Grid self-attention mechanism 3D object detection method based on raw point cloud by Bin LU, Yang SUN, Zhenyu YANG

“…To enhance the feature representation of region of interest (RoI), which incorporated a spatial context encoding module and soft regression loss, a grid self-attention mechanism 3D object detection method based on raw point cloud, named GT3D, was proposed.The spatial context encoding module was designed to effectively weight the local and spatial features of points through the attention mechanism, considering the contribution of different point cloud features for a more accurate feature representation.The soft regression loss was introduced to address label ambiguity arising during the data annotation phase.Experiments conducted on the public KITTI 3D object detection dataset demonstrate that the proposed method achieves significant improvements in detection accuracy compared to other publicly available point cloud-based 3D object detection methods.The detection results of the test set are submitted to the official KITTI server for public evaluation, achieving detection accuracies of 91.45%, 82.76%, and 79.74% for easy, moderate, and hard difficulty levels in car detection, respectively.…”
Get full text

Machine learning-based identification of proteomic markers in colorectal cancer using UK Biobank data by Swarnima Kollampallath Radhakrishnan, Dipanwita Nath, Dominic Russ, Dominic Russ, Dominic Russ, Laura Bravo Merodio, Laura Bravo Merodio, Laura Bravo Merodio, Priyani Lad, Folakemi Kola Daisi, Animesh Acharjee, Animesh Acharjee, Animesh Acharjee

Get full text

Breast Cancer Detection Analysis Using Different Machine Learning Techniques: South Iraq Case Study by Salma Abdulbaki Mahmood, Myssar Jabbar Hammood Al-Battbootti, Saad Shaheen Hamadi, Iuliana Marin, Costin-Anton Boiangiu, Nicolae Goga

Get full text

Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens by Paul English, Muir J. Morrison, Blaine Mathison, Elizabeth Enrico, Ryan Shean, Brendan O'Fallon, Deven Rupp, Katie Knight, Alexandra Rangel, Jeffrey Gilivary, Amanda Vance, Haleina Hatch, Leo Lin, David P. Ng, Salika M. Shakir

“…Although performance of our model was not sufficient to be clinically implemented in our laboratory, our study provides a framework for AI-based AFB detection and a publicly available data set to support future advancements in automated detection of AFB.IMPORTANCEWe present the development of an artificial intelligence model to detect acid-fast bacilli (AFB) directly from stained clinical smears. …”
Get full text

Fusing wrist pulse and ECG data for enhanced identification of coronary heart disease and its complications by Lei-Xin Hong, Wen-Jie Wu, Xia Chen, Dan-Qun Xiong, Ye-Qing Zhang, Xiang-Dong Xu, Jian-Jun Yan, Rui Guo

Get full text

Mixed image detection method of belt coal blockage and leakage based on improved RetinaNet mode by Qingjun Fu, Xiang Liu, Yinqiang Yan, Zhibin Guo

“…An improved RetinaNet model is used to train the labeled three-dimensional image data set, and features are extracted and fused through attention mechanism and feature pyramid to detect coal blockage and coal leakage, and it is deployed in production environment to realize real-time monitoring. …”
Get full text

Detection and classification of hypertensive retinopathy based on retinal image analysis using a deep learning approach by Bambang Krismono Triwijoyo, Ahmat Adil, Muhammad Zulfikri

“…Methods: This research utilizes secondary data, specifically a retinal image dataset from the open-source Messidor database. …”
Get full text

Exploring Bioimage Synthesis and Detection via Generative Adversarial Networks: A Multi-Faceted Case Study by Valeria Sorgente, Dante Biagiucci, Mario Cesarelli, Luca Brunese, Antonella Santone, Fabio Martinelli, Francesco Mercaldo

“…Method: We propose a two-step method aimed to detect whether a bioimage can be considered fake or real. …”
Get full text

Model-Based Fault Detection and Isolation of a Liquid-Cooled Frequency Converter on a Wind Turbine by Peng Li, Peter Fogh Odgaard, Jakob Stoustrup, Alexander Larsen, Kim Mørk

“…The designed fault detection and isolation algorithm is applied on a set of measured experiment data in which different faults are artificially introduced to the scaled cooling system. …”
Get full text

Machine Learning Applied to Reference Signal-Less Detection of Motion Artifacts in Photoplethysmographic Signals: A Review by Erick Javier Argüello-Prada, Javier Ferney Castillo García

“…Machine learning algorithms have brought remarkable advancements in detecting motion artifacts (MAs) from the photoplethysmogram (PPG) with no measured or synthetic reference data. …”
Get full text

A cross dataset meta-model for hepatitis C detection using multi-dimensional pre-clustering by Aryan Sharma, Tanmay Khade, Shashank Mouli Satapathy

