Toward AI-Enabled Approach for Urdu Text Recognition: A Legacy for Urdu Image Apprehension by Kamlesh Narwani, Hongzhi Lin, Sandeep Pirbhulal, Mir Hassan

“…To further evaluate the performance of these models, we have used the most popular evaluation matrices of precision, recall, and F-measure. …”
Get full text

Sentence type identification-based product review sentiment analysis using BeDi-DC and Log-Squish CNN by Neetesh Kumar Nema, Vivek Shukla, Rohit Miri, Praveen Chouksey, Rohit Raja, Kamred Udham Singh, Ankit Kumar, Mohd Asif Shah

“…The customer’s perception of the product is reviewed by analysing the sentiment of product reviews, thus assisting in business decision-making. In most of the prevailing works, the sentence type of product review was not recognised to analyse the sentiment; thus, the complexity of the sentiment analysis process increased. …”
Get full text

Enhancing prostate cancer segmentation in bpMRI: Integrating zonal awareness into attention-guided U-Net by Chao Wei, Zheng Liu, Yibo Zhang, Lianhui Fan

“…Purpose Prostate cancer (PCa) is the second most common cancer in males worldwide, requiring improvements in diagnostic imaging to identify and treat it at an early stage. …”
Get full text

Improving Cerebrovascular Imaging with Deep Learning: Semantic Segmentation for Time-of-Flight Magnetic Resonance Angiography Maximum Intensity Projection Image Enhancement by Tomonari Yamada, Takaaki Yoshimura, Shota Ichikawa, Hiroyuki Sugimori

“…While the model effectively removed most external carotid structures, further refinement is needed to improve venous structure suppression. …”
Get full text

Sea-Ice Surface Types Characterization and SAR Volume Backscattering Properties in Response to Sea States Interactions Using Structural Feature Fusion by Iman Heidarpour Shahrezaei, Hyun-Cheol Kim

“…Despite extensive research in polar remote sensing, there is still no consensus on how sea-ice evolves in response to interactions with ocean waves, nor is there agreement on the most effective way to characterize it based on fluctuations in height profile, both of which compromise interpretations of its texture properties when observed by synthetic aperture radar (SAR). …”
Get full text

A Review for the Driving Behavior Recognition Methods Based on Vehicle Multisensor Information by Dengfeng Zhao, Yudong Zhong, Zhijun Fu, Junjian Hou, Mingyuan Zhao

“…The frequent traffic accidents lead to a large number of casualties and large related financial losses every year; this serious state is owed to several factors; among those, driving behavior is one of the most imperative subjects to discuss. Driving behaviors mainly include behavior characteristics such as car-following, lane change, and risky driving behavior such as distraction, fatigue, or aggressive driving, which are of great help to various tasks in traffic engineering. …”
Get full text

Technical note: Impact of tissue section thickness on accuracy of cell classification with a deep learning network by Ida Skovgaard Christiansen, Rasmus Hartvig, Thomas Hartvig Lindkær Jensen

“…Random forest analysis generally identified variations in nuclear granularity as the most important features in distinguishing cells. …”
Get full text

Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids by Yanfei Li, Juejing Liu, Xiaodong Zhao, Wenjun Liu, Tong Geng, Ang Li, Xin Zhang

“…Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieve close performance to models analyzing preprocessed data, with minimal accuracy differences. …”
Get full text

Symbol Detection and Channel Estimation for Space Optical Communications Using Neural Network and Autoencoder by Abdelrahman Elfikky, Zouheir Rezki

“…Additionally, with no fading and for both perfect and imperfect CSI with different code rates and fading channels, the proposed AE-based detection outperforms both benchmark learning frameworks and most popular convolutional codes.…”
Get full text

Study on Quality Assessment Methods for Enhanced Resolution Graph-Based Reconstructed Images in 3D Capacitance Tomography by Robert Banasiak, Mateusz Bujnowicz, Anna Fabijańska

“…Finally, we present our conclusions regarding the effectiveness of the proposed GQA methods, and we identify the most promising approach for assessing the quality of graph-based ECT images.…”
Get full text

