DeepBiteNet: A Lightweight Ensemble Framework for Multiclass Bug Bite Classification Using Image-Based Deep Learning by Doston Khasanov, Halimjon Khujamatov, Muksimova Shakhnoza, Mirjamol Abdullaev, Temur Toshtemirov, Shahzoda Anarova, Cheolwon Lee, Heung-Seok Jeon

“…Our model aggregates three semantically diverse convolutional neural networks—DenseNet121, EfficientNet-B0, and MobileNetV3-Small—using a stacked meta-classifier designed to aggregate their predicted outcomes into an integrated, discriminatively strong output. …”
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Slim-sugarcane: a lightweight and high-precision method for sugarcane node detection and edge deployment in natural environments by Lijiao Wei, Lijiao Wei, Shuo Wang, Xinwei Liang, Dongjie Du, Xinyi Huang, Ming Li, Yuangang Hua, Weihua Huang, Zhenhui Zheng, Zhenhui Zheng

“…The proposed method exhibits superior accuracy and computational efficiency compared to existing approaches, offering a promising solution for precision agriculture and intelligent sugarcane cultivation.…”
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Category semantic and global relation distillation for object detection by Yanpeng LIANG, Zhonggui MA, Zongjie WANG, Zhuo LI

“…Compared with other baseline methods, the proposed approach achieved competitive improvements in mean average precision without considerably increasing the number of parameters and FLOPS during distillation training, thereby striking a better balance between accuracy and efficiency.…”
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An Optimised CNN Hardware Accelerator Applicable to IoT End Nodes for Disruptive Healthcare by Arfan Ghani, Akinyemi Aina, Chan Hwang See

“…Addressing the challenges posed by constrained dataset sizes, compute-intensive AI algorithms, and hardware limitations, the approach presented in this paper leverages efficient image augmentation and pre-processing techniques to enhance both prediction accuracy and the training efficiency. …”
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Chaotic moving video quality enhancement based on deep in-loop filtering by Tong Tang, Yi Yang, Dapeng Wu, Ruyan Wang, Zhidu Li

“…The in-loop filter in VVC inherits the De-Blocking Filter (DBF) and Sample Adaptive Offset (SAO) of High Efficiency Video Coding (HEVC, H.265), and adds the Adaptive Loop Filter (ALF) to minimize the error between the original sample and the decoded sample. …”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…The core of our methodology involves a novel algorithm featuring an Efficient-Unet based Deep Learning model for the precise segmentation of NSR areas. …”
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Leveraging Large Language Models for Departmental Classification of Medical Records by Baha Ihnaini, Xintong Zeng, Handi Yan, Feige Fang, Abdur Rashid Sangi

“…The models utilize medical records as a dataset for fine-tuning and use clinical knowledge bases to enhance accuracy and efficiency in identifying appropriate departments. This study explores the integration of advanced large language models (LLMs) with quantized low-rank adaptation (QLoRA) for efficient training. …”
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A Robust H.264/AVC Video Watermarking Scheme with Drift Compensation by Xinghao Jiang, Tanfeng Sun, Yue Zhou, Wan Wang, Yun-Qing Shi

“…Malicious attacks with different quantization parameters (QPs) or motion estimation algorithms can be resisted efficiently, with 80% accuracy on average after lossy compression.…”
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A fast monocular 6D pose estimation method for textureless objects based on perceptual hashing and template matching by Jose Moises Araya-Martinez, Jose Moises Araya-Martinez, Vinicius Soares Matthiesen, Vinicius Soares Matthiesen, Simon Bøgh, Jens Lambrecht, Rui Pimentel de Figueiredo

“…Additionally, our algorithm efficiently utilizes all CPU cores and includes adjustable parameters for balancing computation time and accuracy, making it suitable for a wide range of applications where hardware cost and power efficiency are critical. …”
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FloodNet-Lite: A Lightweight Deep Learning for Flood Mapping Using Remote Sensing Data With Optimized UNet and Edge Deployment Approach in 6G by Puviyarasi Thirugnanasammandamoorthi, Debabrata Ghosh, Ram Kishan Dewangan, Mohammad Kamrul Hasan, Khairul Akram Zainol Ariffin, Huda Saleh Abbas, Hashim Elshafie, Rashid A. Saeed, Ala Eldin Awouda

