Zero-Shot Automated Detection of Fake News: An Innovative Approach (ZS-FND) by Rania Baashirah

“…However, these models often struggle with data dependency, overfitting, scalability, flexibility, and high computational costs. A Zero-Shot Learning (ZSL) approach is proposed for Fake News Detection (ZS-FND) to address these challenges. …”
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Explainable Siamese Neural Networks for Detection of High Fall Risk Older Adults in the Community Based on Gait Analysis by Christos Kokkotis, Kyriakos Apostolidis, Dimitrios Menychtas, Ioannis Kansizoglou, Evangeli Karampina, Maria Karageorgopoulou, Athanasios Gkrekidis, Serafeim Moustakidis, Evangelos Karakasis, Erasmia Giannakou, Maria Michalopoulou, Georgios Ch Sirakoulis, Nikolaos Aggelousis

“…Background/Objectives: Falls among the older adult population represent a significant public health concern, often leading to diminished quality of life and serious injuries that escalate healthcare costs, and they may even prove fatal. Accurate fall risk prediction is therefore crucial for implementing timely preventive measures. …”
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Automatic identification of clinically important Aspergillus species by artificial intelligence-based image recognition: proof-of-concept study by Chi-Ching Tsang, Chenyang Zhao, Yueh Liu, Ken P. K. Lin, James Y. M. Tang, Kar-On Cheng, Franklin W. N. Chow, Weiming Yao, Ka-Fai Chan, Sharon N. L. Poon, Kelly Y. C. Wong, Lianyi Zhou, Oscar T. N. Mak, Jeremy C. Y. Lee, Suhui Zhao, Antonio H. Y. Ngan, Alan K. L. Wu, Kitty S. C. Fung, Tak-Lun Que, Jade L. L. Teng, Dirk Schnieders, Siu-Ming Yiu, Susanna K. P. Lau, Patrick C. Y. Woo

“…Given its short turn-around-time, minimal demand of expertise, low reagent/equipment costs and user-friendliness, it has the potential to serve as a routine laboratory diagnostic tool after the database is further expanded.…”
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Hybrid CNN-Ensemble Framework for Intelligent Optical Fiber Fault Detection and Diagnosis by Salem Titouni, Idris Messaoudene, Yassine Himeur, Omar Alnaseri, Farouk Chetouah, Boualem Hammache, Massinissa Belazzoug, Shadi Atalla, Wathiq Mansoor

“…The results demonstrate the framework’s ability to improve fault detection performance, streamline fiber monitoring processes, reduce operational costs, and enhance network resilience to both physical attacks and accidental failures.…”
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Real-Time Interference Mitigation for Reliable Target Detection with FMCW Radar in Interference Environments by Youlong Weng, Ziang Zhang, Guangzhi Chen, Yaru Zhang, Jiabao Chen, Hongzhan Song

“…DL-based approaches typically have high computational costs, which makes them unsuitable for real-time applications with strict latency requirements and limited computing resources. …”
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Fresh or Rotten? Enhancing Rotten Fruit Detection With Deep Learning and Gaussian Filtering by Leopold Fischer-Brandies, Lucas Muller, Justus Johannes Riegger, Ricardo Buettner

“…It can thus help reduce food waste, improve food safety, and reduce costs for growers, distributors, and retailers, thereby improving the overall efficiency of the supply chain.…”
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Control-Oriented Real-Time Trajectory Planning for Heterogeneous UAV Formations by Weichen Qian, Wenjun Yi, Shusen Yuan, Jun Guan

“…Aiming at the trajectory planning problem for heterogeneous UAV formations in complex environments, a trajectory prediction model combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory networks (LSTM) is designed, and a real-time trajectory planning method is proposed based on this model. …”
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Spatiotemporal hybrid deep learning for estimating and analyzing carbon stocks: a case study in Jiangsu province, China by Lizhi Miao, Jvmin Wang, Kaiwen Wu, Heng Xu, Xiying Sun, Gang Lu, Mei-Po Kwan

“…Traditional models, reliant on extensive experimental data, are costly and impractical for large-scale applications. …”
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Cooperative Sleep and Energy-Sharing Strategy for a Heterogeneous 5G Base Station Microgrid System Integrated with Deep Learning and an Improved MOEA/D Algorithm by Ming Yan, Tuanfa Qin, Wenhao Guo, Yongle Hu