Analysis of different IDS-based machine learning models for secure data transmission in IoT networks by Gladić Dejana, Petrovački Jelena, Sladojević Srdan, Arsenović Marko, Ristić Sonja

“…Based on the results of the experiment, the most effective model and preprocessing technique were proposed.…”
Get full text

Optimal Feature Selection and Classification for Parkinson’s Disease Using Deep Learning and Dynamic Bag of Features Optimization by Aarti, Swathi Gowroju, Mst Ismat Ara Begum, A. S. M. Sanwar Hosen

“…Our method combines neural network-based feature extraction with a strong optimization technique to dynamically choose the most relevant characteristics from biological data. …”
Get full text

Lightweight Spatial–Spectral Shift Module With Multihead MambaOut for Hyperspectral Image Classification by Yi Liu, Yanjun Zhang, Yu Guo, Yunchao Li

“…Two-dimensional CNNs fail to effec-tively extract spatial and spectral information, and deploying three-dimensional CNNs on microprocessors is challenging as these net-works consume excessive resources. If graph convolutional networks (GCN) are adopted, most networks employ superpixel segmentation for HSI classification. …”
Get full text

Road Damage Detection Using YOLOv7 with Cluster Weighted Distance-IoU NMS by Rudy Rachman, Nanik Suciati, Shintami Chusnul Hidayati

“…Potholes are one of the most common types of road damage. Previous research that used images as input for pothole detection used the Faster Regional Convolutional Neural Network (R-CNN) method. …”
Get full text

DS4NN: Direct training of deep spiking neural networks with single spike-based temporal coding by Maryam Mirsadeghi, Majid Shalchian, Saeed Reza Kheradpisheh

“…Here we propose DS4NN, temporal backpropagation for deep spiking neural networks with one spike per neuron. We consider a convolutional spiking neural network consisting of simple non-leaky integrate-and-fire (IF) neurons, and a form of coding named time-to-first-spike temporal coding in which, neurons are allowed to fire at most once in a specific time interval, which corresponds to simulation duration here. …”
Get full text

LFEN: A language feature enhanced network for scene text recognition by Hui Chen, Runming Jiang, Fang Hu, Min Chen, Yin Zhang

“…Compared to the baselines, the experimental results demonstrate that LFEN achieves superior performance in most evaluation metrics. Specifically, LFEN has around 2% in recall improved to BERT. …”
Get full text

Machine Learning-Potato Leaf Disease Detection App (MR-PoLoD) by Ahmad Fauzi, Annisya E Chandra, Sofyah Imammah, Malvin Zapata, Marza I Marzuki, Soni Prayogi

“…This application uses the CNN (Convolutional Neural Network) Machine Learning Algorithm because currently, CNN is recognized as the most efficient and effective model in pattern and image recognition tasks. …”
Get full text

Short-term Power Load Forecasting for a 33/11 KV Sub-Station by Utilizing Attention-Based Hybrid Deep Learning Architectures by Mukkamala R.

“…The performance of these models measured using several key metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R²). The most important result is that the CNN-BiLSTM attention model significantly outperforms the other models, achiev-ing an MSE of 0.0079, an RMSE of 0.0889, and an R² value of 0.8547. that underscores that the CNN-BiLSTM attention model represents an effective and practical tool for accurate power load forecasting. …”
Get full text

Deep learning based rapid X-ray fluorescence signal extraction and image reconstruction for preclinical benchtop X-ray fluorescence computed tomography applications by Amrit Kaphle, Sandun Jayarathna, Sang Hyun Cho

“…For routine in vivo benchtop XFCT imaging, however, additional challenges, most notably the need for rapid/near-real-time handling of X-ray fluorescence (XRF) signal extraction and XFCT image reconstruction, must be successfully addressed. …”
Get full text

How to detect occluded crosswalks in overview images? Comparing three methods in a heavily occluded area by Yuanyuan Zhang, Joseph Luttrell, IV, Chaoyang Zhang

“…The results showed that the AVM suffered the most when dealing with images from a heavily occluded area, resulting in the lowest accuracy, precision, recall, and F1 score among the three methods. …”
Get full text