using deep learning applied to pictures of the pharynx. Using pharyngeal imaging data and clinical information, the researcher created a deep-learning model for influenza diagnosis. People who sought medical attention for flu-like symptoms were the subjects included. METHODOLOGY: The study created a diagnostic and predicting Artificial Intelligence (AI) method using deep learning techniques to forecast clinical data and pharyngeal pictures for PCR confirmation of influenza. The accuracy of the AI method as a diagnostic tool was measured during the validation process. The extra research evaluated the AI model's diagnosis accuracy to that of three human doctors and explained the methodology using high-impact heat maps. In the training stage, a cohort of 8,000 patients was recruited from 70 hospitals. Subsequently, a subset of 700 patients, including 300 individuals with PCR-confirmed influenza, was selected from 15 hospitals during the validation stage. RESULTS: The AI model exhibited an operating receiver curve with an area of 1.01, surpassing the performance of three doctors by achieving a sensitivity of 80% and a specificity of 80%. The significance of heat maps lies in their ability to provide valuable insights. In AI models, particular attention is often directed towards analyzing follicles on the posterior pharynx wall. Researchers introduced a novel artificial intelligence model that can assist medical professionals in swiftly diagnosing influenza based on pharyngeal images.
Face recognition is a biometric approach t at employs automated methods to verify or recogni ze t... more Face recognition is a biometric approach t at employs automated methods to verify or recogni ze the identity of a living person based on his/her ph ysiological characteristics. In general, a biometri c identification system makes use of either physiolog ical characteristics (such as a fingerprint, iris p attern, or face) or behavior patterns (such as hand-writing, v oice, or key-stroke pattern) to identify a person. Because of human inherent protectiveness of his/her eyes, s ome people are reluctant to use eye identification systems. Face recognition has the benefit of being a passive , non-intrusive system to verify personal identity in a “natural” and friendly way.
Image processing using surface defect detection techniques in image detection, form of signal pro... more Image processing using surface defect detection techniques in image detection, form of signal processing for which the input is an image, such as a photograph or video frame. Examination of ceramic tile is finished in conditions like noise, high temperature, and wetness. There are many stages through that we are able to maintain quality of a tile. These stages include examination of color variation during a tile, chip offs during a tile, surface defects during a tile. This paper provides analysis of techniques that are helpful to search out surface defects like crack, blob, hole, variation in color, defect in corners, and pattern pair in tile that has pattern thereon. Glass defects are a significant reason for poor quality and of embarrassment for makers. It’s a tedious method to manually examine terribly giant size glasses. The manual examination method is slow, long and vulnerable to human error. Automatic examination systems victimization image process will overcome several of th...
International Journal of Recent Technology and Engineering, 2020
A roll of fabric with defects can have a depreciation of 45 to 65% with respect to the original p... more A roll of fabric with defects can have a depreciation of 45 to 65% with respect to the original price. While some commercial solutions exist, automatic fabric defect detection remains an active field of development and research. The goal is to extract the characteristics of the texture of the fabric to detect defects contained using image processing techniques. To date, there is no standard method which ensures the detection of texture defects in fabrics with high precision. In the following work, the use of Singular Value Decomposition (SVD), Local Binary Pattern (LBP) and GrayLevel Co-Occurrence Matrix (GLCM) features of images for the identification of defects in textiles is presented, where the application of techniques for pre-processing is presented, and for the analysis of texture LBP and the GLCM in order to extract features and segmentation is done using SVD approach. This model makes it possible to obtain compact and precise detection of the faulty texture structures. Our ...