A Novel Dataset for Polyp Segmentation and Detection Using a Vision-Language Model by Mahdiyeh Alilou, Javad Mozaffari, Abdollah Amirkhani, Shahriar B. Shokouhi, Alireza Khafaf

“…Colorectal Cancer (CRC) is caused by malignant polyps that develop on the colon walls, and early detection is crucial for prevention. Colonoscopy is one of the most effective methods for the detection of polyps, and deep learning algorithms can be utilized for colonoscopy image processing. …”
Get full text

HAF-YOLO: Dynamic Feature Aggregation Network for Object Detection in Remote-Sensing Images by Pengfei Zhang, Jian Liu, Jianqiang Zhang, Yiping Liu, Jiahao Shi

“…The growing use of remote-sensing technologies has placed greater demands on object-detection algorithms, which still face challenges. …”
Get full text

Single-element ultrasound system for high-resolution jugular venous pulse contour detection by Navya Rose George, P. M. Nabeel, Kiran V. Raj, Rahul Manoj, Mohanasankar Sivaprakasam, Jayaraj Joseph

“…Conventional ultrasound imaging systems can reliably measure jugular venous vessel dynamics but are hindered by low operational frame rates, large form factors, and the requirement for trained operators. …”
Get full text

Improved YOLOv8s-based foreign object detection method for mine conveyor belts by LI Runze, GUO Xingge, YANG Fazhan, ZHAO Peipei, XIE Guolong

“…In low-illumination mine environments, conveyor belt foreign object detection algorithms suffer from insufficient extraction of global image features and an excessive number of model parameters. …”
Get full text

A novel feature extractor based on constrained cross network for detecting sleep state by Chenlei Tian, Fei Song

“…Most existing methods that utilize wrist-worn devices data for detection rely on heuristic algorithms or traditional machine learning, which suffer from low classification efficiency and insufficient accuracy. …”
Get full text

AI-powered IoT and UAV systems for real-time detection and prevention of illegal logging by Montaser N.A. Ramadan, Mohammed A.H. Ali, Shin Yee Khoo, Mohammad Alkhedher

“…This paper introduces a novel Unmanned Aerial Vehicles (UAV)-based IoT system for chainsaw noise detection and prevention. The system uses low-cost IoT nodes with microphones and microcontrollers to detect chainsaw sounds via a Convolutional Neural Network (CNN) model. …”
Get full text

Swincloud: a hybrid network for cloud detection in thermal infrared remote sensing images by Long Gao, Liyuan Li, Jianing Yu, Xiaoxuan Zhou, Lu Zou, Nan Fang, Xiaofeng Su, Fansheng Chen

“…Convolutional neural networks have shown outstanding performance in previous cloud detection algorithms due to their robust ability to extract local information. …”
Get full text

A Self-Supervised Feature Point Detection Method for ISAR Images of Space Targets by Shengteng Jiang, Xiaoyuan Ren, Canyu Wang, Libing Jiang, Zhuang Wang

“…Traditional feature point detection methods perform poorly when confronted with the low texture and uneven brightness characteristics of ISAR images. …”
Get full text

Understanding the Influence of Image Enhancement on Underwater Object Detection: A Quantitative and Qualitative Study by Ashraf Saleem, Ali Awad, Sidike Paheding, Evan Lucas, Timothy C. Havens, Peter C. Esselman

“…We also find that over-enhancement may lead to deteriorated object detection performance. Lastly, we note that enhanced images reveal hidden objects that were not annotated due to the low visibility of the original images.…”
Get full text

FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…RGB-IR object detection provides a promising solution for complex scenarios, such as remote sensing and low-light environments, by leveraging the complementary strengths of visible and infrared modalities. …”
Get full text

AAMS-YOLO: enhanced farmland parcel detection for high-resolution remote sensing images by Binyao Wang, Ya’nan Zhou, Weiwei Zhu, Li Feng, Jinke He, Tianjun Wu, Jiancheng Luo, Xin Zhang

“…Extensive experiments on a custom-built dataset validate AAMS-YOLO's effectiveness, demonstrating notable enhancements over the baseline in mAP0.5 (2.6%) and mAP0.5:0.95 (2.2%) and surpassing other state-of-the-art algorithms. The proposed model excels in detecting small and densely overlapping objects through advanced feature fusion and multi-scale processing strategies.…”
Get full text

