CoroYOLO: a novel colorectal cancer detection method based on the Mamba framework by Wenfei Chen, Fengrui Hou, Yika Shen

“…Colorectal cancer (CRC) is one of the most common malignant tumors worldwide, and early detection is crucial for improving cure rates. …”
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Seg-Eigen-CAM: Eigen-Value-Based Visual Explanations for Semantic Segmentation Models by Ching-Ting Chung, Josh Jia-Ching Ying

“…In recent years, most Explainable Artificial Intelligence methods have primarily focused on image classification. …”
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FruitNet: Lightweight CNN for High-Throughput Image-Based Fruit Yield Estimation by Yadav Kamlesh Kumar, Tandan Gajendra

“…Innovations in this work include the most lightweight Convolutional Neural Network (CNN) named FruitNet proposed for achieving high throughput and image based estimation offrait yield. …”
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Task-Related EEG as a Biomarker for Preclinical Alzheimer’s Disease: An Explainable Deep Learning Approach by Ziyang Li, Hong Wang, Lei Li

“…Task-related EEG has been rarely used in Alzheimer’s disease research, as most studies have focused on resting-state EEG. An interpretable deep learning framework—Interpretable Convolutional Neural Network (InterpretableCNN)—was utilized to identify AD-related EEG features. …”
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IchthyNet: An Ensemble Method for the Classification of In Situ Marine Zooplankton Shadowgraph Images by Brittney Slocum, Bradley Penta

“…This study explores the use of machine learning for the automated classification of the ten most abundant groups of marine organisms (in the size range of 5–12 cm) plus marine snow found in the ecosystem of the U.S. east coast. …”
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Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP. by Sajid Mehmood, Rashid Amin, Jamal Mustafa, Mudassar Hussain, Faisal S Alsubaei, Muhammad D Zakaria

“…We propose to implement both MLP (Multilayer Perceptron) and CNN (Convolutional Neural Networks) based on conventional methods to detect the Denial of Services (DDoS) attack. …”
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Enhanced Transformer Network With High-Dimensional Attention Mechanism for Diabetic Retinopathy Classification by M. Rizvana, Sathiya Narayanan

“…Prominent among them are Convolutional Neural Networks (CNN), Recurrent Neural Networks, Generative Adversarial Networks, and the Vision Transformer (ViT). …”
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Deblurring Method of Face Recognition AI Technology Based on Deep Learning by Weilong Li, Jie Li, Junhui Zhou

“…As a common method of deep learning, a convolutional neural network (CNN) shows excellent performance in face recognition. …”
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Performance Comparison of ResNet50, VGG16, and MobileNetV2 for Brain Tumor Classification on MRI Images by Muhammad Bayu Kurniawan, Ema Utami

“…This study aims to compare the performance of three Convolutional Neural Network (CNN) models—ResNet50, VGG16, and MobileNetV2—for brain tumor classification based on MRI images. …”
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CNN Performance Improvement for Classifying Stunted Facial Images Using Early Stopping Approach by Yunidar Yunidar, Y Yusni, N Nasaruddin, Fitri Arnia

“…The main aim of this research is to identify the CNN model that is most effective in differentiating facial images of stunted children from normal children. …”
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Protein homodimers structure prediction based on deep neural network by A. Y. Hadarovich, A. A. Kalinouski, A. V. Tuzikov

“…Homodimers (complexes which consist of two identical proteins) are the most common type of protein complexes in nature but there is still no universal algorithm to predict their 3D structures. …”
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An Investigation on Prediction of Infrastructure Asset Defect with CNN and ViT Algorithms by Nam Lethanh, Tu Anh Trinh, Mir Tahmid Hossain

“…Convolutional Neural Networks (CNNs) have been demonstrated to be one of the most powerful methods for image recognition, being applied in many fields, including civil and structural health monitoring in infrastructure asset management. …”
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Progression risk of adolescent idiopathic scoliosis based on SHAP-Explained machine learning models: a multicenter retrospective study by Xinyi Fang, Ting Weng, Zhehao Zhang, Wanfeng Gong, Yu Zhang, Mei Wang, Jianhua Wang, Zhongxiang Ding, Can Lai

“…Abstract Objective To develop an interpretable machine learning model, explained using SHAP, based on imaging features of adolescent idiopathic scoliosis extracted by convolutional neural networks (CNNs), in order to predict the risk of curve progression and identify the most accurate predictive model. …”
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Analyzing spatiotemporal variation in suspended particulate matter in lakes using remote sensing by WEI Junyan, ZHAO Yiming, HAO Yanling, JIA Xiaoxue, MA Xinyan

“…The most accurate model was selected to estimate SPM concentrations across the lake.…”
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Digitization of Medical Device Displays Using Deep Learning Models: A Comparative Study by Pedro Ferreira, Pedro Lobo, Filipa Reis, João L. Vilaça, Pedro Morais

“…In addition to these comparisons, we also explore a hybrid approach that combines the YOLOv8l model for object detection with a Convolutional Neural Network (CNN) for classification. …”
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Maize and soybean yield prediction using machine learning methods: a systematic literature review by Ramandeep Kumar Sharma, Jasleen Kaur, Gary Feng, Yanbo Huang, Chandan Kumar, Yi Wang, Sandhir Sharma, Johnie Jenkins, Jagmandeep Dhillon

“…The Random Forest (RF), Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), and Extreme Gradient Boosting (XG-Boost) were identified as the mostly used ML algorithms. Most often applied deep learning techniques include long short-term memory (LSTM) and convolutional neural networks (CNNs). …”
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Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review by Aijing Luo, Wei Chen, Hongtao Zhu, Wenzhao Xie, Xi Chen, Zhenjiang Liu, Zirui Xin

“…In terms of model type, deep learning, represented by convolutional neural networks, was most frequently applied (14/23, 61%). …”
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Prior Waveform Guided Network (PWGN) for Laser Detection in Fog by Haowei Zhu, Long Wu, Xu Yang, Lu Xu, Shuyu Chen, Yong Zhang, Jianlong Zhang, Chenghua Yang, Wei Zhang

“…With the rapid development of autonomous vehicles and mobile robotics, lidar has been one of the most popular researches in the world. But the poor ranging accuracy and detection range in the foggy situation have limited the application of lidar. …”
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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…Classification is one of the most prominent modeling approaches that can be successfully applied in model-based medical support systems to make more accurate diagnostic decisions. …”
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Contrasted Trends in Chlorophyll‐a Satellite Products by Etienne Pauthenet, Elodie Martinez, Thomas Gorgues, Joana Roussillon, Lucas Drumetz, Ronan Fablet, Maïlys Roux

“…To assess if these trends can be related to changes in the environment or to bias in radiometric products, a convolutional neural network is used to examine the relationship between physical ocean variables versus Schl. …”
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