Advanced object detection for smart accessibility: a Yolov10 with marine predator algorithm to aid visually challenged people.

A significant challenge for many visually impaired people is they cannot be entirely independent and are restricted by their vision. They face problems with such actions and object detection should be an essential feature they can rely on a regular basis. Object detection is applied to discover objects in the real world from an image of the world, like chairs, bicycles, tables, or doors, that are normal in the scenes of a blind predicated on their places.

Advanced smart assistance with enhancing social interaction and daily activities for visually impaired individuals using deep learning with modified seagull optimization.

Visually impaired individuals face daily challenges in social engagement and routine activities due to limited access to real-time environmental information. Damage detection is a common approach in infrastructure that combines steel and concrete reinforcement to achieve optimal durability and structural strength. These bridges, designed to withstand diverse loads such as seismic forces, traffic weight, and environmental factors, are significant for maintaining structural integrity.

Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images.

Stroke is a main risk to life and fitness in current society, particularly in the aging population. Also, the stroke is recognized as a cerebrovascular accident. It contains a nervous illness, which can result from haemorrhage or ischemia of the brain veins, and regular mains to assorted motor and cognitive damages that cooperate with functionality.

A hybrid object detection approach for visually impaired persons using pigeon-inspired optimization and deep learning models.

Visually challenged persons include a significant part of the population, and they exist all over the globe. Recently, technology has demonstrated its occurrence in each field, and state-of-the-art devices aid humans in their everyday lives. However, visually impaired people cannot view things around their atmospheres; they can only imagine the roaming surroundings.

Cloud-to-Thing continuum-based sports monitoring system using machine learning and deep learning model.

Sports monitoring and analysis have seen significant advancements by integrating cloud computing and continuum paradigms facilitated by machine learning and deep learning techniques. This study presents a novel approach for sports monitoring, specifically focusing on basketball, that seamlessly transitions from traditional cloud-based architectures to a continuum paradigm, enabling real-time analysis and insights into player performance and team dynamics. Leveraging machine learning and deep learning algorithms, our framework offers enhanced capabilities for player tracking, action recognition, and performance evaluation in various sports scenarios.

Artificial intelligence-driven ensemble deep learning models for smart monitoring of indoor activities in IoT environment for people with disabilities.

Disabled persons demanding healthcare is a developing global occurrence. The support in longer-term care includes nursing, intricate medical, recovery, and social help services. The price is large, but advanced technologies can aid in decreasing expenditure by certifying effective health services and enhancing the superiority of life.

Deep gradient reinforcement learning for music improvisation in cloud computing framework.

Artificial intelligence (AI) in music improvisation offers promising new avenues for developing human creativity. The difficulty of writing dynamic, flexible musical compositions in real time is discussed in this article. We explore using reinforcement learning (RL) techniques to create more interactive and responsive music creation systems.

Deep feature fusion with computer vision driven fall detection approach for enhanced assisted living safety.

Assisted living facilities cater to the demands of the elderly population, providing assistance and support with day-to-day activities. Fall detection is fundamental to ensuring their well-being and safety. Falls are frequent among older persons and might cause severe injuries and complications.

Harbor seal whiskers optimization algorithm with deep learning-based medical imaging analysis for gastrointestinal cancer detection.

Gastrointestinal (GI) cancer detection includes the detection of cancerous or potentially cancerous lesions within the GI tract. Earlier diagnosis is critical for increasing the success of treatment and improving patient outcomes. Medical imaging plays a major role in diagnosing and detecting GI cancer.

An enhanced drought forecasting in coastal arid regions using deep learning approach with evaporation index.

Coastal arid regions are similar to deserts, where it receives significantly less rainfall, less than 10 cm. Perhaps the world's worst natural disaster, coastal area droughts, can only be detected using reliable monitoring systems. Creating a reliable drought forecast model and figuring out how well various models can analyze drought factors in coastal arid regions are two of the biggest obstacles in this field.

Enhanced Pelican Optimization Algorithm with Deep Learning-Driven Mitotic Nuclei Classification on Breast Histopathology Images.

Breast cancer (BC) is a prevalent disease worldwide, and accurate diagnoses are vital for successful treatment. Histopathological (HI) inspection, particularly the detection of mitotic nuclei, has played a pivotal function in the prognosis and diagnosis of BC. It includes the detection and classification of mitotic nuclei within breast tissue samples.

Clinical Decision Support Systems to Predict Drug-Drug Interaction Using Multilabel Long Short-Term Memory with an Autoencoder.

Big Data analytics is a technique for researching huge and varied datasets and it is designed to uncover hidden patterns, trends, and correlations, and therefore, it can be applied for making superior decisions in healthcare. Drug-drug interactions (DDIs) are a main concern in drug discovery. The main role of precise forecasting of DDIs is to increase safety potential, particularly, in drug research when multiple drugs are co-prescribed.

Manta Ray Foraging Optimization Transfer Learning-Based Gastric Cancer Diagnosis and Classification on Endoscopic Images.

Gastric cancer (GC) diagnoses using endoscopic images have gained significant attention in the healthcare sector. The recent advancements of computer vision (CV) and deep learning (DL) technologies pave the way for the design of automated GC diagnosis models. Therefore, this study develops a new Manta Ray Foraging Optimization Transfer Learning technique that is based on Gastric Cancer Diagnosis and Classification (MRFOTL-GCDC) using endoscopic images.

Atom Search Optimization with Deep Learning Enabled Arabic Sign Language Recognition for Speaking and Hearing Disability Persons.

Sign language has played a crucial role in the lives of impaired people having hearing and speaking disabilities. They can send messages via hand gesture movement. Arabic Sign Language (ASL) recognition is a very difficult task because of its high complexity and the increasing intraclass similarity.

Hybrid Rider Optimization with Deep Learning Driven Biomedical Liver Cancer Detection and Classification.

Biomedical engineering is the application of the principles and problem-solving methods of engineering to biology along with medicine. Computation intelligence is the study of design of intelligent agents which are systems acting perceptively. The computation intelligence paradigm offers more advantages to the enhancement and maintenance of the field of biomedical engineering.

Optimal Deep Learning Enabled Prostate Cancer Detection Using Microarray Gene Expression.

Prostate cancer is the main cause of death over the globe. Earlier detection and classification of cancer is highly important to improve patient health. Previous studies utilized statistical and machine learning (ML) techniques for prostate cancer detection.