Get full text

Enhancing ECG disease detection accuracy through deep learning models and P-QRS-T waveform features. by Rida Nayyab, Asim Waris, Iqra Zaheer, Muhammad Jawad Khan, Fawwaz Hazzazi, Muhammad Adeel Ijaz, Hassan Ashraf, Syed Omer Gilani

“…The R-peaks of the clean signal were used to detect the subsequent morphological features, i.e., P-QRS-T intervals and amplitudes. …”
Get full text

Novel Deep Learning Model for Glaucoma Detection Using Fusion of Fundus and Optical Coherence Tomography Images by Saad Islam, Ravinesh C. Deo, Prabal Datta Barua, Jeffrey Soar, U. Rajendra Acharya

“…In addition to a fixed test set evaluation, we perform five-fold cross-validation, confirming the robustness and consistency of the fusion model across multiple data partitions. …”
Get full text

Detection of arterial remodeling using epicardial adipose tissue assessment from CT calcium scoring scan by Juhwan Lee, Tao Hu, Michelle C. Williams, Ammar Hoori, Hao Wu, Justin N. Kim, David E. Newby, Robert Gilkeson, Robert Gilkeson, Sanjay Rajagopalan, David L. Wilson, David L. Wilson

Get full text

A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images by Mishmala Sushith, A. Sathiya, V. Kalaipoonguzhali, V. Sathya

“…These enriched spatial features are then fed into an RNN with attention mechanism to capture temporal dependencies so that most relevant data aspects can be considered for analysis. This combined approach enables the model to consider both current and previous states of the retina, improving its ability to detect subtle changes indicative of early-stage DR. …”
Get full text

Improved cohesin HiChIP protocol and bioinformatic analysis for robust detection of chromatin loops and stripes by Karolina Buka, Zofia Parteka-Tojek, Abhishek Agarwal, Michał Denkiewicz, Sevastianos Korsak, Mateusz Chiliński, Krzysztof H. Banecki, Dariusz Plewczynski

“…Additionally, we propose an automated pipeline called nf-HiChIP ( https://github.com/SFGLab/hichip-nf-pipeline ) for processing HiChIP samples starting from raw sequencing reads data and ending with a set of significant chromatin interactions (loops), which allows efficient and timely analysis of multiple samples in parallel, without requiring additional ChIP-seq experiments. …”
Get full text

Time Frequency Analysis Based Fault Detection in PV Array Using Scaling Basis Chirplet Transform by S Ramana Kumar Joga, Chidurala SaiPrakash, Srikanth Velpula, Alivarani Mohapatra, Theophilus A. T. Kambo Jr.

“…In this proposed fault detection method, PV array signal is decomposed into a set of chirplets using the SBCT. …”
Get full text

Pragmatic questionnaire-based evaluation of auditory function in individuals with major neurocognitive disorders and hearing loss in diverse contexts by Panagiotis Alexopoulos, Panagiotis Alexopoulos, Panagiotis Alexopoulos, Panagiotis Alexopoulos, Antonios Alexandros Demertzis, Panagiotis Biris, Polychronis Economou, Eric Frison, Piers Dawes, Iracema Leroi

“…BackgroundHearing impairment in older people is a significant risk factor for cognitive decline and dementia, while it is a source of bias in the diagnostic workup of cognitive complaints. Early detection and intervention are critical, yet audiometric equipment is often unavailable in primary healthcare- and/or community care-, as well as in low-resource settings across the globe.ObjectiveThis study aims (i) to develop brief accurate instruments for capturing hearing loss severity based on items of the 25-item Hearing Handicap Inventory for the Elderly (HHIE) and its counterpart the Hearing Handicap Inventory for the communication partner (HHIE-SP) and (ii) to compare their usefulness as well as that of the 10-item screening version of HHIE (HHIE-S) in detecting hearing loss severity in people with dementia and hearing loss to HHIE and HHIE-SP.MethodsThe study relies on screening- and baseline data of the Sense-Cog Trial, being a European, multi-center, observer-blind, 36-week long, randomized controlled trial (RCT) of people with dementia with sensory impairment and their companions. …”
Get full text

Applying transfer learning in CNN model architectures for detecting tomato leaf disease with explainable artificial intelligence by Alexander Takele Mengesha, Melaku Alelign Mengistie

Get full text

Collaborative Static-Dynamic Teaching: A Semi-Supervised Framework for Stripe-like Space Target Detection by Zijian Zhu, Ali Zia, Xuesong Li, Bingbing Dan, Yuebo Ma, Hongfeng Long, Kaili Lu, Enhai Liu, Rujin Zhao

“…Using just 1/16 of the labeled data, CSDT outperforms the second-best Interactive Self-Training Mean Teacher (ISMT) method by 2.64% in mean Intersection over Union (mIoU) and 4.5% in detection rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>P</mi><mi>d</mi></msub></semantics></math></inline-formula>), while exhibiting strong generalization in unseen scenarios. …”
Get full text