Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…Automated video anomaly detection (VAD) is a challenging task due to its context-dependent and sporadic nature. …”
Get full text

A Comprehensive Study On Underwater Object Detection Using Deep Neural Networks by K. Samanth, Ramyashree Ramyashree, B. N. Anoop, S. Raghavendra

“…Identifying and removing submerged debris is challenging due to poor visibility, complex water conditions, and the inefficiency of traditional manual approaches. …”
Get full text

Classifying IoT Botnet Attacks With Kolmogorov-Arnold Networks: A Comparative Analysis of Architectural Variations by Phuc Hao do, Tran Duc Le, Truong Duy Dinh, van Dai Pham

“…The Original-KAN variant, in particular, excelled in capturing complex, non-linear patterns inherent in IoT botnet traffic, achieving higher accuracy and faster convergence rates. …”
Get full text

Sustainability in pharmaceutical analysis: greenness assessment of HPLC methods for paclitaxel by Ruchita Rajput, Sonal Desai

“…Abstract Sustainability in pharmaceutical analysis is gaining significant attention, driven by global initiatives to reduce environmental impact and enhance operational efficiency. This study evaluates the greenness of HPLC-based methods for paclitaxel quantification using seven assessment tools: NEMI, Complex NEMI, Analytical Eco-Scale, SPMS, ChlorTox, RGBfast, and BAGI. …”
Get full text

FSDN-DETR: Enhancing Fuzzy Systems Adapter with DeNoising Anchor Boxes for Transfer Learning in Small Object Detection by Zhijie Li, Jiahui Zhang, Yingjie Zhang, Dawei Yan, Xing Zhang, Marcin Woźniak, Wei Dong

“…This approach achieves a balance between computational efficiency for medium-resolution images and the accuracy required for small object detection. …”
Get full text

An Enhanced and Lightweight YOLOv8-Based Model for Accurate Rice Pest Detection by Guisuo Liu, Juxing Di, Qing Wang, Yan Zhao, Yang Yang

“…The results validate that the proposed model is not only effective and efficient but also robust and lightweight, making it a promising solution for rice pest detection and offering valuable support for pest management in precision agriculture.…”
Get full text

A Secure and Robust Machine Learning Model for Intrusion Detection in Internet of Vehicles by Pradeep Kumar Tiwari, Shiv Prakash, Animesh Tripathi, Tiansheng Yang, Rajkumar Singh Rathore, Manish Aggarwal, Narendra Kumar Shukla

“…In this paper, we proposed a fine tree-based model to study the complex behavior of network traffic inside the IoV to detect and classify anomalies for securing the IoV. …”
Get full text

Dynamic response and discrimination of gaseous sarin using a boron‐difluoride complex film‐based fluorescence sensor by Zhijie Zhou, Lei Zhang, Lingya Peng, Yingjie Li, Xiaolin Zhu, Yidi Wu, Zebiao Qiu, Gang He, Molin Qin, Haonan Peng, Yu Fang

“…Abstract This study presents a novel boron‐difluoride complex‐based fluorescent nanofilm sensor capable of detecting sarin vapors in the environment by reporting an output fluorescence signal. …”
Get full text

A small underwater object detection model with enhanced feature extraction and fusion by Tao Li, Yijin Gang, Sumin Li, Yizi Shang

“…Advancements in deep learning have led to the development of many efficient detection techniques. However, the complexity of the underwater environment, limited information available from small objects, and constrained computational resources make small object detection challenging. …”
Get full text

Lightweight Apple Leaf Disease Detection Algorithm Based on Improved YOLOv8 by LUO Youlu, PAN Yonghao, XIA Shunxing, TAO Youzhi

“…To reduce the incidence of apple diseases and increase fruit yield, developing efficient and fast apple leaf disease detection technology is of great significance. …”
Get full text

PCPE-YOLO with a lightweight dynamically reconfigurable backbone for small object detection by Weijia Chen, Jiaming Liu, Tong Liu, Yaoming Zhuang

“…Abstract In the domain of object detection, small object detection remains a pressing challenge, as existing approaches often suffer from limited accuracy, high model complexity, and difficulty meeting lightweight deployment requirements. …”
Get full text

