VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…Convolution Neural Networks (CNN) are best in their ability to detect rice diseases but still face challenges in generalizing equally well for all classes of disease in multiclass classification. …”
Get full text

Deep Learning-Based Pulmonary Nodule Screening: A Narrative Review by Abhishek Mahajan, Ujjwal Agarwal, Rajat Agrawal, Aditi Venkatesh, Shreya Shukla, K S. S. Bharadwaj, M L. V. Apparao, Vivek Pawar, Vivek Poonia

“…Given its capacity to generate three-dimensional pictures, computed tomography is the most effective means of detecting lung nodules with more excellent resolution of detected nodules. …”
Get full text

Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids by Yanfei Li, Juejing Liu, Xiaodong Zhao, Wenjun Liu, Tong Geng, Ang Li, Xin Zhang

“…Notably, MTL models show superior accuracy compared to binary classification convolutional neural networks. Additionally, introducing a tailored cross‐entropy loss function improves MTL model performance. …”
Get full text

SMART HYBRID MODELS FOR IMPROVED BREAST CANCER DETECTION by Nageswara Rao Gali, Panduranga Vital Terlapu, Yasaswini Mandavakuriti, Sai Manoj Somu, Madhavi Varanasi, Vijay Telugu, Maheswara Rao V V R

“…Breast cancer (BC) ranks the second most prevalent cancer among women globally and is the leading cause of female mortality. …”
Get full text

A Novel Dual-Stream Attention-Based Hybrid Network for Solar Power Forecasting by Rafiq Asghar, Michele Quercio, Lorenzo Sabino, Assia Mahrouch, Francesco Riganti Fulginei

“…This research introduces a novel dual-steam hybrid model that uses Bidirectional Long-Short Term Memory (BiLSTM) and Convolutional Neural Networks (CNN) to predict PV power production. …”
Get full text

An advanced CNN-attention model with IFTTA optimization for prediction air consumption of relay nozzles by Shen Min, Shao Ning, Cao Yongbo, Xiong Xiaoshuang, Yang Xuezheng, Wang Zhen, Yu Lianqing

“…This paper proposes a Convolutional Neural Network (CNN)-Attention regression model to predict air consumption of the relay nozzle, enhancing accuracy and efficiency with an Improved Football Team Training Algorithm (IFTTA). …”
Get full text

Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis by Ji Soo Park, Sa-Yoon Park, Jae Won Moon, Kwangsoo Kim, Dong In Suh

“…Convolutional neural networks were the predominant ML model, often combined with recurrent neural networks or residual network architectures. …”
Get full text

Coffee Leaf Rust Disease Detection and Implementation of an Edge Device for Pruning Infected Leaves via Deep Learning Algorithms by Raka Thoriq Araaf, Arkar Minn, Tofael Ahamed

“…Currently, pesticide spraying is considered the most effective solution for mitigating coffee leaf rust. …”
Get full text

Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review by Catarina Sousa Santos, Mário Amorim-Lopes

“…Results From 4023 deduplicated abstracts and 636 full-text reviews, 56 studies (2018–2022) met the inclusion criteria, covering diverse cancer types and applications. Convolutional neural networks were most prevalent, demonstrating high performance, followed by gradient- and decision tree-based algorithms. …”
Get full text

A Lightweight Direction-Aware Network for Vehicle Detection by Luxia Yang, Yilin Hou, Hongrui Zhang, Chuanghui Zhang

“…Moreover, to further reduce model parameters and computational requirements, a lightweight shared convolutional detection head (SCL-Head) is devised using a parameter-sharing mechanism. …”
Get full text

Deep Learning for Connectivity Identification in Random Subsurface Flows: A Methodological Workflow for Early Solute Arrival Time Quantification by A. Manzoni, F. P. J. deBarros, G. M. Porta, M. Riva, A. Guadagnini

“…Our methodology is based on a two‐stage approach that combines Convolutional Neural Networks (CNN) and Multi‐Layer Perceptron (MLP) techniques. …”
Get full text

Building Damage Detection Using Deep Learning Architecture with Satellite Images: The Case of the 6 February 2023 Kahramanmaraş Earthquake by Zeynep Aygün, Merve Kocaman, Salih Aydemir, Berkant Konakoğlu

“…The Kahramanmaraş earthquake on February 6, 2023, was one of the most devastating in recent years, causing extensive damage and loss. …”
Get full text

CD-CTFM: A Lightweight CNN-Transformer Network for Remote Sensing Cloud Detection Fusing Multiscale Features by Wenxuan Ge, Xubing Yang, Rui Jiang, Wei Shao, Li Zhang

“…Hence, cloud detection is a necessary preprocessing procedure. However, most existing methods have numerous calculations and parameters. …”
Get full text

GCAFlow: Multi-Scale Flow-Based Model with Global Context-Aware Channel Attention for Industrial Anomaly Detection by Lin Liao, Congde Lu, Yujie Gao, Hao Yu, Biao Cai

“…In addition, we design a hierarchical convolutional subnetwork to improve the probabilistic modeling capacity of the flow-based framework. …”
Get full text

Brain-Inspired Architecture for Spiking Neural Networks by Fengzhen Tang, Junhuai Zhang, Chi Zhang, Lianqing Liu

“…The proposed network integrates the input-encoding process into the spiking neural network architecture via convolutional operations such that the network can accept the real-valued input and automatically transform it into spikes for further processing. …”
Get full text

Multilevel Feature Gated Fusion Based Spatial and Frequency Domain Attention Network for Joint Classification of Hyperspectral and LiDAR Data by Cuiping Shi, Zhipeng Zhong, Shihang Ding, Yeqi Lei, Liguo Wang, Zhan Jin

“…First, extract multilevel convolutional features from hyperspectral and LiDAR images and adaptively fuse them through a gating mechanism. …”
Get full text

Intelligent Fault Diagnosis of Inter-Turn Short Circuit Faults in PMSMs for Agricultural Machinery Based on Data Fusion and Bayesian Optimization by Mingsheng Wang, Wuxuan Lai, Hong Zhang, Yang Liu, Qiang Song

“…In this article, a multi-source data-fusion algorithm based on convolutional neural networks (CNNs) has been proposed for the early fault diagnosis of ITSCs. …”
Get full text

Hybrid Darknet53-SVM model with random grid search optimization for enhanced colorectal cancer histological image classification by Pragati Patharia, Prabira Kumar Sethy, K. Lakshmipathi Raju, Anita Khanna, Ashoka Kumar Ratha, Santi Kumari Behera, Aziz Nanthaamornphong

“…Initially, 18 pre-trained Convolutional Neural Networks (CNNs) were evaluated using transfer learning techniques. …”
Get full text

Multimodal fusion transformer network for multispectral pedestrian detection in low-light condition by Gong Li, Guoyin Ren, Jingyu Wang, Mobing Zhi, Zhijie Yu, Bo Jiang, Haoliang Guan, Qidan Guo

“…Abstract Multispectral pedestrian detection has attracted significant attention owing to its advantages, such as providing rich information, adapting to various scenes, enhancing features, and diversifying applications. However, most existing fusion methods are based on convolutional neural network (CNN) feature fusion. …”
Get full text

Remaining Useful Life Prediction for Pressurized Fluid Pipelines Based on Acoustic Emission Monitoring and an Adaptive Fuzzy Similarity Measure by Duc-Thuan Nguyen, Tuan-Khai Nguyen, Zahoor Ahmad, Jong-Myon Kim

“…Pressurized fluid pipelines are among the most crucial components in industrial settings. Operating under high pressure leads to pipeline susceptibility to cracking, rupture, and significant damage. …”
Get full text