Review of iris segmentation and recognition using deep learning to improve biometric application by Rasheed Hind Hameed, Shamini Sara Swathy, Mahmoud Moamin A., Alomari Mohammad Ahmed

“…Iris segmentation, which isolates the iris from the rest of the ocular image, determines iris identification accuracy. The main problem is concerned with selecting the best deep learning (DL) algorithm to classify and estimate biometric iris biometric iris. …”
Get full text

Automated classification of trees and evaluation of cone yield using drones by Alekhina Anna, Pastukhova Albina, Shcherba Yulia, Rodin Ilya

“…In the study, analyzed the effectiveness of unmanned aerial vehicles (UAVs) for forest monitoring. Investigated various image processing algorithms aimed at identifying tree species. …”
Get full text

Blockchain and Bigdata to Secure Data Using Hash and Salt Techniques by AlSelami Fudhah A.

“…Data Types these days varies from images, video, social media data, surveys to blogs etc. …”
Get full text

Quantification of nipple size and shape among an ethnically diverse sample of US women by Peter Wildfeuer, Alexis Alban, Bob Worrell, Shilo Ben Zeev, Judith Shamian, Mike Woolridge

“…A total of 510 women were recruited into this study—using an iPhone App, employing the ‘True Depth Scanning’ software, and scanning their torso from both the left and right aspect to secure an image of each breast. They provided 1,129 scans, of which 835 (74%) were submitted to a purpose-built algorithm which isolated the nipple-areola complex as a definable 3D cube, which was re-aligned to enable key parameters of nipple geometry to be measured. …”
Get full text

Integration of resting state functional MRI into clinical practice - A large single institution experience. by Eric C Leuthardt, Gloria Guzman, S Kathleen Bandt, Carl Hacker, Ananth K Vellimana, David Limbrick, Mikhail Milchenko, Pamela Lamontagne, Benjamin Speidel, Jarod Roland, Michelle Miller-Thomas, Abraham Z Snyder, Daniel Marcus, Joshua Shimony, Tammie L S Benzinger

“…One hundred and ninety one consecutive patients underwent a 3T rs-fMRI, 83 of whom also underwent both motor and language task-based fMRI. Data were processed using a novel, automated, multi-layer perceptron algorithm and integrated into stereotactic navigation using a streamlined IT imaging pipeline. …”
Get full text

Real-Time Common Rust Maize Leaf Disease Severity Identification and Pesticide Dose Recommendation Using Deep Neural Network by Zemzem Mohammed Megersa, Abebe Belay Adege, Faizur Rashid

“…In the model development process, we collected 5000 maize leaf images experimentally, with permission from Haramaya University, and increased the size of the dataset to 8000 through augmentation. …”
Get full text

DeepDate: A deep fusion model based on whale optimization and artificial neural network for Arabian date classification. by Nour Eldeen Mahmoud Khalifa, Jiaji Wang, Mohamed Hamed N Taha, Yudong Zhang

“…However, the increasing yields also put a lot of pressure on the classification step afterward. Image recognition based on deep learning algorithms can help to identify and classify the date fruit species, even in natural light.…”
Get full text

Convolutional transform learning based fusion framework for scale invariant long term target detection and tracking in unmanned aerial vehicles by Fatma S. Alrayes, Nazir Ahmad, Asma Alshuhail, Menwa Alshammeri, Ali Alqazzaz, Hassan Alkhiri, Jehad Saad Alqurni, Yahia Said

“…At first, the presented LTTDT–UAVDFCTL technique performs image pre-processing by utilizing the median median-enhanced wiener filter (MEWF) technique to improve clarity and reduce noise. …”
Get full text

ANALYSIS OF EMOTION RECOGNITION BASED ON DEEP CONVOLUTIONAL NEURAL NETWORK MODELS by V. M. Goryaev, G. A. Mankaeva, T. B. Ochir-Goryaeva, A. B. Mantusov, V. V. Lidji-Garyaev, A. B. Kornyakov

“…Experimental studies of emotional processes are usually based on the observation of images with affective content, including facial expressions. …”
Get full text

An AI-Based Open-Source Software for <i>Varroa</i> Mite Fall Analysis in Honeybee Colonies by Jesús Yániz, Matías Casalongue, Francisco Javier Martinez-de-Pison, Miguel Angel Silvestre, Beeguards Consortium, Pilar Santolaria, Jose Divasón

“…This study was designed to develop and test under field conditions a new free software (VarroDetector) based on a deep learning approach for the automated detection and counting of <i>Varroa</i> mites using smartphone images of sticky boards collected in honeybee colonies. …”
Get full text

