Fake news proliferation on social media platforms has become alarming because it poses threats to various aspects of society. Fake news encompasses intentionally falsified information designed to mislead readers and m...
详细信息
The recent growth of open source repositories and deep learning models brought big promises for the next generation of programming tools that can automate or significantly improve the software development process. Yet...
详细信息
For many developing countries like India the role of the agricultural sector is very significant. Chili has a very high economic value. India is ranked 5th in the production and 1st in exporting chili. Chili is one of...
For many developing countries like India the role of the agricultural sector is very significant. Chili has a very high economic value. India is ranked 5th in the production and 1st in exporting chili. Chili is one of the important cash crops of our country but they are vulnerable to various fungal, bacterial, and viral diseases. Among these diseases, the leaves of chili plants are more susceptible to harm, it's one main reason we have considered chili leaves for our study. This paper presents a detailed overview of various chili diseases and the work done in this field till now. Manual detection of diseases is a time consuming and strenuous task for the farmers. In this paper we are introducing various imageprocessing and machinelearning techniques for early and efficient detection of diseases in chili leaves. The diagnosis of chili disease by capturing leaf images is a very efficient and affordable system, especially for helping farmers to keep an eye on large plantations.
This chapter reviews the basics and recent researches of computer-aided diagnosis (CAD) systems for assisting neuroradiologists in the detection, monitoring and prediction of multiple sclerosis (MS) in magnetic resona...
详细信息
The proceedings contain 32 papers. The topics discussed include: a survey of image pre-processing techniques for medical images;disease detection in rice leaves using transfer learning techniques;comparative analysis ...
The proceedings contain 32 papers. The topics discussed include: a survey of image pre-processing techniques for medical images;disease detection in rice leaves using transfer learning techniques;comparative analysis of machinelearning methods to detect chronic kidney disease;DEEPORCD: detection of oral cancer using deep learning;an adaptive fuzzy system based insider attacks detection with group key management for wireless ad-hoc network;student result prediction in Covid-19 lockdown using machinelearning techniques;acceleration of web interface generation through voice commands;football player performance analysis using particle swarm optimization and player value calculation using regression;auto-off ID: automatic detection of offensive language in social media;and implementation of robotics and its impact on sustainable banking: a futuristic study.
The identification of traditional Chinese medicine is the key to control the quality of traditional Chinese medicine and ensure the safety and effectiveness of clinical medication. Compared with the physical and chemi...
详细信息
The identification of traditional Chinese medicine is the key to control the quality of traditional Chinese medicine and ensure the safety and effectiveness of clinical medication. Compared with the physical and chemical identification methods with expensive equipment and complex operation, microscopic image identification of traditional Chinese medicine is an effective method with low cost. However, this method still has a high learning cost and identification errors due to staff fatigue. Therefore, this paper designs an effective automatic recognition approach of Chinese herbal medicine by micro imageprocessing. The core of this method is the introduction of transfer learning and data enhancement methods, which effectively alleviates the problem of insufficient number of microscopic image data samples in the microscopic recognition of traditional Chinese medicine, and realizes the automatic recognition of traditional Chinese medicine. We construct a library of microscopic recognition features of Chinese herbal medicine, and designe evaluation experiments on this basis. The results show that the recognition performance of our method is better than that of SSD method, especially the F1 value is increased by 7.25 %.
Kidney disease has become a worldwide public health crisis because of the shocking rise in death and illness it has caused. Due to its low cost and the flexibility to do investigations at the bedside, ultrasound has b...
详细信息
Kidney disease has become a worldwide public health crisis because of the shocking rise in death and illness it has caused. Due to its low cost and the flexibility to do investigations at the bedside, ultrasound has become the imaging modality of choice for identifying kidney disorders. Radiologists and sonologists are the experts at deciphering ultrasound images for medical purposes. The diagnostics and healthcare of a society can be vastly improved with the introduction of a low-cost imaging modality that eliminates the need for radiation. This problem must be solved in a way that eliminates observer variance. One such option is computer-assisted diagnosis (CAD), which provides more trustworthy and accurate diagnoses that are temporarily immune to observer variances. The renal region has been proposed to be segmented using Distance Regularized Level Set (DRLS), which is driven by a theoretically intensity invariant characteristic. In the past, ultrasound image segmentation has been considered difficult because of the poor contrast of the pictures. There are a number of issues with these photographs, including weak signal and blurry edges. It has been discovered by medical professionals that manual demarcation relies not only on intensity data but also on contextual details. Because of this, properties like local phase and direction, which are theoretically independent of intensity, are often used. The monogenic signal notion is used to retrieve local information in this study. Metrics like the dice similarity coefficient and the mean absolute deviation are used to quantify the potential of the suggested segmentation system. And in the setting of inter-observer and intra-observer variability in organ delineation, PBDRLSE is determined to be effective and promising when compared to the standard and current efforts.
This research paper aimed to identify the most effective machine-learning approach for breast cancer detection. The study utilized the Breast Cancer Wisconsin (Diagnostic) Data Set and evaluated five different algorit...
详细信息
Modern Unmanned Aerial Vehicles (UAV) equipped with cameras can play an essential role in speeding up the identification and rescue of people who have fallen overboard, i.e., man overboard (MOB). To this end, Artifici...
详细信息
ISBN:
(纸本)9783031064302;9783031064296
Modern Unmanned Aerial Vehicles (UAV) equipped with cameras can play an essential role in speeding up the identification and rescue of people who have fallen overboard, i.e., man overboard (MOB). To this end, Artificial Intelligence techniques can be leveraged for the automatic understanding of visual data acquired from drones. However, detecting people at sea in aerial imagery is challenging primarily due to the lack of specialized annotated datasets for training and testing detectors for this task. To fill this gap, we introduce and publicly release the MOBDrone benchmark, a collection of more than 125K drone-view images in a marine environment under several conditions, such as different altitudes, camera shooting angles, and illumination. We manually annotated more than 180K objects, of which about 113K man overboard, precisely localizing them with bounding boxes. Moreover, we conduct a thorough performance analysis of several state-of-the-art object detectors on the MOBDrone data, serving as baselines for further research.
From time to time, lung cancer has appeared in the category of nearly the most lethal maladies since humankind existed. It is even among the most incessant fatalities and major reasons of mortality among all cancers. ...
详细信息
暂无评论