A Precise Detection Method for Tomato Fruit Ripeness and Picking Points in Complex Environments by Xinfa Wang, Xuan Wen, Yi Li, Chenfan Du, Duokuo Zhang, Chengxiu Sun, Bihua Chen

“…Aiming at the problems faced in practical applications, such as low accuracy of tomato ripeness and picking points detection in complex greenhouse environments, which leads to wrong picking, missed picking, and fruit damage by robots, this study proposes the YOLO-TMPPD (Tomato Maturity and Picking Point Detection) model. …”
Get full text

Diagnostic accuracy of artificial intelligence for obstructive sleep apnea detection: a systematic review by Sara Haghighat, Muhammed Joghatayi, Julien Issa, Sarina Azimian, Janet Brinz, Ali Ashkan, Akhilanand Chaurasia, Zahra Rahimian, Linda Sangalli

“…Artificial intelligence (AI) algorithms can facilitate diagnosis by detecting patients’ signs and symptoms. …”
Get full text

Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…Pavement distress is one of the most serious and prevalent diseases in pavement road detection. However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. …”
Get full text

Ultra-Low Dose Computed Tomography Imaging in Quantifying Bone Trauma and Disorders: A Cross-Sectional Study by Fariba Zarei, Seyedeh Marzieh Ahmadi, Saber Dehbani-Zadeh, Anahita Jafari, Vyas Akondi, Sabyasachi Chatterjee, Seyed Alireza Mirhosseini, Rezvan Ravanfar Haghighi

“…This study aims to assess the effectiveness of ultra-low-dose CT (ULD-CT) imaging, reconstructed using an Iterative Reconstruction (IR) algorithm, in detecting bone trauma and disorders.Methods: In the present cross-sectional study, 71 patients with CT requests for spine or extremity (limb) bone underwent scanning using standard dose (SD) and ULD-CT protocols, in Shahid Faghihi Hospital, Shiraz, Iran from June 2019 to June 2020. …”
Get full text

Context guided transformer enhanced YOLOv8 for accurate juvenile abalone detection and counting by Dapeng Cheng, Ji Ruan, Xinhao Li, Feng Zhao, Shoudu Zhang, Guofan Zhang, Fucun Wu

“…However, due to the small size, dense distribution, and frequent occlusion among individuals during the rearing period, existing detection algorithms often demonstrate low precision in identifying abalones. …”
Get full text

RST-YOLOv8: An Improved Chip Surface Defect Detection Model Based on YOLOv8 by Wenjie Tang, Yangjun Deng, Xu Luo

“…We propose an enhanced chip surface defect detection algorithm based on an improved version of YOLOv8, termed RST-YOLOv8. …”
Get full text

GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…To address the current challenges in fire detection algorithms, including insufficient feature extraction, high computational complexity, limited deployment on resource-constrained devices, missed detections, false detections, and low accuracy, we developed a high-precision algorithm named GSF-YOLOv8. …”
Get full text

Cell‐free epigenomes enhanced fragmentomics‐based model for early detection of lung cancer by Yadong Wang, Qiang Guo, Zhicheng Huang, Liyang Song, Fei Zhao, Tiantian Gu, Zhe Feng, Haibo Wang, Bowen Li, Daoyun Wang, Bin Zhou, Chao Guo, Yuan Xu, Yang Song, Zhibo Zheng, Zhongxing Bing, Haochen Li, Xiaoqing Yu, Ka Luk Fung, Heqing Xu, Jianhong Shi, Meng Chen, Shuai Hong, Haoxuan Jin, Shiyuan Tong, Sibo Zhu, Chen Zhu, Jinlei Song, Jing Liu, Shanqing Li, Hefei Li, Xueguang Sun, Naixin Liang

“…Plasma cfDNA was analysed for its epigenetic and fragmentomic profiles using chromatin immunoprecipitation sequencing, reduced representation bisulphite sequencing and low‐pass whole‐genome sequencing. Machine learning algorithms were then employed to integrate the multi‐omics data, aiding in the development of a precise lung cancer detection model. …”
Get full text

Decoding basic emotional states through integration of an fNIRS-based brain-computer interface with supervised learning algorithms. by Ayşenur Eser, Sinem Burcu Erdoğan

“…The high-performance classification results highlight the potential of fNIRS-based BCI systems for real-time, objective detection of basic emotional states for daily life and clinical applications. fNIRSbased BCIs may show promise for future developments in personalized user experiences and clinical applications due to their practicality and low computational complexity.…”
Get full text