Semi-supervised machine learning for primary user emulation attack detection and prevention through core-based analytics for cognitive radio networks by Sundar Srinivasan, KB Shivakumar, Muazzam Mohammad

“…Selfish attacks among other attacks are the most challenging, in which a secondary user or an unauthorized user with unlicensed spectrum pretends to be a primary user by altering the signal characteristics. …”
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Load Reconstruction Technique Using D-Optimal Design and Markov Parameters by Deepak K. Gupta, Anoop K. Dhingra

“…It has been noted that the computation of inverse Markov parameters, like most other inverse problems, is ill-conditioned which causes their convolution with the measured response to become quite sensitive to errors in system modeling and response measurements. …”
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GNN for LoRa Device Fingerprint Identification by Bojun Zhang

“…The system employs GGC(Gated Graph Convolution) networks to extract feature representations from the graphs, which are then encoded by a time encoder, specifically an LSTM(Long Short-Term Memory) network, to obtain a coarse-grained temporal representation. …”
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Stationary Underdispersed INAR(1) Models based on the Backward Approach by Emad-Eldin A. A. Aly, Nadjib Bouzar

“… Most of the stationary first-order autoregressive integer-valued (INAR(1)) models in the literature have been developed using the idea of binomial thinning. …”
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EcoDetect-YOLOv2: A High-Performance Model for Multi-Scale Waste Detection in Complex Surveillance Environments by Jing Su, Ruihan Chen, Mingzhi Li, Shenlin Liu, Guobao Xu, Zanhong Zheng

“…To reduce computational overhead and inference latency without sacrificing detection accuracy, Ghost Convolution (GhostConv) replaces conventional convolution layers within the neck. …”
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Transformers for Neuroimage Segmentation: Scoping Review by Maya Iratni, Amira Abdullah, Mariam Aldhaheri, Omar Elharrouss, Alaa Abd-alrazaq, Zahiriddin Rustamov, Nazar Zaki, Rafat Damseh

“…The most developed were those of hybrid convolutional neural network-transformer architectures (n=57, 85.07%), where the vision transformer is the most frequently used type of transformer (n=37, 55.22%). …”
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Evaluation of the Effectiveness of the UNet Model with Different Backbones in the Semantic Segmentation of Tomato Leaves and Fruits by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa, Julieta Raquel Hernandez Vidales

“…This task is accomplished through training various models of Convolutional Neural Networks. This paper presents a comparative analysis of semantic segmentation performance using a convolutional neural network model with different backbone architectures. …”
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Breath Detection from a Microphone Using Machine Learning by Tomasz Sankowski, Piotr Sulewski, Jan Walczak, Aleksandra Bruska

“…Spectrogram Classification Using Convolutional Neural Networks: This approach involves classifying spectrograms of half-second or quarter-second audio segments using a convolutional neural network adapted for image classification tasks. 3. …”
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A Framework for Breast Cancer Classification with Deep Features and Modified Grey Wolf Optimization by Fathimathul Rajeena P.P, Sara Tehsin

“…Breast cancer is the most common disease in women, with 287,800 new cases and 43,200 deaths in 2022 across United States. …”
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Analysis of Students’ Role Perceptions and their Tendencies in Classroom Education Based on Visual Inspection by Lanlan Jiang

“…A multi example learning student engagement assessment method based on a one-dimensional convolutional neural network is proposed. Based on the conceptual composition of student engagement, head posture, eye gaze, and eye-opening and closing states and the most used facial movement units are used as visual features. …”
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Deep learning-integrated MRI brain tumor analysis: feature extraction, segmentation, and Survival Prediction using Replicator and volumetric networks by Deependra Rastogi, Prashant Johri, Massimo Donelli, Seifedine Kadry, Arfat Ahmad Khan, Giuseppe Espa, Paola Feraco, Jungeun Kim

“…Abstract The most prevalent form of malignant tumors that originate in the brain are known as gliomas. …”
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Tuberculosis detection with customized CNN and oversampling techniques: a deep learning approach by B. H. Shekar, Shazia Mannan

“…Tuberculosis has been with us since time immemorial, and although being treatable and curable, it remains one of the world’s most infectious malady, killing millions each year. …”
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Estimating Bandwidth and Analyzing Worst-Case Delay Bounds Using Network Calculus by Md Amirul Islam, Giovanni Stea

“…Our approach models available bandwidth as a service curve and employs min-plus algebra-specifically, convolution and deconvolution operations-to derive end-to-end predictions from individual link characteristics. …”
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Logatome and Sentence Recognition Related to Acoustic Parameters of Enclosures by Jedrzej KOCIŃSKI, Edward OZIMEK

“…On this base, the following objective parameters of the enclosure were determined: Reverberation Time (RT), Early Decay Time (EDT), Weighted Clarity (C50) and Speech Transmission Index (STI). A convolution of the IRs with logatome tests and the Polish Sentence Test (PST) was made. …”
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Effectiveness of the Spatial Domain Techniques in Digital Image Steganography by Rosshini Selvamani, Yusliza Yusoff

“…In addition to using statistics as a foundation, convolution neural networks (CNN), generative adversarial networks (GAN), coverless approaches, and machine learning are all used to construct steganographic methods. …”
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A YOLOv8 algorithm for safety helmet wearing detection in complex environment by Chunning Song, Yinzhong Li

“…Abstract Helmets are the most common protective equipment on construction sites and can effectively reduce head injuries caused by falling objects. …”
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A Combined Deep CNN: LSTM with a Random Forest Approach for Breast Cancer Diagnosis by Almas Begum, V. Dhilip Kumar, Junaid Asghar, D. Hemalatha, G. Arulkumaran

“…The most predominant kind of disease that is normal among ladies is breast cancer. …”
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Explore human parsing modality for action recognition by Jinfu Liu, Runwei Ding, Yuhang Wen, Nan Dai, Fanyang Meng, Fang‐Lue Zhang, Shen Zhao, Mengyuan Liu

“…The first human pose branch feeds robust skeletons in the graph convolutional network to model pose features, while the second human parsing branch also leverages depictive parsing feature maps to model parsing features via convolutional backbones. …”
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Development of Robust CNN Architecture for Grading and Classification of Renal Cell Carcinoma Histology Images by Amit Kumar Chanchal, Shyam Lal, Shilpa Suresh

“…Kidney cancer is a commonly diagnosed cancer disease in recent years, and Renal Cell Carcinoma (RCC) is the most common kidney cancer responsible for 80% to 85% of all renal tumors. …”
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Inference of Gene Regulatory Networks for Breast Cancer Based on Genetic Modules by Yihao Chen, Ling Guo, Yue Pan, Hui Cai, Zhitong Bing

“…This new method combining genetic modules and convolutional neural networks is presented to infer GRNs from the RNA sequencing data of breast cancer. …”
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