Abstract In the last decade, there has been a significant increase in medical cases involving brain tumors. Brain tumor is tenth most common type of tumor, affecting millions people. However, if it detected early, cure rate can increase. Computer vision researchers are working to develop sophisticated techniques for detecting and classifying MRI scans primarily used analysis. We proposed an automated system detection classification using saliency map deep learning feature optimization this...

One of the most challenging tasks for clinicians is detecting symptoms cardiovascular disease as earlier possible. Many individuals worldwide die each year from disease. Since heart a major concern, it must be dealt with timely. Multiple variables affecting health, such excessive blood pressure, elevated cholesterol, an irregular pulse rate, and many more, make to diagnose cardiac Thus, artificial intelligence can useful in identifying treating diseases early on. This paper proposes...

With the quick evolution of medical technology, era big data in medicine is quickly approaching. The analysis and mining these significantly influence prediction, monitoring, diagnosis, treatment tumor disorders. Since it has a wide range traits, low survival rate, an aggressive nature, brain regarded as deadliest most devastating disease. Misdiagnosed tumors lead to inadequate treatment, reducing patient's life chances. Brain detection highly challenging due capacity distinguish between...

Agriculture has becomes an immense area of research and is ascertained as a key element in the computer vision. In agriculture field, image processing acts primary part. Cucumber important vegetable its production Pakistan higher compared to other vegetables because use salads. However, diseases cucumber such Angular leaf spot, Anthracnose, blight, Downy mildew, powdery mildew widely decrease quality quantity. Lately, numerous methods have been proposed for identification classification...

Smart monitoring and assisted living systems for cognitive health assessment play a central role in of individuals’ conditions. Autistic children suffer from some difficulties including social skills, repetitive behaviors, speech nonverbal communication, accommodating to the environment around them. Thus, dealing with autistic is serious public problem as it hard determine what they feel lack emotional ability. Currently, no medical treatments have been shown cure children, most assistive...

Coronavirus disease 2019 (COVID-19) is a highly contagious that has claimed the lives of millions people worldwide in last 2 years. Because disease's rapid spread, it critical to diagnose at an early stage order reduce rate spread. The images lungs are used this infection. In years, many studies have been introduced help with diagnosis COVID-19 from chest X-Ray images. all researchers looking for quick method virus, deep learning-based computer controlled techniques more suitable as second...

COVID-19 detection and classification using chest X-ray images is a current hot research topic based on the important application known as medical image analysis. To halt spread of COVID-19, it critical to identify infection soon possible. Due time constraints expertise radiologists, manually diagnosing this from difficult time-consuming process. Artificial intelligence techniques have had significant impact analysis also introduced several for diagnosis. Deep learning explainable AI shown...

Fruit disease recognition is quickly becoming a hot topic in the field of computer vision. The presence plant diseases not only reduces fruit production but also causes significant loss to national economy. Citrus fruits help strengthen immune system, allowing it fight off such as COVID-19. Manual inspection with naked eye takes time and difficult; therefore, based method always required for accurate diseases. Several deep learning techniques recognizing citrus have been introduced...

Gait is commonly defined as the movement pattern of limbs over a hard substrate, and it serves source identification information for various computer-vision image-understanding techniques. A variety parameters, such human clothing, angle shift, walking style, occlusion, so on, have significant impact on gait-recognition systems, making scene quite complex to handle. In this article, we propose system that effectively handles problems associated with viewing shifts styles in real-time...

Image processing has enabled faster and more accurate image classification. It been of great benefit to the health industry. Manually examining medical images like MRI X-rays can be very time-consuming, prone human error, way costly. One such examination is Pap smear exam, where cervical cells are examined in laboratory settings distinguish healthy from abnormal cells, thus indicating early signs cancer. In this paper, we propose a convolutional neural network- (CNN-) based cell...

With the advent of Reinforcement Learning (RL) and its continuous progress, state-of-the-art RL systems have come up for many challenging real-world tasks. Given scope this area, various techniques are found in literature. One such notable technique, Multiple Deep Q-Network (DQN) based use multiple DQN-based-entities, which learn together communicate with each other. The learning has to be distributed wisely among all entities a scheme inter-entity communication protocol carefully designed....

