Results 41 to 50 of about 2,576 (162)

Improved YOLOv5 for Efficient Elimination of Unwanted Video Frames From High‐Speed Video Arrays Capturing Bat's Kinematics

Applied AI Letters, Volume 7, Issue 1, February 2026.
Deep learning pipeline developed to filter high‐speed bat flight recordings captured inside a custom flight tunnel. ABSTRACT This research aims to investigate the flying kinematics of bats, drawing inspiration from nature to benefit humans in achieving vision‐independent flights. The project uses 50 cameras mounted inside a specially designed tunnel to
D. P. Jayathunga, M. Ramashini, Juliana Zaini, R. Müller, Liyanage C. De Silva   +4 more
wiley   +1 more source

An Effective Approach for Recognition of Crop Diseases Using Advanced Image Processing and YOLOv8

Food Science &Nutrition, Volume 14, Issue 2, February 2026.
The performance of processed images is evaluated using mean‐squared‐error and peak‐signal‐to‐noise ratio. After the processing phase, an advanced deep learning model, YOLOv8, was used for the segmentation and classification of crop diseases. Using a large dataset comprising 32 diseases to train our model, we implemented Transfer Learning using YOLOv8 ...
Muhammad Nouman Noor, Muhammad Masab, Farah Haneef, Muzammil Hussain, Mateen Yaqoob, Tehseen Mazhar, Muhammad Amir Khan, Ghadah Aldehim   +7 more
wiley   +1 more source

BiT‐HyMLPKANClassifier: A Hybrid Deep Learning Framework for Human Peripheral Blood Cell Classification Using Big Transfer Models and Kolmogorov–Arnold Networks

Advanced Intelligent Systems, Volume 8, Issue 1, January 2026.
This study presents BiT‐HyMLPKANClassifier, a novel hybrid deep learning framework for automated human peripheral blood cell classification. Model combines Big Transfer models with multilayer perceptron and efficient Kolmogorov–Arnold Network architectures, achieving over 97% accuracy.
Ömer Miraç KÖKÇAM, Ferhat UÇAR
wiley   +1 more source

Analyzing darknet traffic through machine learning and neucube spiking neural networks

Intelligent and Converged Networks
The rapidly evolving darknet enables a wide range of cybercrimes through anonymous and untraceable communication channels. Effective detection of clandestine darknet traffic is therefore critical yet immensely challenging.
Iman Akour, Mohammad Alauthman, Khalid M. O. Nahar, Ammar Almomani, Brij B. Gupta   +4 more
doaj   +1 more source

A Critical Review on the Application and Innovation in Smart Fisheries

Engineering Reports, Volume 8, Issue 1, January 2026.
Smart fisheries powered by Artificial Intelligence (AI), Internet of Things (IoT), and machine learning can spot diseases early, monitor water in real time, and identify fish automatically, helping farmers boost yields, cut losses, and protect sustainability in countries like Bangladesh.
Shahim Uddin Saba, Fatima Ibrahim, Sabrina Islam Priti, Rayhan Pervej, Alaya Parven Alo, Mahady Hasan, Md. Tarek Habib   +6 more
wiley   +1 more source

Classification for avian malaria parasite Plasmodium gallinaceum blood stages by using deep convolutional neural networks

Scientific Reports, 2021
The infection of an avian malaria parasite (Plasmodium gallinaceum) in domestic chickens presents a major threat to the poultry industry because it causes economic loss in both the quality and quantity of meat and egg production. Computer-aided diagnosis
Veerayuth Kittichai, Morakot Kaewthamasorn, Suchansa Thanee, Rangsan Jomtarak, Kamonpob Klanboot, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang   +8 more
doaj   +1 more source

stichwort Darknet

merz | medien + erziehung, 2017
Spätestens seit dem Amoklauf in München im Juli 2016, der neun Menschen das Leben kostete, ist das Darknet in aller Munde. Der Amokläufer hatte seine Waffe und Munition mit hoher Wahrscheinlichkeit dort gekauft. Das Internet besteht nämlich aus drei unterschiedlichen Schichten: 1) dem Clearnet, das jeder nutzen kann.
openaire   +1 more source

YOLO‐O: An Improved YOLO‐Based Framework for Vehicle Detection

IET Image Processing, Volume 20, Issue 1, January/December 2026.
This study proposes a YOLO‐O model, based on YOLOv7, for improved detection of tiny vehicles on roads. Enhancements like residual networks, Squeeze and Excitation Network (SENet), coordinate attention, and SIoU regression loss boost precision, especially for small objects.
Rabbia Mahum, Usama Irshad, Ahmed M. El‐Sherbeeny, Mohammad Shehab, Seongkwan Mark Lee   +4 more
wiley   +1 more source

Age and Sex Estimation in Children and Young Adults Using Panoramic Radiographs with Convolutional Neural Networks

Applied Sciences
Image processing with artificial intelligence has shown significant promise in various medical imaging applications. The present study aims to evaluate the performance of 16 different convolutional neural networks (CNNs) in predicting age and gender from
Tuğçe Nur Şahin, Türkay Kölüş
doaj   +1 more source

A Novel Fusion Mechanism‐Based Lightweight Efficient Convolutional Attention Network for Jute Pest Classification

IET Image Processing, Volume 20, Issue 1, January/December 2026.
Accurate and efficient identification of jute pests is essential to sustaining agricultural yield and preventing fiber‐quality degradation in jute (Corchorus spp.) production. Traditional visual inspection is subjective, labor‐intensive, and error‐prone under variable field conditions, motivating the need for robust automated classification systems ...
Irfan Haider, Muhammad Attique Khan, Saleha Masood, Haya Aldossary, Leila Jamel, Yongwon Cho, Yunyoung Nam   +6 more
wiley   +1 more source