An improved method of AUD-YOLO for surface damage detection of wind turbine blades by Li Zou, Anqi Chen, Xinhua Yang, Yibo Sun

“…Abstract The detection of wind turbine blades (WTBs) damage is crucial for improving power generation efficiency and extending the lifespan of turbines. …”
Get full text

Detection of Pear Quality Using Hyperspectral Imaging Technology and Machine Learning Analysis by Zishen Zhang, Hong Cheng, Meiyu Chen, Lixin Zhang, Yudou Cheng, Wenjuan Geng, Junfeng Guan

“…In summary, the combination of HSI and machine learning models enabled an efficient, rapid, and non-destructive detection of pear quality and provided a practical value for quality control and the commercial processing of pears.…”
Get full text

HGLFNet: Hybrid Global Semantic and Local Detail Feature Network for Lane Detection by Lei Ding, Chunhui Tang, Yi Fang

“…The experimental results comprehensively demonstrate that HGLFNet surpasses the existing state-of-the-art techniques in both accuracy and efficiency, providing a novel and effective solution for lane detection in complex scenarios and showing significant potential in practical applications.…”
Get full text

YOLO-MES: An Effective Lightweight Underwater Garbage Detection Scheme for Marine Ecosystems by Chengxu Huang, Wenyuan Zhang, Beitian Zheng, Jiahao Li, Bochen Xie, Ruisi Nan, Zongming Tan, Baohua Tan, Neal N. Xiong

“…Experimental results indicate that YOLO-MES achieves 95.8% accuracy on the dataset, while reducing model size and computational complexity by 64% and 67%, respectively. Compared to existing mainstream detection algorithms, YOLO-MES offers significant advantages in lightweight design and computational efficiency, providing a practical and deployable solution for underwater target detection on mobile devices.…”
Get full text

Effects of Ageing and Sex on Complexity in the Human Sleep EEG: A Comparison of Three Symbolic Dynamic Analysis Methods by Pinar Deniz Tosun, Derk-Jan Dijk, Raphaelle Winsky-Sommerer, Daniel Abasolo

“…All three SDA techniques distinguished the vigilance states (i.e., wakefulness, REM sleep, NREM sleep, and its sub-stages: stage 1, stage 2, and slow wave sleep). Complexity of the sleep EEG increased with ageing. Sex on the other hand did not affect the complexity values assessed with any of these three SDA methods, even though FFT detected sex differences. …”
Get full text

Experimental Demonstration of 16-QAM DD-SEFDM With Cascaded BPSK Iterative Detection by Jun Huang, Qi Sui, Zhaohui Li, Fei Ji

“…To simplify the complexity of a spectrally efficient frequency-division multiplexing (SEFDM) system, cascaded binary-phase-shift-keying iterative detection (CBID) is proposed for square <inline-formula> <tex-math notation="LaTeX">$M$</tex-math></inline-formula>-ary quadrature-amplitude-modulation (M-QAM) SEFDM as the first decoding stage, in conjunction with a fixed sphere decoder (FSD). …”
Get full text

Enhanced anomaly traffic detection framework using BiGAN and contrastive learning by Haoran Yu, Wenchuan Yang, Baojiang Cui, Runqi Sui, Xuedong Wu

“…However, existing methods face many challenges when processing complex high-dimensional traffic data. Especially in dealing with redundant features, data sparsity and nonlinear features, traditional methods often suffer from high computational complexity and low detection efficiency. …”
Get full text

An Anomaly Detection Method for Industrial System Cybersecurity Based on GGL-WAVE-CNN by Bing Zou, Ke jun Zhang, Xin Ying Yu, Yu han Jin, Jun Wang, Ling yu Liu

“…Current approaches often struggle to handle complex, unknown topological time series data, thereby necessitating improved anomaly detection accuracy. …”
Get full text

Self-Supervised Drift-Resilient Classification for Time Series Industrial Anomaly Detection by Myung-Kyo Seo, Byeong Hoon Yoon, Junseung Ryu, Hyung Ju Hwang

“…In modern industrial environments, early detection of anomalies is essential to prevent unplanned downtime and maintain operational efficiency. …”
Get full text