Human gait recognition has emerged as a branch of biometric identification in the last decade, focusing on individuals based several characteristics such movement, time, and clothing. It is also great for video surveillance applications. The main issue with these techniques loss accuracy time caused by traditional feature extraction classification. With advances deep learning variety applications, particularly biometrics, we proposed lightweight method human this work. includes sequential...

Malignant melanoma is the most invasive skin cancer and currently regarded as one of deadliest disorders; however, it can be cured more successfully if detected treated early. Recently, CAD (computer-aided diagnosis) systems have emerged a powerful alternative tool for automatic detection categorization lesions, such malignant or benign nevus, in given dermoscopy images. In this paper, we propose an integrated framework rapid accurate Initially, input image pre-processed by using median...

The earlier prediction of heart diseases and appropriate treatment are important for preventing cardiac failure complications reducing the mortality rate. traditional classification approaches have resulted in a minimum rate accuracy hence to overcome pitfalls existing systems, present research is aimed perform with quantum learning. When learning employed ML (Machine Learning) DL (Deep algorithms, complex data can be performed efficiently less time higher Moreover, proposed algorithms...

The healthcare sector is a very crucial and important of any society, with the evolution various deployed technologies, like Internet Things (IoT), machine learning blockchain it has numerous advantages. However, in this section, data much more vulnerable than others, because strictly private confidential, requires highly secured framework for transmission between entities. In article, we aim to design blockchain-envisioned authentication key management mechanism IoMT-based smart...

In this study, twelve machine learning (ML) techniques are used to accurately estimate the safety factor of rock slopes (SFRS). The dataset for developing these models consists 344 from various open-pit mines around Iran, evenly distributed between training (80%) and testing (20%) datasets. evaluated accuracy using Janbu's limit equilibrium method (LEM) commercial tool GeoStudio methods. Statistical assessment metrics show that random forest model is most accurate in estimating SFRS (MSE =...

Diabetic retinopathy seems to be the cause of micro-vascular retinal alterations. It remains a leading reason for blindness and vision loss in adults around age 20 74. Screening this disease has become vital identifying referable cases that require complete ophthalmic evaluation treatment avoid permanent vision. The computer-aided design could ease screening process, which requires limited time, assist clinicians. main complexity classifying images involves huge computation, slow...

The significance of intelligent transportation is increasing in modern societies. development electric mobility a result extensive research and industrial needs. Conspicuously, the current study proposes smart Electric Vehicular (EV) performance system for industry that uses IoT-Fog-Cloud (IFC) computing technology to provide an effective analysis domestic commercial EVs. analyzes real-time EV-oriented attributes present Performance Analysis Measure (PAM). framework Bayesian Belief Model...

In recent times, the global rise in prevalence rate of amyotrophic lateral sclerosis (ALS) has profoundly affected welfare several people world. ALS is a lethal neurodegenerative disease (NDD) that damages nerve cells brain and spinal cord. Moreover, it removes person’s capability controlling muscle movements body. It necessary to detect earlier, reduce severity, enhance life expectancy patients. Traditionally, screening handled by qualified physicians through blood tests, which an...

ASD (autism spectrum disorder) is a neurodevelopmental disorder affecting people’s social interaction, learning, and communication skills worldwide. It behaviorally distinct syndrome that combined with several unknown known disorders. The symptoms include sleep disorders, seizures, gastrointestinal tract symptoms, anxiety, wandering, hyperactivity/attention‐deficit disorder, obesity. Hence, early detection of significant. However, clinically standardized screening tests are considered...

Alzheimer's disease (AD) and Parkinson's (PD) are two of the most prevalent neurodegenerative disorders, necessitating accurate diagnostic approaches for early detection effective management. This study introduces deep learning architectures, Residual-based Attention Convolutional Neural Network (RbACNN) Inverted (IRbACNN), designed to enhance medical image classification AD PD diagnosis. By integrating self-attention mechanisms, these models improve feature extraction, interpretability,...