Laryngeal cancer diagnosis based on improved YOLOv8 algorithm by Xin Nie, Xueyan Zhang, Di Wang, Yuankun Liu, Lumin Xing, Wenjian Liu

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FlightScope: An Experimental Comparative Review of Aircraft Detection Algorithms in Satellite Imagery by Safouane El Ghazouali, Arnaud Gucciardi, Francesca Venturini, Nicola Venturi, Michael Rueegsegger, Umberto Michelucci

“…While deep learning algorithms are constantly evolving, they have been mostly implemented and tested on popular ground-taken photos. …”
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Optimization of the Naive Bayes Algorithm with SMOTETomek Combination for Imbalance Class Fraud Detection by Arief Tri Arsanto, Arif Faizin, Moch lutfi, Zulfatun Nikmatus Saadah

“…Dataset analysis needs to be carried out to analyze the history of transactions that have been carried out. In the fraud detection dataset, it can be seen that there are attributes that cause data imbalance. …”
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A Low-Latency Dynamic Object Detection Algorithm Fusing Depth and Events by Duowen Chen, Liqi Zhou, Chi Guo

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YOLOv-MA: A High-Precision Foreign Object Detection Algorithm for Rice by Jiahui Wang, Mengdie Jiang, Tauseef Abbas, Hao Chen, Yuying Jiang

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Energy-Efficient Fall-Detection System Using LoRa and Hybrid Algorithms by Manny Villa, Eduardo Casilari

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An improved air conditioner label defect detection algorithm based on SURF features by Huizi ZHOU, Yuelin LIU, Qing LIU, Jianwu LI

“…Aiming at the bottleneck that deep learning algorithms are not compatible with device detection and new sample collection,as well as poor detection timeliness and generalization ability,a traditional template matching detection algorithm based on SURF features was proposed. …”
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Deep Learning for Early Earthquake Detection: Application of Convolutional Neural Networks for P-Wave Detection by Dauren Zhexebay, Alisher Skabylov, Margulan Ibraimov, Serik Khokhlov, Aldiyar Agishev, Gulnur Kudaibergenova, Aibala Orazakova, Almansur Agishev

“…In contrast, traditional methods such as the short-term average/long-term average (STA/LTA) algorithm and the Akaike information criterion (AIC) have limitations in detecting primary (P) waves in high-noise conditions, caused by industrial and anthropogenic disturbances. …”
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Person re-identification algorithm by image from video surveilance sistem using a neural network compound descriptor by S. A. Ihnatsyeva, R. P. Bohush

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Alfalfa stem count estimation using remote sensing imagery and machine learning on Google Earth Engine by Hazhir Bahrami, Karem Chokmani, Saeid Homayouni, Viacheslav I. Adamchuk, Md Saifuzzaman, Rami Albasha, Maxime Leduc

“…This study aims to propose a framework for estimating alfalfa stem density using satellite imagery and machine learning (ML) algorithms, which can lead to winter mortality detection early in the spring and provide a better understanding of potential total dry matter. …”
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Simulation of automatic intrusion detection in university networks by using neural network algorithms by Houdun Xu

“…Preprocess the collected data and use neural network algorithms to design appropriate network structures and parameters. …”
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Hypertension Detection Using Passive-Aggressive Algorithm With The PA-I And PA-II Methods by M. Hafidz Ariansyah, Sri Winarno

“…This algorithm can work well for learning by transforming data and dealing with unbalanced classification problems. …”
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A dual-phase deep learning framework for advanced phishing detection using the novel OptSHQCNN approach by Srikanth Meda, Vangipuram Sesha Srinivas, Killi Chandra Bhushana Rao, Repudi Ramesh, Narasimha Rao Yamarthi

“…Deep Learning (DL), which can precisely learn the intrinsic features of the websites and recognize phishing websites, is one of the innovative techniques utilized to solve this issue. …”
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A novel deep learning algorithm for real-time prediction of clinical deterioration in the emergency department for a multimodal clinical decision support system by Arom Choi, Kwanhyung Lee, Heejung Hyun, Kwang Joon Kim, Byungeun Ahn, Kyung Hyun Lee, Sangchul Hahn, So Yeon Choi, Ji Hoon Kim

“…Additionally, predictive accuracy improved with the inclusion of continuous data input at shorter intervals. This study suggests the feasibility of using AI algorithms in diverse clinical scenarios, particularly for earlier detection of clinical deterioration. …”
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JASBO: Jaya Average Subtraction Based Optimization with Deep Learning Model for Multi-Classification of Infectious Disease from Unstructured Data by Vian Sabeeh, Ahmed Bahaaulddin A. Alwahhab, Ali Abdulmunim Ibrahim Al-kharaz

“…In this research, proposed Jaya Average Subtraction Based Optimization (JASBO), which is enabled by Deep Learning (DL) is used to classify infectious diseases into many categories from unstructured data. …”
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AI-Driven Predictive Modeling for Lung Cancer Detection and Management Using Synthetic Data Augmentation and Random Forest Classifier by Nisreen Innab, Asma Aldrees, Dina Abdulaziz AlHammadi, Abeer Hakeem, Muhammad Umer, Shtwai Alsubai, Silvia Trelova, Imran Ashraf

“…The application of machine learning algorithms enables medical researchers to examine large amounts of data accurately, which leads to the development of precise and effective treatment approaches. …”
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A hybrid approach using support vector machine rule-based system: detecting cyber threats in internet of things by M. Wasim Abbas Ashraf, Arvind R. Singh, A. Pandian, Rajkumar Singh Rathore, Mohit Bajaj, Ievgen Zaitsev

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Robust development of data-driven models for methane and hydrogen mixture solubility in brine by Kashif Saleem, Abhinav Kumar, K. D. V. Prasad, Ahmad Alkhayyat, T. Ramachandran, Protyay Dey, Navdeep Kaur, R. Sivaranjani, I. B. Sapaev, Mehrdad Mottaghi

“…In this paper, we aim to form robust data-driven intelligent algorithms founded on various machine learning methods of Support Vector Machine, Random Forest, AdaBoost, Decision Tree, K-nearest Neighbors, Multilayer Perceptron Artificial Neural Network and Convolutional Neural Network to model solubility of hydrogen/methane blend in brine under realistic conditions of underground hydrogen storage projects by utilizing an experimental dataset collected from the existing body of published research. …”
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Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning by Christopher Kormpos, Fotios Zantalis, Stylianos Katsoulis, Grigorios Koulouras

“…The intersection of medical image classification and deep learning has garnered increasing research interest, particularly in the context of breast tumor detection using ultrasound images. …”
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RESEARCH ON DEEP NEURAL NETWORK LEARNING BASED ON IMPROVED BP ALGORITHM by HUANG Pei

“…Deep learning can make the computing model that contains a number of processing layers to learn the data that contains many levels of abstract representation.This kind of learning way in the most advanced speech recognition,visual object recognition,object detection and many other areas,such as biology,genetics and medicine brought significant improvement.Deep learning can find the complex structure of large data,and the convolution neural network as one of the important models of the depth study in the processing of voice,image,video and text,and other aspects of a new breakthrough.It is the use of BP algorithm to guide the machine how to get the error before the layer to adjust the parameters of this layer,so that these parameters are more conducive to the calculation of the model.In view of the shortcomings of traditional BP algorithm,a fast BP algorithm is proposed,which has the disadvantages of slow convergence speed and often falls into local minimum points.The improved convolutional neural network is used to validate the data set MNIST,English character recognition and medical image.The simulation results show the effectiveness of the proposed algorithm.…”
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