“…This underscores the need for energy-efficient networks that lower operational costs and carbon emissions, leading to a focus on microgrids powered by renewable energy. …”
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HE-BiDet: A Hardware Efficient Binary Neural Network Accelerator for Object Detection in SAR Images by Dezheng Zhang, Zehan Liang, Rui Cen, Zhihong Yan, Rui Wan, Dong Wang

“…Convolutional Neural Network (CNN)-based Synthetic Aperture Radar (SAR) target detection eliminates manual feature engineering and improves robustness but suffers from high computational costs, hindering on-satellite deployment. …”
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Accessible AI Diagnostics and Lightweight Brain Tumor Detection on Medical Edge Devices by Akmalbek Abdusalomov, Sanjar Mirzakhalilov, Sabina Umirzakova, Abror Shavkatovich Buriboev, Azizjon Meliboev, Bahodir Muminov, Heung Seok Jeon

“…Furthermore, the model significantly reduces computational costs, making real-time analysis feasible on low-power hardware. …”
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Evaluation of Peroxide Value and Free Fatty Acid Content in Coconut Oil and Palm Oil under Different Heating Temperature Treatments using Reflectance–Fluorescence-based computer vi... by Luluk Oktaviana, Wahyunanto Agung Nugroho, Dimas Firmanda Al Riza Al Riza

“…The background of this research lies in the need for a more efficient analytical method compared to conventional laboratory testing, which is often time-consuming and costly. In this study, oil samples were subjected to heating treatments at 180 and 200 °C to simulate frying conditions. …”
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EMHANet: Lightweight Salient Object Detection for Remote Sensing Images via Edge-Aware Multiscale Feature Fusion by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…Salient object detection in remote sensing images (RSI-SOD) aims to identify visually prominent objects by mimicking human visual perception. While convolutional neural networks (CNNs) have significantly improved detection accuracy, most RSI-SOD methods suffer from high computational costs and large model sizes, limiting their applicability in resource-constrained environments. …”
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Enhancing remote patient monitoring with AI-driven IoMT and cloud computing technologies by Vijay Kumar Damera, Ramesh Cheripelli, Narsaiah Putta, G. Sirisha, Deepthi Kalavala

“…The study highlights the effectiveness of AI-enhanced IoMT systems in reducing healthcare costs, improving early disease detection, and ensuring timely medical interventions. …”
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Estimating Subsurface Geostatistical Properties from GPR Reflection Data Using a Supervised Deep Learning Approach by Yu Liu, James Irving, Klaus Holliger

“…However, the associated computational costs are inherently high. To alleviate this problem, we present an alternative deep-learning-based technique, that, once trained in a supervised context, allows us to perform the same task in a highly efficient manner. …”
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Novel deep neural network architecture fusion to simultaneously predict short-term and long-term energy consumption. by Abrar Ahmed, Safdar Ali, Ali Raza, Ibrar Hussain, Ahmad Bilal, Norma Latif Fitriyani, Yeonghyeon Gu, Muhammad Syafrudin

“…However, due to the constraints and costs associated with energy generation resources, it has become crucial for both energy generation companies and consumers to predict energy consumption well in advance. …”
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The Short-Term Wind Power Forecasting by Utilizing Machine Learning and Hybrid Deep Learning Frameworks by Sunku V.S., Namboodiri V., Mukkamala R.

“…This paper addresses the rising demand for accurate short-term wind power forecasting, which is critical for minimizing the impacts on grid operations and reducing associated costs. The objective is to develop an innovative deep learning (DL) model that integrates a convolutional neural network (CNN) with a gated recurrent unit (GRU) to enhance forecasting precision for day-ahead applications. …”
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Dual-Alignment CLIP: Task-Specific Alignment of Text and Visual Features for Few-Shot Remote Sensing Scene Classification by Dongmei Deng, Ping Yao

“…Convolutional neural networks (CNNs) are widely adopted for remote sensing image scene classification. …”
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Dam Crack Instance Segmentation Algorithm Based on Improved YOLOv8 by Shuaisen Ma, Mingyue Xu, Weiwu Feng

“…It also employs Diverse Branch Block (DBB) technology to strengthen the convolutional network’s ability to extract subtle crack features without increasing inference costs. …”
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An Effective Feature Extraction Method for Tomato Leafminer - Tuta Absoluta (Meyrick) (Lepidoptera: Gelechiidae) Classification by Tahsin Uygun, Serhat Kiliçarslan, Cemil Közkurt, Mehmet Metin Ozguven

“…While excessive use of insecticides harms human health and environmental pollution, it also increases production costs, causes changes in the genetic structures of pests, causing them to become more resistant, and makes agricultural control difficult. …”
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