“…The system integrates an optimized UNet architecture with MobileNetV3 as a backbone, enhanced by depthwise separable convolutions, attention mechanisms, and advanced model compression techniques, such as quantization-aware training and structured pruning. Knowledge distillation transfers learning from a high-capacity teacher model to a compact student model, while self-supervised learning further reduces dependency on labeled data to boost efficiency and robustness. …”
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Reinforcement learning energy management control strategy of electric tractor based on condition identification by Liqiao Li, Jiangchun Chen, Jing Nie, Zongyu Gao

“…However, low traction efficiency, short battery life, and high energy consumption are the main reasons hindering the industrialization of ET. …”
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Digital identification and adulteration analysis of Codonopsis Radix and Stellariae Radix based on the “digital identity” of chemical compositions by Xianrui Wang, Jiating Zhang, Wenguang Jing, Xiaohan Guo, Minghua Li, Xianlong Cheng, Feng Wei

“…Finally, the above “digital identities” of CR and SR were used as benchmarks for matching positive samples and market samples to provide feedback on the matching credibility (MC) for identification and adulteration analysis.ResultsThe results showed that based on the “digital identities” of CR and SR, the digital identification of CR, SR, and positive samples can be realized at the individual level of TCM efficiently and accurately, even if 3% of SR in the mixed samples can still be identified efficiently and accurately. …”
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Accelerating Streaming Subgraph Matching via Vector Databases by Liuyi Chen, Yi Ding, Xushuo Tang, Fangyue Chen, Siyuan Gong, Xu Zhou, Zhengyi Yang

“…The streaming subgraph matching problem, an extension of this task, aims to efficiently process queries in a stream with minimal latency. …”
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Embedded Sensor Data Fusion and TinyML for Real-Time Remaining Useful Life Estimation of UAV Li Polymer Batteries by Jutarut Chaoraingern, Arjin Numsomran

“…The accurate real-time estimation of the remaining useful life (RUL) of lithium-polymer (LiPo) batteries is a critical enabler for ensuring the safety, reliability, and operational efficiency of unmanned aerial vehicles (UAVs). Nevertheless, achieving such prognostics on resource-constrained embedded platforms remains a considerable technical challenge. …”
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Voice-activated home automation system for IoT edge devices using TinyML by Timothy Malche, Sandeep Budhani, Pramod Kumar Soni, Govind Murari Upadhyay

“…The results show that our keyword spotting model is both highly accurate and efficient and uses minimum computational resources. …”
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Real-Time Dolphin Whistle Detection on Raspberry Pi Zero 2 W with a TFLite Convolutional Neural Network by Rocco De Marco, Francesco Di Nardo, Alessandro Rongoni, Laura Screpanti, David Scaradozzi

“…This work achieved a critical balance between computational efficiency and detection fidelity (F1-score: 86.9%) by leveraging quantized, multithreaded inference. …”
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Text-Guided Synthesis in Medical Multimedia Retrieval: A Framework for Enhanced Colonoscopy Image Classification and Segmentation by Ojonugwa Oluwafemi Ejiga Peter, Opeyemi Taiwo Adeniran, Adetokunbo MacGregor John-Otumu, Fahmi Khalifa, Md Mahmudur Rahman

“…The validation accuracy of various classification models Big Transfer (BiT), Fixed Resolution Residual Next Generation Network (FixResNeXt), and Efficient Neural Network (EfficientNet) were 92%, 91%, and 86%, respectively. …”
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Video matching method based on "bag of words" by LI Yuan-ning1, LIU Ting1, JIANG Shu-qiang1, HUANG Qing-ming1

“…A "bag of words" was presented based method for video representation and matching.First,all local features of all video frames were quantized into a dictionary of visual words.Then each sub-shot of the video was represented by a set of visual words.Finally,a revered index of visual words was created to speed the matching process of video clips.This method not only takes local appearance and spatial information into account,but also compresses the representation of video content.Highly competitive experimental results show that our proposed method is more effective and efficient than former methods for video matching in large video dataset.…”
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Relationship Study on Land Use Spatial Distribution Structure and Energy-Related Carbon Emission Intensity in Different Land Use Types of Guangdong, China, 1996–2008 by Yi Huang, Bin Xia, Lei Yang

“…The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective.…”
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Embedded Artificial Intelligence for IoT Applications Using the MAX78000 by Martina Balbi, Lance Doherty, Thomas Watteyne

“…This enables developers to create efficient, real-time AI solutions, highlighting the transformative potential of embedded AI in IoT.…”
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