Enhancing lung cancer detection through integrated deep learning and transformer models by Revathi Durgam, Bharathi Panduri, V. Balaji, Adil O. Khadidos, Alaa O. Khadidos, Shitharth Selvarajan

“…These are SwiNet for segmented analysis, XLG CancerNet for precise classification of the cases, and DevLO that optimizes the parameters of the lung cancer detection system, making the system more sensible and efficient. …”
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Detection and Recognition of Underwater Acoustic Communication Signal Under Ocean Background Noise by Mengyi Li, Jilong Li, Haihong Feng

“…Non-cooperative underwater acoustic signal detection and recognition technologies occupy an important position in the marine communication environment. …”
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Empowering Quality of Recommendations by Integrating Matrix Factorization Approaches With Louvain Community Detection by Srilatha Tokala, Murali Krishna Enduri, T. Jaya Lakshmi, Ashu Abdul, Jenhui Chen

“…The efficient functioning of the recommendation system undergoes the scalability challenge in controlling large and varying datasets. …”
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Partial feature reparameterization and shallow-level interaction for remote sensing object detection by Minh Tai Pham Nguyen, Quoc Duy Nam Nguyen, Hoang Viet Anh Le, Minh Khue Phan Tran, Tadashi Nakano, Thi Hong Tran

“…Abstract Remote sensing object detection has recently emerged as one of the challenging topics in the field of deep learning applications due to the demand for both high detection performance and computational efficiency. …”
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Novel Wavelet Convolutional Neural Networks for Signal Detection in OFDM-IM Systems by Yang Zhao, SI-YU Zhang, Yuexia Zhang, Gongpu Wang, Behnam Shahrrava

“…However, CNNs' limited receptive field growth poses a challenge in capturing long range dependencies. To achieve efficient deep learning based OFDM-IM detection, this paper proposes two novel OFDM-IM signal detection networks that integrate wavelet transforms with CNNs (WTConv). …”
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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. …”
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Fault Detection in Gearboxes Using Fisher Criterion and Adaptive Neuro-Fuzzy Inference by Houssem Habbouche, Tarak Benkedjouh, Yassine Amirat, Mohamed Benbouzid

“…Consequently, deploying expert methods for fault detection and diagnosis is crucial to ensuring the reliability and efficiency of these systems. …”
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Research on downhole drilling target detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…To monitor the drilling process in real time and enhance the efficiency of target detection at underground coal mine drill sites, an improved algorithm based on Yolov8n has been proposed, which offers advantages compared with the traditional detection methods. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…The unique characteristics of 5G networks, while enabling advanced communication, present challenges in distinguishing between legitimate and malicious traffic, making it more difficult to detect anonymous traffic. Current methodologies for intrusion detection within 5G communication exhibit limitations in accuracy, efficiency, and adaptability to evolving network conditions. …”
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Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…It has two primary types: one-stage detectors known for their high speed and efficiency, and two-stage detectors, which offer higher accuracy but are often slower due to their complex architecture. …”
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Blockage detection in pipelines based on linear frequency modulated acoustic reflection method by Haiyuan Yao, Dan Li, Yan Li, Bo Yang, Yang Meng

“…This study proposes a novel acoustic-based structural health monitoring system integrating linear frequency modulated (LFM) signals with adaptive matched filtering, specifically designed for early blockage detection in complex pipeline networks, including those in built environments. …”
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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. …”
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LiDAR-Based Detection of Urban Trees Using a Backpack System by M. F. da Silva, L. F. Castanheiro, A. M. G. Tommaselli, A. M. G. Tommaselli, R. C. dos Santos, R. C. dos Santos, M. Galo, M. Galo

“…The sensor’s effective range is up to 50 m (at 80% reflectivity), enabling the acquisition of high-density point clouds at close-range distances while maintaining efficiency and accessibility in complex urban environments. …”
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AFHNet: Attention-Free Hybrid Network for Salient Object Detection in Underwater Images by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…However, traditional machine vision and deep learning approaches face notable challenges in complex underwater environments due to issues such as light attenuation, scattering, motion blur, color distortion, noise, low contrast, and multipath effects, which severely affect detection accuracy. …”
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RT-DETR-Smoke: A Real-Time Transformer for Forest Smoke Detection by Zhong Wang, Lanfang Lei, Tong Li, Xian Zu, Peibei Shi

“…Unlike generic object detection, smoke detection faces unique challenges due to smoke’s semitransparent, fluid nature, which often leads to false positives in complex backgrounds and missed detections—particularly around smoke edges and small targets. …”
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Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

“…Compared with existing detection methods, this approach shows outstanding performance in detection accuracy, localization precision, and computational efficiency, particularly excelling in small object detection.…”
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An Image-Free Single-Pixel Detection System for Adaptive Multi-Target Tracking by Yicheng Peng, Jianing Yang, Yuhao Feng, Shijie Yu, Fei Xing, Ting Sun

“…Conventional vision-based sensors face limitations such as low update rates, restricted applicability, and insufficient robustness in dynamic environments with complex object motions. Single-pixel tracking systems offer high efficiency and minimal data redundancy by directly acquiring target positions without full-image reconstruction. …”
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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

“…Although these technologies provide unparalleled connectivity and communication capabilities, they also introduce new security challenges, particularly in terms of Intrusion Detection. This paper presents a robust machine learning (ML) technique to enhance the security of IoV networks by developing an efficient intrusion detection system (IDS). …”
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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.…”
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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. …”
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