Deep Residual Transfer Ensemble Model for mRNA Gene-Expression-Based Breast Cancer by Job Prasanth Kumar Chinta Kunta, Vijayalakshmi A. Lepakshi

“…The proposed method at first transformed mRNA one-dimensional sequences into 2D images. Executing standard pre-processing tasks, the synthetic underrepresented class over-sampling technique (SMOTE) was applied to alleviate any possible class-imbalance problem. …”
Get full text

Developing an AI-based application for caries index detection on intraoral photographs by Niha Adnan, Syed Muhammad Faizan Ahmed, Jai Kumar Das, Sehrish Aijaz, Rashna Hoshang Sukhia, Zahra Hoodbhoy, Fahad Umer

“…These images were meticulously annotated by two experienced dentists and further verified by senior dentists. …”
Get full text

Defect segmentation network of photovoltaic modules based on multi-scale convolution and attention mechanism by Dang Ning, Li Shifeng, Yu Kunyi

“…Compared with the traditional U-Net and FCN networks, the accuracy rate is increased by 0.32% and 1.17% respectively, and the algorithm consumes 0.054 s. Compared with the comparison, the segmentation algorithm improves by 0.006 s~0.013 s; Then the split defect mask and the original image are operated. …”
Get full text

Research on Flexible Material Identification and Positioning Based on Machine Vision by Xiaowei Zhou, Qingmei Pan, Dingyuan Jiang, Jiazang Zhang

“…Based on the positioning information, the cutter head position is initialized, establishing the correspondence between the physical coordinates of the robot and the pixel coordinates of the data image. Traditional shape-based template matching algorithms are prone to local optima and overall shifts when dealing with size scaling and deformation of flexible materials, resulting in decreased positioning accuracy. …”
Get full text

Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation by S. Rashmi, S. Srinath, R. Rakshitha, B. V. Poornima

“…The methodology is strategically designed to address the complexities and variations in cephalometric images through a dual learning process: building base learners using end-to-end regression approaches and then constructing a meta-learner that ensembles the output of the base models to obtain collective predictions. …”
Get full text

Myocarditis Detection Using Proximal Policy Optimization and Mutual Learning by Asadi Srinivasulu, Sivaram Rajeyyagari

“…The model employs multiple convolutional neural networks (CNNs) to extract feature vectors from images for classification. To address class imbalance, a proximal policy optimization (PPO)-based algorithm is utilized, significantly improving the training process by preventing abrupt policy shifts and stabilizing them. …”
Get full text

High-efficiency sparse convolution operator for event-based cameras by Sen Zhang, Fusheng Zha, Fusheng Zha, Xiangji Wang, Mantian Li, Wei Guo, Pengfei Wang, Xiaolin Li, Lining Sun

“…However, despite their inherent sparsity, most existing visual processing algorithms are optimized for conventional standard cameras and dense images captured from them, resulting in computational redundancy and high latency when applied to event-based cameras. …”
Get full text

Intelligent Manufacturing in Wine Barrel Production: Deep Learning-Based Wood Stave Classification by Frank A. Ricardo, Martxel Eizaguirre, Desmond K. Moru, Diego Borro

“…Several techniques using classical image processing and deep learning have been developed to detect tree-ring boundaries, but they often struggle with woods exhibiting heterogeneity and texture irregularities. (2) Methods: This study proposes a hybrid approach combining classical computer vision techniques for preprocessing with deep learning algorithms for classification, designed for continuous automated processing. …”
Get full text

Automating areas of interest analysis in mobile eye tracking experiments based on machine learning by Julian Wolf, Stephan Hess, David Bachmann, Quentin Lohmeyer, Mirko Meboldt

“…Using only 72 training images with 264 labelled object representations, cGOM is able to reach a TPR of approx. 80% and a TNR of 85% compared to the manual mapping. …”
Get full text

Development and observation of a three-dimensional scanning coaxial Mie lidar for dynamic monitoring of near-surface aerosol plumes by QingWei Li, Yu Xin, ChunSheng Chen, YiNing Li, Yun Jiang, WeiWei Song

“…In this study, a 3D scanning coaxial Mie lidar (3D-STML) was developed to achieve a fast three-dimensional scanning observation of aerosol diffusion processes in near-surface areas. 3D-STML generates high-spatiotemporal resolution images of aerosol extinction coefficient in real-time and captures the dynamic changes of aerosols in near real-time. …”
Get full text